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Author SHA1 Message Date
Clair Blacketer 1e0360980a fixing missing documentation 2025-03-06 20:22:19 -05:00
Clair Blacketer a00afcd6ef closes #533 2025-03-06 12:29:35 -05:00
Clair Blacketer 4b96b13b55 closes #504 2025-03-06 11:48:31 -05:00
Clair Blacketer 4c707cdd64 closes #498 2025-03-06 11:42:51 -05:00
Clair Blacketer 7cc1ad81ac closes #496 2025-03-06 11:40:53 -05:00
Clair Blacketer 0ca99109dc closes #479 2025-03-06 11:34:04 -05:00
Clair Blacketer 014b50fcda fixes #676 2025-03-06 11:22:38 -05:00
Clair Blacketer 4a08b6276e adds concept_ancestor description
closes #664
2025-03-06 11:09:45 -05:00
Clair Blacketer 71474f855b adding concept_synonym info
closes #663
2025-03-06 11:00:05 -05:00
Clair Blacketer 7921e51b32 Add relationship table description
closes #662
2025-03-06 10:56:35 -05:00
clairblacketer ab8a55dfa3
Merge pull request #540 from MaximMoinat/er-diagram
OMOP CDM ER Diagram challenge 2022
2025-03-06 09:32:45 -05:00
Clair Blacketer b60f4f43dd Fixing v6.0 admitted_from_concept_id and source_value
closes #700
2025-03-06 09:30:58 -05:00
Clair Blacketer 8e7f8d48ca Fix misspelling ot observation period
closes #701
2025-03-06 09:23:36 -05:00
Clair Blacketer b4d867c5f1 Merge branch 'main' of https://github.com/OHDSI/CommonDataModel 2025-03-06 09:21:41 -05:00
Clair Blacketer 766171a6a3 Update CDM_source documentation
closes #673
2025-03-06 09:21:33 -05:00
clairblacketer d2dddc5318
Merge pull request #699 from wardle/main
Standardise case of integer datatype avoiding use of both 'integer' and 'Integer' for field datatypes
2025-03-06 09:17:30 -05:00
clairblacketer 4e14518681
Merge branch 'main' into main 2025-03-06 09:16:40 -05:00
clairblacketer f8c78f882c
Merge pull request #469 from OHDSI/v5.4_conversions
CDM v5.3 to v5.4 conversion scripts
2025-03-06 09:14:41 -05:00
Clair Blacketer 225f5e5a7e Merge branch 'main' of https://github.com/OHDSI/CommonDataModel 2025-03-06 09:13:42 -05:00
Clair Blacketer 9f098edced fixing incorrect links to cdm531 2025-03-06 09:11:39 -05:00
clairblacketer 863898b883
Merge pull request #705 from eroell/patch-1
Typos in `condition_occurrence` User Guide
2025-03-06 09:06:11 -05:00
clairblacketer ab08bea1af
Merge branch 'main' into patch-1 2025-03-06 09:05:51 -05:00
clairblacketer eecba279eb
Merge pull request #730 from MaximMoinat/fix-729
Remove reference to value_as_datetime from documentation
2025-03-06 08:59:40 -05:00
clairblacketer 76d3701a6f
Merge branch 'main' into fix-729 2025-03-06 08:59:23 -05:00
clairblacketer 033253f49a
Merge pull request #718 from lawrenceadams/lawrenceadams-fix-54-docs-links
Fix dead 5.3.1 CDM links
2025-03-06 08:41:52 -05:00
Maxim Moinat bbc3fb9f74
remove reference to value_as_datetime 2025-02-21 08:30:41 +01:00
Maxim Moinat 696cf58b5a
fix typo 2025-02-20 21:11:38 +01:00
Maxim Moinat 9b5f756648
Merge pull request #694 from OHDSI/MaximMoinat-patch-2
Remove drug end date convention
2025-02-20 20:03:09 +01:00
Clair Blacketer 561c93dc65 Revert "docs update"
This reverts commit 330c087340.
2025-01-07 12:38:59 -05:00
Clair Blacketer 330c087340 docs update 2024-12-16 15:20:57 -05:00
Clair Blacketer c914c1ac65 Update CRAN-SUBMISSION 2024-10-15 15:23:54 -04:00
Lawrence Adams 720b5480e9 fix: data model conventions dead links 2024-10-02 08:14:53 +01:00
Lawrence Adams 080816f659 fix: deadlinks in 5.4 rendered docs 2024-10-02 08:13:35 +01:00
Lawrence Adams c84042399c fix: dead links for 5.4 docs source csvs 2024-10-02 08:13:13 +01:00
Clair Blacketer 17b2d139c7 Cran submission Oct 2024 2024-10-01 13:22:32 -04:00
Clair Blacketer 41253286a7 Adding CRAN comments for submission 2024-09-30 18:58:24 -04:00
Clair Blacketer b53e7da8fe Editing description for newest release of package 2024-09-30 18:44:11 -04:00
Eljas Roellin b437f60f1b undo changes to htmls 2024-07-22 18:11:27 +02:00
Eljas Roellin bf335b87ff Merge branch 'patch-1' of github.com:eroell/CommonDataModel into patch-1 2024-07-22 18:09:21 +02:00
Eljas Roellin 1de5a4b0f7 fix typos in .csv s 2024-07-22 18:08:50 +02:00
Eljas Roellin ce456b4971
Fix typo in cdm60.html 2024-07-22 16:20:21 +02:00
Eljas Roellin 990531b3b2
Fix typo in cdm53.html 2024-07-22 16:19:31 +02:00
Eljas Roellin feb0b7964d
Fix typos cdm54.html 2024-07-22 16:11:18 +02:00
Maxim Moinat abe75876ae
render cdm specs 2024-06-14 16:11:28 +02:00
Mark Wardle af17663f67 Standardise case of integer datatype
The CDM datatype column uses a mixture of 'integer' and 'Integer'. All other datatypes only use lowercase.
2024-06-09 21:58:29 +01:00
Maxim Moinat ad666fdd9d
remove drug end date convention 2024-06-06 17:31:54 +02:00
Maxim Moinat 0c07bfe881
add option to only include subset of tables 2022-12-01 13:59:57 +01:00
Maxim Moinat 759270d000
create ER diagram from OMOP CDM specification 2022-11-30 16:12:26 +01:00
AnthonyMolinaro c4ab611981
Update bigquery_migration.sql 2022-03-04 13:08:46 -05:00
AnthonyMolinaro 4ac3d61c6f
Update impala_migration.sql 2022-03-04 13:08:30 -05:00
AnthonyMolinaro 074bd288f8
Update netezza_migration.sql 2022-03-04 13:07:48 -05:00
AnthonyMolinaro 65166e4bd7
Update oracle_migration.sql 2022-03-04 13:07:29 -05:00
AnthonyMolinaro e10628d954
Update postgresql_migration.sql 2022-03-04 13:07:10 -05:00
AnthonyMolinaro bdb5789d4a
Update sqlserver_migration.sql 2022-03-04 13:05:50 -05:00
AnthonyMolinaro 2c61a520fb
Update redshift_migration.sql
Typo in measurement - column should be unit_source_concept_id, not unit_source_id
2022-03-04 13:00:26 -05:00
AnthonyMolinaro 64a8fd6645 Script to assist in migration from 6.0 to 5.4 2022-01-27 16:23:19 -05:00
AnthonyMolinaro 2456c66c62 CDM v5.3 to v5.4 conversion scripts, initial commit 2022-01-06 16:08:16 -05:00
32 changed files with 17087 additions and 531 deletions

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@ -1,3 +1,3 @@
Version: 0.2.0
Date: 2024-02-06 20:13:33 UTC
SHA: d152472484fb2bedd2596e2279a24afbd0084f0b
Version: 1.0.1
Date: 2024-10-01 17:22:58 UTC
SHA: 17b2d139c7e982c33cd8abb2ea7db0cd104e756a

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@ -1,8 +1,11 @@
Package: CommonDataModel
Type: Package
Title: OMOP CDM DDL and Documentation Generator
Version: 0.2.0
Author: Clair Blacketer [aut, cre]
Version: 1.0.1
Authors@R: person(given = "Clair",
family = "Blacketer",
role = c("aut", "cre"),
email = "mblacke@its.jnj.com")
Maintainer: Clair Blacketer <mblacke@its.jnj.com>
Description: Generates the scripts required to create an Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) database and associated documentation for supported database platforms. Leverages the 'SqlRender' package to convert the Data Definition Language (DDL) script written in parameterized Structured Query Language (SQL) to the other supported dialects.
License: Apache License 2.0

10
NEWS.md Normal file
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@ -0,0 +1,10 @@
CommonDataModel v5.4.2
======================
Bigfixes:
1. Removed package test that was causing issues with downstream dependencies (test-BuildRelease.R)
Documentation:
1. Updated documentation for the OMOP Common Data Model based on the April Olympians 2024 initiative.

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@ -1,13 +1,12 @@
One test was removed due to its restricting of downstream dependencies.
## R CMD check results
* This is a new release
# Update based on reviewer feedback
- turned off tests when environment variables are not set
- removed vignetteBuilder field from DESCRIPTION
- added return values in function documentation
- updated buildRelease.R default output folder to tempdir()
There were no ERRORs or WARNINGs.
0 errors | 0 warnings | 0 notes
## Comments from reviewer
Edited the author field in the DESCRIPTION file.

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@ -13,7 +13,7 @@
<title>OMOP CDM v5.3</title>
<script src="site_libs/header-attrs-2.25/header-attrs.js"></script>
<script src="site_libs/header-attrs-2.27/header-attrs.js"></script>
<script src="site_libs/jquery-3.6.0/jquery-3.6.0.min.js"></script>
<meta name="viewport" content="width=device-width, initial-scale=1" />
<link href="site_libs/bootstrap-3.3.5/css/cosmo.min.css" rel="stylesheet" />
@ -985,7 +985,7 @@ gender_source_concept_id
Due to the small number of options, this tends to be zero.
</td>
<td style="text-align:left;">
If the source data codes asigned sex at birth in a non-standard
If the source data codes assigned sex at birth in a non-standard
vocabulary, store the concept_id here.
</td>
<td style="text-align:left;">
@ -3455,16 +3455,14 @@ entry is stored with only the corresponding SOURCE_CONCEPT_ID and
DRUG_SOURCE_VALUE and a DRUG_CONCEPT_ID of 0. The Drug Concept with the
most detailed content of information is preferred during the mapping
process. These are indicated in the CONCEPT_CLASS_ID field of the
Concept and are recorded in the following order of precedence:
<d2>Marketed Product<d3>, <d2>Branded Pack<d3>, <d2>Clinical Pack<d3>,
<d2>Branded Drug<d3>, <d2>Clinical Drug<d3>, <d2>Branded Drug
Component<d3>, <d2>Clinical Drug Component<d3>, <d2>Branded Drug
Form<d3>, <d2>Clinical Drug Form<d3>, and only if no other information
is available <d2>Ingredient<d3>. Note: If only the drug class is known,
the DRUG_CONCEPT_ID field should contain 0. <a
Concept and are recorded in the following order of precedence: <20>Marketed
Product<EFBFBD>, <20>Branded Pack<63>, <20>Clinical Pack<63>, <20>Branded Drug<75>, <20>Clinical
Drug<EFBFBD>, <20>Branded Drug Component<6E>, <20>Clinical Drug Component<6E>, <20>Branded
Drug Form<72>, <20>Clinical Drug Form<72>, and only if no other information is
available <20>Ingredient<6E>. Note: If only the drug class is known, the
DRUG_CONCEPT_ID field should contain 0. <a
href="https://athena.ohdsi.org/search-terms/terms?domain=Drug&amp;standardConcept=Standard&amp;page=1&amp;pageSize=15&amp;query=">Accepted
Concepts</a>.
</d3></d2></d3></d2></d3></d2></d3></d2></d3></d2></d3></d2></d3></d2></d3></d2></d3></d2></d3></d2>
</td>
<td style="text-align:left;">
integer
@ -3552,23 +3550,8 @@ the patient.
</td>
<td style="text-align:left;">
If this information is not explicitly available in the data, infer the
end date using the following methods:<br><br> 1. Start first with
duration or days supply using the calculation drug start date + days
supply -1 day. 2. Use quantity divided by daily dose that you may obtain
from the sig or a source field (or assumed daily dose of 1) for solid,
indivisibile, drug products. If quantity represents ingredient amount,
quantity divided by daily dose * concentration (from drug_strength) drug
concept id tells you the dose form. 3. If it is an administration
record, set drug end date equal to drug start date. If the record is a
written prescription then set end date to start date + 29. If the record
is a mail-order prescription set end date to start date + 89. The end
date must be equal to or greater than the start date. Ibuprofen 20mg/mL
oral solution concept tells us this is oral solution. Calculate duration
as quantity (200 example) * daily dose (5mL) /concentration (20mg/mL)
200*5/20 = 50 days. <a
href="https://ohdsi.github.io/CommonDataModel/drug_dose.html">Examples
by dose form</a><br><br>For detailed conventions for how to populate
this field, please see the <a
end date from start date and duration.<br>For detailed conventions for
how to populate this field, please see the <a
href="https://ohdsi.github.io/Themis/tag_drug_exposure.html">THEMIS
repository</a>.
</td>
@ -5294,8 +5277,8 @@ concept mapped from the source value which represents a measurement.
</td>
<td style="text-align:left;">
The CONCEPT_ID that the MEASUREMENT_SOURCE_VALUE maps to. Only records
whose source values map to concepts with a domain of <d2>Measurement<d3>
should go in this table. </d3></d2>
whose source values map to concepts with a domain of <EFBFBD>Measurement<EFBFBD>
should go in this table.
</td>
<td style="text-align:left;">
integer
@ -5898,13 +5881,13 @@ Procedure, Drug, Specimen, Measurement or Device should be stored in the
Observation table. Observations can be stored as attribute value pairs,
with the attribute as the Observation Concept and the value representing
the clinical fact. This fact can be a Concept (stored in
VALUE_AS_CONCEPT), a numerical value (VALUE_AS_NUMBER), a verbatim
string (VALUE_AS_STRING), or a datetime (VALUE_AS_DATETIME). Even though
Observations do not have an explicit result, the clinical fact can be
stated separately from the type of Observation in the VALUE_AS_* fields.
It is recommended for Observations that are suggestive statements of
positive assertion should have a value of Yes (concept_id=4188539),
recorded, even though the null value is the equivalent.</p>
VALUE_AS_CONCEPT), a numerical value (VALUE_AS_NUMBER) or a verbatim
string (VALUE_AS_STRING). Even though Observations do not have an
explicit result, the clinical fact can be stated separately from the
type of Observation in the VALUE_AS_* fields. It is recommended for
Observations that are suggestive statements of positive assertion should
have a value of Yes (concept_id=4188539), recorded, even though the
null value is the equivalent.</p>
<table class="table table-condensed table-hover" style="font-size: 13px; margin-left: auto; margin-right: auto;">
<thead>
<tr>

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@ -13,7 +13,7 @@
<title>OMOP CDM v5.4</title>
<script src="site_libs/header-attrs-2.25/header-attrs.js"></script>
<script src="site_libs/header-attrs-2.27/header-attrs.js"></script>
<script src="site_libs/jquery-3.6.0/jquery-3.6.0.min.js"></script>
<meta name="viewport" content="width=device-width, initial-scale=1" />
<link href="site_libs/bootstrap-3.3.5/css/cosmo.min.css" rel="stylesheet" />
@ -715,7 +715,7 @@ Person. This field should not be used to study gender identity issues.
Use the gender or sex value present in the data under the assumption
that it is the biological sex at birth. If the source data captures
gender identity it should be stored in the <a
href="https://ohdsi.github.io/CommonDataModel/cdm531.html#observation">OBSERVATION</a>
href="https://ohdsi.github.io/CommonDataModel/cdm54.html#observation">OBSERVATION</a>
table. <a
href="http://athena.ohdsi.org/search-terms/terms?domain=Gender&amp;standardConcept=Standard&amp;page=1&amp;pageSize=15&amp;query=">Accepted
gender concepts</a>. Please refer to the <a
@ -939,7 +939,7 @@ should capture the last known location of the person.
</td>
<td style="text-align:left;">
Put the location_id from the <a
href="https://ohdsi.github.io/CommonDataModel/cdm531.html#location">LOCATION</a>
href="https://ohdsi.github.io/CommonDataModel/cdm54.html#location">LOCATION</a>
table here that represents the most granular location information for
the person. For additional information on how to populate this field,
please refer to the <a
@ -974,7 +974,7 @@ Practitioner).
</td>
<td style="text-align:left;">
Put the provider_id from the <a
href="https://ohdsi.github.io/CommonDataModel/cdm531.html#provider">PROVIDER</a>
href="https://ohdsi.github.io/CommonDataModel/cdm54.html#provider">PROVIDER</a>
table of the last known general practitioner of the person. If there are
multiple providers, it is up to the ETL to decide which to put here.
</td>
@ -1093,7 +1093,7 @@ gender_source_concept_id
Due to the small number of options, this tends to be zero.
</td>
<td style="text-align:left;">
If the source data codes asigned sex at birth in a non-standard
If the source data codes assigned sex at birth in a non-standard
vocabulary, store the concept_id here.
</td>
<td style="text-align:left;">
@ -1266,7 +1266,7 @@ occurrence or the first high quality occurrence of a Clinical Event
(Condition, Drug, Procedure, Device, Measurement, Visit) is defined as
the start of the OBSERVATION_PERIOD record, and the end date of the last
occurrence of last high quality occurrence of a Clinical Event, or the
end of the database period becomes the end of the OBSERVATOIN_PERIOD for
end of the database period becomes the end of the OBSERVATION_PERIOD for
each Person. If a Person only has a single Clinical Event the
OBSERVATION_PERIOD record can be as short as one day. Depending on these
definitions it is possible that Clinical Events fall outside the time
@ -1379,7 +1379,7 @@ insurance claim data, the Observation Period can be considered as the
time period the Person is enrolled with a payer. If a Person switches
plans but stays with the same payer, and therefore capturing of data
continues, that change would be captured in <a
href="https://ohdsi.github.io/CommonDataModel/cdm531.html#payer_plan_period">PAYER_PLAN_PERIOD</a>.
href="https://ohdsi.github.io/CommonDataModel/cdm54.html#payer_plan_period">PAYER_PLAN_PERIOD</a>.
</td>
<td style="text-align:left;">
date
@ -1879,7 +1879,7 @@ PROCEDURE_OCCURRENCE, etc.) or in the VISIT_DETAIL table.
If there are multiple providers associated with a visit, you will need
to choose which one to put here. The additional providers can be stored
in the <a
href="https://ohdsi.github.io/CommonDataModel/cdm531.html#visit_detail">VISIT_DETAIL</a>
href="https://ohdsi.github.io/CommonDataModel/cdm54.html#visit_detail">VISIT_DETAIL</a>
table.
</td>
<td style="text-align:left;">
@ -2594,7 +2594,7 @@ OMOP supported vocabulary put the concept id representing the source
value here.
</td>
<td style="text-align:left;">
Integer
integer
</td>
<td style="text-align:left;">
No
@ -2628,7 +2628,7 @@ Concepts</a>. If a person was admitted from home or was self-referred,
set this to 0.
</td>
<td style="text-align:left;">
Integer
integer
</td>
<td style="text-align:left;">
No
@ -2858,21 +2858,21 @@ identifying Persons who should suffer from the recorded Condition.
Record all conditions as they exist in the source data. Any decisions
about diagnosis/phenotype definitions would be done through cohort
specifications. These cohorts can be housed in the <a
href="https://ohdsi.github.io/CommonDataModel/cdm531.html#payer_plan_period">COHORT</a>
href="https://ohdsi.github.io/CommonDataModel/cdm54.html#payer_plan_period">COHORT</a>
table. Conditions span a time interval from start to end, but are
typically recorded as single snapshot records with no end date. The
reason is twofold: (i) At the time of the recording the duration is not
known and later not recorded, and (ii) the Persons typically cease
interacting with the healthcare system when they feel better, which
leads to incomplete capture of resolved Conditions. The <a
href="https://ohdsi.github.io/CommonDataModel/cdm531.html#condition_era">CONDITION_ERA</a>
href="https://ohdsi.github.io/CommonDataModel/cdm54.html#condition_era">CONDITION_ERA</a>
table addresses this issue. Family history and past diagnoses (history
of) are not recorded in this table. Instead, they are listed in the <a
href="https://ohdsi.github.io/CommonDataModel/cdm531.html#observation">OBSERVATION</a>
href="https://ohdsi.github.io/CommonDataModel/cdm54.html#observation">OBSERVATION</a>
table. Codes written in the process of establishing the diagnosis, such
as question of of and rule out, should not represented here.
Instead, they should be recorded in the <a
href="https://ohdsi.github.io/CommonDataModel/cdm531.html#observation">OBSERVATION</a>
href="https://ohdsi.github.io/CommonDataModel/cdm54.html#observation">OBSERVATION</a>
table, if they are used for analyses. However, this information is not
always available.</p>
<p><strong>ETL Conventions</strong></p>
@ -3579,16 +3579,14 @@ entry is stored with only the corresponding SOURCE_CONCEPT_ID and
DRUG_SOURCE_VALUE and a DRUG_CONCEPT_ID of 0. The Drug Concept with the
most detailed content of information is preferred during the mapping
process. These are indicated in the CONCEPT_CLASS_ID field of the
Concept and are recorded in the following order of precedence:
<d2>Marketed Product<d3>, <d2>Branded Pack<d3>, <d2>Clinical Pack<d3>,
<d2>Branded Drug<d3>, <d2>Clinical Drug<d3>, <d2>Branded Drug
Component<d3>, <d2>Clinical Drug Component<d3>, <d2>Branded Drug
Form<d3>, <d2>Clinical Drug Form<d3>, and only if no other information
is available <d2>Ingredient<d3>. Note: If only the drug class is known,
the DRUG_CONCEPT_ID field should contain 0. <a
Concept and are recorded in the following order of precedence: Marketed
Product, Branded Pack, Clinical Pack, Branded Drug, Clinical Drug,
Branded Drug Component, Clinical Drug Component, Branded Drug Form,
Clinical Drug Form, and only if no other information is available
Ingredient. Note: If only the drug class is known, the DRUG_CONCEPT_ID
field should contain 0. <a
href="https://athena.ohdsi.org/search-terms/terms?domain=Drug&amp;standardConcept=Standard&amp;page=1&amp;pageSize=15&amp;query=">Accepted
Concepts</a>.
</d3></d2></d3></d2></d3></d2></d3></d2></d3></d2></d3></d2></d3></d2></d3></d2></d3></d2></d3></d2>
</td>
<td style="text-align:left;">
integer
@ -3676,23 +3674,8 @@ the patient.
</td>
<td style="text-align:left;">
If this information is not explicitly available in the data, infer the
end date using the following methods:<br><br> 1. Start first with
duration or days supply using the calculation drug start date + days
supply -1 day. 2. Use quantity divided by daily dose that you may obtain
from the sig or a source field (or assumed daily dose of 1) for solid,
indivisibile, drug products. If quantity represents ingredient amount,
quantity divided by daily dose * concentration (from drug_strength) drug
concept id tells you the dose form. 3. If it is an administration
record, set drug end date equal to drug start date. If the record is a
written prescription then set end date to start date + 29. If the record
is a mail-order prescription set end date to start date + 89. The end
date must be equal to or greater than the start date. Ibuprofen 20mg/mL
oral solution concept tells us this is oral solution. Calculate duration
as quantity (200 example) * daily dose (5mL) /concentration (20mg/mL)
200*5/20 = 50 days. <a
href="https://ohdsi.github.io/CommonDataModel/drug_dose.html">Examples
by dose form</a><br><br>For detailed conventions for how to populate
this field, please see the <a
end date from start date and duration.<br>For detailed conventions for
how to populate this field, please see the <a
href="https://ohdsi.github.io/Themis/tag_drug_exposure.html">THEMIS
repository</a>.
</td>
@ -3982,7 +3965,10 @@ route_concept_id
</td>
<td style="text-align:left;">
The standard CONCEPT_ID that the ROUTE_SOURCE_VALUE maps to in the route
domain.
domain. This is meant to represent the route of administration of the
drug. <a
href="https://athena.ohdsi.org/search-terms/terms?domain=Route&amp;standardConcept=Standard&amp;page=1&amp;pageSize=15&amp;query=">Accepted
Concepts</a>
</td>
<td style="text-align:left;">
integer
@ -4267,18 +4253,20 @@ expected resulting amount and unit then it should be a measurement.
Phlebotomy is a procedure but so trivial that it tends to be rarely
captured. It can be assumed that there is a phlebotomy procedure
associated with many lab tests, therefore it is unnecessary to add them
as separate procedures. If the user finds the same procedure over
concurrent days, it is assumed those records are part of a procedure
lasting more than a day. This logic is in lieu of the
procedure_end_date, which will be added in a future version of the
CDM.</p>
as separate procedures.</p>
<p><strong>ETL Conventions</strong></p>
<p>When dealing with duplicate records, the ETL must determine whether
to sum them up into one record or keep them separate. Things to consider
are: - Same Procedure - Same PROCEDURE_DATETIME - Same Visit Occurrence
or Visit Detail - Same Provider - Same Modifier for Procedures. Source
codes and source text fields mapped to Standard Concepts of the
Procedure Domain have to be recorded here.</p>
are:</p>
<ul>
<li>Same Procedure</li>
<li>Same procedure_datetime</li>
<li>Same Visit Occurrence or Visit Detail</li>
<li>Same Provider</li>
<li>Same Modifier for Procedures.</li>
</ul>
<p>Source codes and source text fields mapped to Standard Concepts of
the Procedure Domain have to be recorded here.</p>
<table class="table table-condensed table-hover" style="font-size: 13px; margin-left: auto; margin-right: auto;">
<thead>
<tr>
@ -5080,9 +5068,8 @@ You can use the TYPE_CONCEPT_ID to denote the provenance of the record,
as in whether the record is from administrative claims or EHR.
</td>
<td style="text-align:left;">
Choose the drug_type_concept_id that best represents the provenance of
the record, for example whether it came from a record of a prescription
written or physician administered drug. <a
Choose the device_type_concept_id that best represents the provenance of
the record. <a
href="https://athena.ohdsi.org/search-terms/terms?domain=Type+Concept&amp;standardConcept=Standard&amp;page=1&amp;pageSize=15&amp;query=">Accepted
Concepts</a>. A more detailed explanation of each Type Concept can be
found on the <a
@ -5604,8 +5591,8 @@ concept mapped from the source value which represents a measurement.
</td>
<td style="text-align:left;">
The CONCEPT_ID that the MEASUREMENT_SOURCE_VALUE maps to. Only records
whose source values map to concepts with a domain of <d2>Measurement<d3>
should go in this table. </d3></d2>
whose source values map to concepts with a domain of <EFBFBD>Measurement<EFBFBD>
should go in this table.
</td>
<td style="text-align:left;">
integer
@ -5763,7 +5750,8 @@ from =.
Operators are =, &gt; and these concepts belong to the Meas Value
Operator domain. <a
href="https://athena.ohdsi.org/search-terms/terms?domain=Meas+Value+Operator&amp;standardConcept=Standard&amp;page=1&amp;pageSize=15&amp;query=">Accepted
Concepts</a>. Leave it NULL if theres an exact numeric value given
Concepts</a>. The operator_concept_id explictly refers to the value of
the measurement. Leave it NULL if theres an exact numeric value given
(instead of putting =) or theres no numeric value at all.
</td>
<td style="text-align:left;">
@ -6304,13 +6292,13 @@ Procedure, Drug, Specimen, Measurement or Device should be stored in the
Observation table. Observations can be stored as attribute value pairs,
with the attribute as the Observation Concept and the value representing
the clinical fact. This fact can be a Concept (stored in
VALUE_AS_CONCEPT), a numerical value (VALUE_AS_NUMBER), a verbatim
string (VALUE_AS_STRING), or a datetime (VALUE_AS_DATETIME). Even though
Observations do not have an explicit result, the clinical fact can be
stated separately from the type of Observation in the VALUE_AS_* fields.
It is recommended for Observations that are suggestive statements of
positive assertion should have a value of Yes (concept_id=4188539),
recorded, even though the null value is the equivalent.</p>
VALUE_AS_CONCEPT), a numerical value (VALUE_AS_NUMBER) or a verbatim
string (VALUE_AS_STRING). Even though Observations do not have an
explicit result, the clinical fact can be stated separately from the
type of Observation in the VALUE_AS_* fields. It is recommended for
Observations that are suggestive statements of positive assertion should
have a value of Yes (concept_id=4188539), recorded, even though the
null value is the equivalent.</p>
<table class="table table-condensed table-hover" style="font-size: 13px; margin-left: auto; margin-right: auto;">
<thead>
<tr>
@ -6616,7 +6604,7 @@ result in a source_data but without mapping, set value_as_concept_id to
0.
</td>
<td style="text-align:left;">
Integer
integer
</td>
<td style="text-align:left;">
No
@ -6971,7 +6959,7 @@ this field is the primary key of the linked record.
<td style="text-align:left;">
Put the primary key of the linked record, if applicable, here. See the
<a
href="https://ohdsi.github.io/CommonDataModel/cdm60.html#observation">ETL
href="https://ohdsi.github.io/CommonDataModel/cdm54.html#observation">ETL
Conventions for the OBSERVATION</a> table for more details.
</td>
<td style="text-align:left;">
@ -12867,8 +12855,10 @@ No
source_documentation_reference
</td>
<td style="text-align:left;">
Refers to a publication or web resource describing the source data
</td>
<td style="text-align:left;">
e.g. a data dictionary.
</td>
<td style="text-align:left;">
varchar(255)
@ -12877,12 +12867,12 @@ varchar(255)
No
</td>
<td style="text-align:left;">
No
</td>
<td style="text-align:left;">
No
</td>
<td style="text-align:left;">
No
</td>
<td style="text-align:left;">
</td>
@ -13178,7 +13168,7 @@ domain_id
</td>
<td style="text-align:left;">
A foreign key to the <a
href="https://ohdsi.github.io/CommonDataModel/cdm531.html#domain">DOMAIN</a>
href="https://ohdsi.github.io/CommonDataModel/cdm54.html#domain">DOMAIN</a>
table the Concept belongs to.
</td>
<td style="text-align:left;">
@ -13207,7 +13197,7 @@ vocabulary_id
</td>
<td style="text-align:left;">
A foreign key to the <a
href="https://ohdsi.github.io/CommonDataModel/cdm531.html#vocabulary">VOCABULARY</a>
href="https://ohdsi.github.io/CommonDataModel/cdm54.html#vocabulary">VOCABULARY</a>
table indicating from which source the Concept has been adapted.
</td>
<td style="text-align:left;">
@ -14078,10 +14068,18 @@ No
<h3 class="tabset tabset-pills">relationship</h3>
<p><strong>Table Description</strong></p>
<p>The RELATIONSHIP table provides a reference list of all types of
relationships that can be used to associate any two concepts in the
CONCEPT_RELATIONSHP table.</p>
relationships that can be used to associate any two Concepts in the
CONCEPT_RELATIONSHIP table, the respective reverse relationships, and
their hierarchical characteristics. Note, that Concepts representing
relationships between the clinical facts, used for filling in the
FACT_RELATIONSHIP table are stored in the CONCEPT table and belong to
the Relationship Domain.</p>
<p><strong>User Guide</strong></p>
<p>NA</p>
<p>Users can leverage the RELATIONSHIP table to explore the full list of
direct and reverse relationships within the OMOP vocabulary system.
Also, users can get insight into how these relationships can be used in
ETL, cohort creation, and other tasks according to their ancestral
characteristics.</p>
<p><strong>ETL Conventions</strong></p>
<p>NA</p>
<table class="table table-condensed table-hover" style="font-size: 13px; margin-left: auto; margin-right: auto;">
@ -14256,7 +14254,7 @@ relationship_concept_id
</td>
<td style="text-align:left;">
A foreign key that refers to an identifier in the <a
href="https://ohdsi.github.io/CommonDataModel/cdm531.html#concept">CONCEPT</a>
href="https://ohdsi.github.io/CommonDataModel/cdm54.html#concept">CONCEPT</a>
table for the unique relationship concept.
</td>
<td style="text-align:left;">
@ -14285,10 +14283,17 @@ CONCEPT
<div id="concept_synonym" class="section level3 tabset tabset-pills">
<h3 class="tabset tabset-pills">concept_synonym</h3>
<p><strong>Table Description</strong></p>
<p>The CONCEPT_SYNONYM table is used to store alternate names and
descriptions for Concepts.</p>
<p>The CONCEPT_SYNONYM table captures alternative terms, synonyms, and
translations of Concept Name into various languages linked to specific
concepts, providing users with a comprehensive view of how Concepts may
be expressed or referenced.</p>
<p><strong>User Guide</strong></p>
<p>NA</p>
<p>Users can leverage the CONCEPT_SYNONYM table to expand search
capabilities and improve query accuracy by incorporating synonymous
terms into data analysis and retrieval processes. Also, users can
enhance their mapping efforts between local terminologies and
standardized concepts by identifying synonymous terms associated with
concepts in the CONCEPT_SYNONYM table.</p>
<p><strong>ETL Conventions</strong></p>
<p>NA</p>
<table class="table table-condensed table-hover" style="font-size: 13px; margin-left: auto; margin-right: auto;">
@ -14410,18 +14415,26 @@ CONCEPT
<p>The CONCEPT_ANCESTOR table is designed to simplify observational
analysis by providing the complete hierarchical relationships between
Concepts. Only direct parent-child relationships between Concepts are
stored in the CONCEPT_RELATIONSHIP table. To determine higher level
stored in the CONCEPT_RELATIONSHIP table. To determine higher-level
ancestry connections, all individual direct relationships would have to
be navigated at analysis time. The CONCEPT_ANCESTOR table includes
records for all parent-child relationships, as well as
grandparent-grandchild relationships and those of any other level of
lineage. Using the CONCEPT_ANCESTOR table allows for querying for all
descendants of a hierarchical concept. For example, drug ingredients and
drug products are all descendants of a drug class ancestor.</p>
<p>This table is entirely derived from the CONCEPT, CONCEPT_RELATIONSHIP
and RELATIONSHIP tables.</p>
lineage for Standard or Classification concepts. Using the
CONCEPT_ANCESTOR table allows for querying for all descendants of a
hierarchical concept, and the other way around. For example, drug
ingredients and drug products, beneath them in the hierarchy, are all
descendants of a drug class ancestor. This table is entirely derived
from the CONCEPT, CONCEPT_RELATIONSHIP, and RELATIONSHIP tables.</p>
<p><strong>User Guide</strong></p>
<p>NA</p>
<p>The CONCEPT_ANCESTOR table can be used to explore the hierarchical
relationships captured in the table to gain insights into the
hierarchical structure of clinical concepts. Understanding the
hierarchical relationships of concepts can facilitate accurate
interpretation and analysis of healthcare data. Also, by incorporating
hierarchical relationships from the CONCEPT_ANCESTOR table, users can
create cohorts containing related concepts within a hierarchical
structure, enabling more comprehensive cohort definitions.</p>
<p><strong>ETL Conventions</strong></p>
<p>NA</p>
<table class="table table-condensed table-hover" style="font-size: 13px; margin-left: auto; margin-right: auto;">

View File

@ -13,7 +13,7 @@
<title>Changes by Table</title>
<script src="site_libs/header-attrs-2.25/header-attrs.js"></script>
<script src="site_libs/header-attrs-2.27/header-attrs.js"></script>
<script src="site_libs/jquery-3.6.0/jquery-3.6.0.min.js"></script>
<meta name="viewport" content="width=device-width, initial-scale=1" />
<link href="site_libs/bootstrap-3.3.5/css/cosmo.min.css" rel="stylesheet" />
@ -645,6 +645,12 @@ a table or field</li>
<li>No change</li>
</ul>
</div>
<div id="provider" class="section level2">
<h2>PROVIDER</h2>
<ul>
<li>No change</li>
</ul>
</div>
<div id="cost" class="section level2">
<h2>COST</h2>
<ul>

File diff suppressed because it is too large Load Diff

View File

@ -603,7 +603,7 @@ the same Concept between releases of the Standardized Vocabularies.</li>
<li>A descriptive name for each Concept is stored as the Concept Name as
part of the CONCEPT table. Additional names and descriptions for the
Concept are stored as Synonyms in the <a
href="https://ohdsi.github.io/CommonDataModel/cdm531.html#concept_synonym">CONCEPT_SYNONYM</a>
href="https://ohdsi.github.io/CommonDataModel/cdm54.html#concept_synonym">CONCEPT_SYNONYM</a>
table.</li>
<li>Each Concept is assigned to a Domain. For Standard Concepts, there
is always a single Domain. Source Concepts can be composite or
@ -631,7 +631,7 @@ participate in the construction of the CONCEPT_ANCESTOR table and can be
used to identify Descendants that may appear in the data. See
CONCEPT_ANCESTOR table. Non-standard Concepts can only appear in
*_source_concept_id fields and are not used in <a
href="https://ohdsi.github.io/CommonDataModel/cdm531.html#concept_ancestor">CONCEPT_ANCESTOR</a>
href="https://ohdsi.github.io/CommonDataModel/cdm54.html#concept_ancestor">CONCEPT_ANCESTOR</a>
table. Please refer to the Standardized Vocabularies specifications for
details of the Standard Concept designation.</li>
<li>The lifespan of a Concept is recorded through its valid_start_date,
@ -760,12 +760,12 @@ concept_id_1 and concept_id_2 fields.</li>
<li>Concept Relationships define direct relationships between Concepts.
Indirect relationships through 3rd Concepts are not captured in this
table. However, the <a
href="https://ohdsi.github.io/CommonDataModel/cdm531.html#concept_ancestor">CONCEPT_ANCESTOR</a>
href="https://ohdsi.github.io/CommonDataModel/cdm54.html#concept_ancestor">CONCEPT_ANCESTOR</a>
table does this for hierarchical relationships over several
“generations” of direct relationships.</li>
<li>In previous versions of the CDM, the relationship_id used to be a
numerical identifier. See the <a
href="https://ohdsi.github.io/CommonDataModel/cdm531.html#relationship">RELATIONSHIP</a>
href="https://ohdsi.github.io/CommonDataModel/cdm54.html#relationship">RELATIONSHIP</a>
table.</li>
</ul>
</div>
@ -790,7 +790,7 @@ purposes of creating a closed Information Model, where all entities in
the OMOP CDM are covered by unique Concepts.</li>
<li>Hierarchical Relationships are used to build a hierarchical tree out
of the Concepts, which is recorded in the <a
href="https://ohdsi.github.io/CommonDataModel/cdm531.html#concept_ancestor">CONCEPT_ANCESTOR</a>
href="https://ohdsi.github.io/CommonDataModel/cdm54.html#concept_ancestor">CONCEPT_ANCESTOR</a>
table. For example, “has_ingredient” is a Relationship between Concept
of the Concept Class Clinical Drug and those of Ingredient, and all
Ingredients can be classified as the “parental” hierarchical Concepts
@ -806,16 +806,16 @@ same Vocabulary or those adopted from different Vocabulary sources.</li>
<li>The concept_synonym_name field contains a valid Synonym of a
concept, including the description in the concept_name itself. I.e. each
Concept has at least one Synonym in the <a
href="https://ohdsi.github.io/CommonDataModel/cdm531.html#concept_synonym">CONCEPT_SYNONYM</a>
href="https://ohdsi.github.io/CommonDataModel/cdm54.html#concept_synonym">CONCEPT_SYNONYM</a>
table. As an example, for a SNOMED-CT Concept, if the fully specified
name is stored as the concept_name of the <a
href="https://ohdsi.github.io/CommonDataModel/cdm531.html#concept">CONCEPT</a>
href="https://ohdsi.github.io/CommonDataModel/cdm54.html#concept">CONCEPT</a>
table, then the Preferred Term and Synonyms associated with the Concept
are stored in the <a
href="https://ohdsi.github.io/CommonDataModel/cdm531.html#concept_synonym">CONCEPT_SYNONYM</a>
href="https://ohdsi.github.io/CommonDataModel/cdm54.html#concept_synonym">CONCEPT_SYNONYM</a>
table.</li>
<li>Only Synonyms that are active and current are stored in the <a
href="https://ohdsi.github.io/CommonDataModel/cdm531.html#concept_synonym">CONCEPT_SYNONYM</a>
href="https://ohdsi.github.io/CommonDataModel/cdm54.html#concept_synonym">CONCEPT_SYNONYM</a>
table. Tracking synonym/description history and mapping of obsolete
synonyms to current Concepts/Synonyms is out of scope for the Standard
Vocabularies.</li>
@ -827,12 +827,12 @@ Vocabularies.</li>
<ul>
<li>Each concept is also recorded as an ancestor of itself.</li>
<li>Only valid and Standard Concepts participate in the <a
href="https://ohdsi.github.io/CommonDataModel/cdm531.html#concept_ancestor">CONCEPT_ANCESTOR</a>
href="https://ohdsi.github.io/CommonDataModel/cdm54.html#concept_ancestor">CONCEPT_ANCESTOR</a>
table. It is not possible to find ancestors or descendants of deprecated
or Source Concepts.</li>
<li>Usually, only Concepts of the same Domain are connected through
records of the <a
href="https://ohdsi.github.io/CommonDataModel/cdm531.html#concept_ancestor">CONCEPT_ANCESTOR</a>
href="https://ohdsi.github.io/CommonDataModel/cdm54.html#concept_ancestor">CONCEPT_ANCESTOR</a>
table, but there might be exceptions.</li>
</ul>
</div>

View File

@ -0,0 +1,605 @@
erDiagram
PERSON {
person_id integer
gender_concept_id integer
year_of_birth integer
month_of_birth integer
day_of_birth integer
birth_datetime datetime
race_concept_id integer
ethnicity_concept_id integer
location_id integer
provider_id integer
care_site_id integer
person_source_value varchar
gender_source_value varchar
gender_source_concept_id integer
race_source_value varchar
race_source_concept_id integer
ethnicity_source_value varchar
ethnicity_source_concept_id integer
}
OBSERVATION_PERIOD {
observation_period_id integer
person_id integer
observation_period_start_date date
observation_period_end_date date
period_type_concept_id integer
}
VISIT_OCCURRENCE {
visit_occurrence_id integer
person_id integer
visit_concept_id integer
visit_start_date date
visit_start_datetime datetime
visit_end_date date
visit_end_datetime datetime
visit_type_concept_id Integer
provider_id integer
care_site_id integer
visit_source_value varchar
visit_source_concept_id integer
admitted_from_concept_id integer
admitted_from_source_value varchar
discharged_to_concept_id integer
discharged_to_source_value varchar
preceding_visit_occurrence_id integer
}
VISIT_DETAIL {
visit_detail_id integer
person_id integer
visit_detail_concept_id integer
visit_detail_start_date date
visit_detail_start_datetime datetime
visit_detail_end_date date
visit_detail_end_datetime datetime
visit_detail_type_concept_id integer
provider_id integer
care_site_id integer
visit_detail_source_value varchar
visit_detail_source_concept_id Integer
admitted_from_concept_id Integer
admitted_from_source_value varchar
discharged_to_source_value varchar
discharged_to_concept_id integer
preceding_visit_detail_id integer
parent_visit_detail_id integer
visit_occurrence_id integer
}
CONDITION_OCCURRENCE {
condition_occurrence_id integer
person_id integer
condition_concept_id integer
condition_start_date date
condition_start_datetime datetime
condition_end_date date
condition_end_datetime datetime
condition_type_concept_id integer
condition_status_concept_id integer
stop_reason varchar
provider_id integer
visit_occurrence_id integer
visit_detail_id integer
condition_source_value varchar
condition_source_concept_id integer
condition_status_source_value varchar
}
DRUG_EXPOSURE {
drug_exposure_id integer
person_id integer
drug_concept_id integer
drug_exposure_start_date date
drug_exposure_start_datetime datetime
drug_exposure_end_date date
drug_exposure_end_datetime datetime
verbatim_end_date date
drug_type_concept_id integer
stop_reason varchar
refills integer
quantity float
days_supply integer
sig varchar
route_concept_id integer
lot_number varchar
provider_id integer
visit_occurrence_id integer
visit_detail_id integer
drug_source_value varchar
drug_source_concept_id integer
route_source_value varchar
dose_unit_source_value varchar
}
PROCEDURE_OCCURRENCE {
procedure_occurrence_id integer
person_id integer
procedure_concept_id integer
procedure_date date
procedure_datetime datetime
procedure_end_date date
procedure_end_datetime datetime
procedure_type_concept_id integer
modifier_concept_id integer
quantity integer
provider_id integer
visit_occurrence_id integer
visit_detail_id integer
procedure_source_value varchar
procedure_source_concept_id integer
modifier_source_value varchar
}
DEVICE_EXPOSURE {
device_exposure_id integer
person_id integer
device_concept_id integer
device_exposure_start_date date
device_exposure_start_datetime datetime
device_exposure_end_date date
device_exposure_end_datetime datetime
device_type_concept_id integer
unique_device_id varchar
production_id varchar
quantity integer
provider_id integer
visit_occurrence_id integer
visit_detail_id integer
device_source_value varchar
device_source_concept_id integer
unit_concept_id integer
unit_source_value varchar
unit_source_concept_id integer
}
MEASUREMENT {
measurement_id integer
person_id integer
measurement_concept_id integer
measurement_date date
measurement_datetime datetime
measurement_time varchar
measurement_type_concept_id integer
operator_concept_id integer
value_as_number float
value_as_concept_id integer
unit_concept_id integer
range_low float
range_high float
provider_id integer
visit_occurrence_id integer
visit_detail_id integer
measurement_source_value varchar
measurement_source_concept_id integer
unit_source_value varchar
unit_source_concept_id integer
value_source_value varchar
measurement_event_id integer
meas_event_field_concept_id integer
}
OBSERVATION {
observation_id integer
person_id integer
observation_concept_id integer
observation_date date
observation_datetime datetime
observation_type_concept_id integer
value_as_number float
value_as_string varchar
value_as_concept_id Integer
qualifier_concept_id integer
unit_concept_id integer
provider_id integer
visit_occurrence_id integer
visit_detail_id integer
observation_source_value varchar
observation_source_concept_id integer
unit_source_value varchar
qualifier_source_value varchar
value_source_value varchar
observation_event_id integer
obs_event_field_concept_id integer
}
DEATH {
person_id integer
death_date date
death_datetime datetime
death_type_concept_id integer
cause_concept_id integer
cause_source_value varchar
cause_source_concept_id integer
}
NOTE {
note_id integer
person_id integer
note_date date
note_datetime datetime
note_type_concept_id integer
note_class_concept_id integer
note_title varchar
note_text varchar
encoding_concept_id integer
language_concept_id integer
provider_id integer
visit_occurrence_id integer
visit_detail_id integer
note_source_value varchar
note_event_id integer
note_event_field_concept_id integer
}
NOTE_NLP {
note_nlp_id integer
note_id integer
section_concept_id integer
snippet varchar
offset varchar
lexical_variant varchar
note_nlp_concept_id integer
note_nlp_source_concept_id integer
nlp_system varchar
nlp_date date
nlp_datetime datetime
term_exists varchar
term_temporal varchar
term_modifiers varchar
}
SPECIMEN {
specimen_id integer
person_id integer
specimen_concept_id integer
specimen_type_concept_id integer
specimen_date date
specimen_datetime datetime
quantity float
unit_concept_id integer
anatomic_site_concept_id integer
disease_status_concept_id integer
specimen_source_id varchar
specimen_source_value varchar
unit_source_value varchar
anatomic_site_source_value varchar
disease_status_source_value varchar
}
FACT_RELATIONSHIP {
domain_concept_id_1 integer
fact_id_1 integer
domain_concept_id_2 integer
fact_id_2 integer
relationship_concept_id integer
}
LOCATION {
location_id integer
address_1 varchar
address_2 varchar
city varchar
state varchar
zip varchar
county varchar
location_source_value varchar
country_concept_id integer
country_source_value varchar
latitude float
longitude float
}
CARE_SITE {
care_site_id integer
care_site_name varchar
place_of_service_concept_id integer
location_id integer
care_site_source_value varchar
place_of_service_source_value varchar
}
PROVIDER {
provider_id integer
provider_name varchar
npi varchar
dea varchar
specialty_concept_id integer
care_site_id integer
year_of_birth integer
gender_concept_id integer
provider_source_value varchar
specialty_source_value varchar
specialty_source_concept_id integer
gender_source_value varchar
gender_source_concept_id integer
}
PAYER_PLAN_PERIOD {
payer_plan_period_id integer
person_id integer
payer_plan_period_start_date date
payer_plan_period_end_date date
payer_concept_id integer
payer_source_value varchar
payer_source_concept_id integer
plan_concept_id integer
plan_source_value varchar
plan_source_concept_id integer
sponsor_concept_id integer
sponsor_source_value varchar
sponsor_source_concept_id integer
family_source_value varchar
stop_reason_concept_id integer
stop_reason_source_value varchar
stop_reason_source_concept_id integer
}
COST {
cost_id integer
cost_event_id integer
cost_domain_id varchar
cost_type_concept_id integer
currency_concept_id integer
total_charge float
total_cost float
total_paid float
paid_by_payer float
paid_by_patient float
paid_patient_copay float
paid_patient_coinsurance float
paid_patient_deductible float
paid_by_primary float
paid_ingredient_cost float
paid_dispensing_fee float
payer_plan_period_id integer
amount_allowed float
revenue_code_concept_id integer
revenue_code_source_value varchar
drg_concept_id integer
drg_source_value varchar
}
DRUG_ERA {
drug_era_id integer
person_id integer
drug_concept_id integer
drug_era_start_date date
drug_era_end_date date
drug_exposure_count integer
gap_days integer
}
DOSE_ERA {
dose_era_id integer
person_id integer
drug_concept_id integer
unit_concept_id integer
dose_value float
dose_era_start_date date
dose_era_end_date date
}
CONDITION_ERA {
condition_era_id integer
person_id integer
condition_concept_id integer
condition_era_start_date date
condition_era_end_date date
condition_occurrence_count integer
}
EPISODE {
episode_id integer
person_id integer
episode_concept_id integer
episode_start_date date
episode_start_datetime datetime
episode_end_date date
episode_end_datetime datetime
episode_parent_id integer
episode_number integer
episode_object_concept_id integer
episode_type_concept_id integer
episode_source_value varchar
episode_source_concept_id integer
}
EPISODE_EVENT {
episode_id integer
event_id integer
episode_event_field_concept_id integer
}
METADATA {
metadata_id integer
metadata_concept_id integer
metadata_type_concept_id integer
name varchar
value_as_string varchar
value_as_concept_id integer
value_as_number float
metadata_date date
metadata_datetime datetime
}
CDM_SOURCE {
cdm_source_name varchar
cdm_source_abbreviation varchar
cdm_holder varchar
source_description varchar
source_documentation_reference varchar
cdm_etl_reference varchar
source_release_date date
cdm_release_date date
cdm_version varchar
cdm_version_concept_id integer
vocabulary_version varchar
}
CONCEPT {
concept_id integer
concept_name varchar
domain_id varchar
vocabulary_id varchar
concept_class_id varchar
standard_concept varchar
concept_code varchar
valid_start_date date
valid_end_date date
invalid_reason varchar
}
VOCABULARY {
vocabulary_id varchar
vocabulary_name varchar
vocabulary_reference varchar
vocabulary_version varchar
vocabulary_concept_id integer
}
DOMAIN {
domain_id varchar
domain_name varchar
domain_concept_id integer
}
CONCEPT_CLASS {
concept_class_id varchar
concept_class_name varchar
concept_class_concept_id integer
}
CONCEPT_RELATIONSHIP {
concept_id_1 integer
concept_id_2 integer
relationship_id varchar
valid_start_date date
valid_end_date date
invalid_reason varchar
}
RELATIONSHIP {
relationship_id varchar
relationship_name varchar
is_hierarchical varchar
defines_ancestry varchar
reverse_relationship_id varchar
relationship_concept_id integer
}
CONCEPT_SYNONYM {
concept_id integer
concept_synonym_name varchar
language_concept_id integer
}
CONCEPT_ANCESTOR {
ancestor_concept_id integer
descendant_concept_id integer
min_levels_of_separation integer
max_levels_of_separation integer
}
SOURCE_TO_CONCEPT_MAP {
source_code varchar
source_concept_id integer
source_vocabulary_id varchar
source_code_description varchar
target_concept_id integer
target_vocabulary_id varchar
valid_start_date date
valid_end_date date
invalid_reason varchar
}
DRUG_STRENGTH {
drug_concept_id integer
ingredient_concept_id integer
amount_value float
amount_unit_concept_id integer
numerator_value float
numerator_unit_concept_id integer
denominator_value float
denominator_unit_concept_id integer
box_size integer
valid_start_date date
valid_end_date date
invalid_reason varchar
}
COHORT {
cohort_definition_id integer
subject_id integer
cohort_start_date date
cohort_end_date date
}
COHORT_DEFINITION {
cohort_definition_id integer
cohort_definition_name varchar
cohort_definition_description varchar
definition_type_concept_id integer
cohort_definition_syntax varchar
subject_concept_id integer
cohort_initiation_date date
}
PERSON ||--o{ CONCEPT : ""
PERSON ||--o{ LOCATION : ""
PERSON ||--o{ PROVIDER : ""
PERSON ||--o{ CARE_SITE : ""
OBSERVATION_PERIOD ||--o{ PERSON : ""
OBSERVATION_PERIOD ||--o{ CONCEPT : ""
VISIT_OCCURRENCE ||--o{ PERSON : ""
VISIT_OCCURRENCE ||--o{ CONCEPT : ""
VISIT_OCCURRENCE ||--o{ PROVIDER : ""
VISIT_OCCURRENCE ||--o{ CARE_SITE : ""
VISIT_OCCURRENCE ||--o{ VISIT_OCCURRENCE : ""
VISIT_DETAIL ||--o{ PERSON : ""
VISIT_DETAIL ||--o{ CONCEPT : ""
VISIT_DETAIL ||--o{ PROVIDER : ""
VISIT_DETAIL ||--o{ CARE_SITE : ""
VISIT_DETAIL ||--o{ VISIT_DETAIL : ""
VISIT_DETAIL ||--o{ VISIT_OCCURRENCE : ""
CONDITION_OCCURRENCE ||--o{ PERSON : ""
CONDITION_OCCURRENCE ||--o{ CONCEPT : ""
CONDITION_OCCURRENCE ||--o{ PROVIDER : ""
CONDITION_OCCURRENCE ||--o{ VISIT_OCCURRENCE : ""
CONDITION_OCCURRENCE ||--o{ VISIT_DETAIL : ""
DRUG_EXPOSURE ||--o{ PERSON : ""
DRUG_EXPOSURE ||--o{ CONCEPT : ""
DRUG_EXPOSURE ||--o{ PROVIDER : ""
DRUG_EXPOSURE ||--o{ VISIT_OCCURRENCE : ""
DRUG_EXPOSURE ||--o{ VISIT_DETAIL : ""
PROCEDURE_OCCURRENCE ||--o{ PERSON : ""
PROCEDURE_OCCURRENCE ||--o{ CONCEPT : ""
PROCEDURE_OCCURRENCE ||--o{ PROVIDER : ""
PROCEDURE_OCCURRENCE ||--o{ VISIT_OCCURRENCE : ""
PROCEDURE_OCCURRENCE ||--o{ VISIT_DETAIL : ""
DEVICE_EXPOSURE ||--o{ PERSON : ""
DEVICE_EXPOSURE ||--o{ CONCEPT : ""
DEVICE_EXPOSURE ||--o{ PROVIDER : ""
DEVICE_EXPOSURE ||--o{ VISIT_OCCURRENCE : ""
DEVICE_EXPOSURE ||--o{ VISIT_DETAIL : ""
MEASUREMENT ||--o{ PERSON : ""
MEASUREMENT ||--o{ CONCEPT : ""
MEASUREMENT ||--o{ PROVIDER : ""
MEASUREMENT ||--o{ VISIT_OCCURRENCE : ""
MEASUREMENT ||--o{ VISIT_DETAIL : ""
OBSERVATION ||--o{ PERSON : ""
OBSERVATION ||--o{ CONCEPT : ""
OBSERVATION ||--o{ PROVIDER : ""
OBSERVATION ||--o{ VISIT_OCCURRENCE : ""
OBSERVATION ||--o{ VISIT_DETAIL : ""
DEATH ||--o{ PERSON : ""
DEATH ||--o{ CONCEPT : ""
NOTE ||--o{ PERSON : ""
NOTE ||--o{ CONCEPT : ""
NOTE ||--o{ PROVIDER : ""
NOTE ||--o{ VISIT_OCCURRENCE : ""
NOTE ||--o{ VISIT_DETAIL : ""
NOTE_NLP ||--o{ CONCEPT : ""
SPECIMEN ||--o{ PERSON : ""
SPECIMEN ||--o{ CONCEPT : ""
FACT_RELATIONSHIP ||--o{ CONCEPT : ""
LOCATION ||--o{ CONCEPT : ""
CARE_SITE ||--o{ CONCEPT : ""
CARE_SITE ||--o{ LOCATION : ""
PROVIDER ||--o{ CONCEPT : ""
PROVIDER ||--o{ CARE_SITE : ""
PAYER_PLAN_PERIOD ||--o{ PERSON : ""
PAYER_PLAN_PERIOD ||--o{ CONCEPT : ""
COST ||--o{ DOMAIN : ""
COST ||--o{ CONCEPT : ""
DRUG_ERA ||--o{ PERSON : ""
DRUG_ERA ||--o{ CONCEPT : ""
DOSE_ERA ||--o{ PERSON : ""
DOSE_ERA ||--o{ CONCEPT : ""
CONDITION_ERA ||--o{ PERSON : ""
CONDITION_ERA ||--o{ CONCEPT : ""
EPISODE ||--o{ PERSON : ""
EPISODE ||--o{ CONCEPT : ""
EPISODE_EVENT ||--o{ EPISODE : ""
EPISODE_EVENT ||--o{ CONCEPT : ""
METADATA ||--o{ CONCEPT : ""
CDM_SOURCE ||--o{ CONCEPT : ""
CONCEPT ||--o{ DOMAIN : ""
CONCEPT ||--o{ VOCABULARY : ""
CONCEPT ||--o{ CONCEPT_CLASS : ""
VOCABULARY ||--o{ CONCEPT : ""
DOMAIN ||--o{ CONCEPT : ""
CONCEPT_CLASS ||--o{ CONCEPT : ""
CONCEPT_RELATIONSHIP ||--o{ CONCEPT : ""
CONCEPT_RELATIONSHIP ||--o{ RELATIONSHIP : ""
RELATIONSHIP ||--o{ CONCEPT : ""
CONCEPT_SYNONYM ||--o{ CONCEPT : ""
CONCEPT_ANCESTOR ||--o{ CONCEPT : ""
SOURCE_TO_CONCEPT_MAP ||--o{ CONCEPT : ""
SOURCE_TO_CONCEPT_MAP ||--o{ VOCABULARY : ""
DRUG_STRENGTH ||--o{ CONCEPT : ""
COHORT_DEFINITION ||--o{ CONCEPT : ""

63
extras/createERDiagram.R Normal file
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cdmVersion <- '5.4'
cdmPart <- c('CDM','VOCAB', 'RESULTS')
cdmTables <- NULL #c('PERSON', 'OBSERVATION_PERIOD', 'VISIT_OCCURRENCE', 'CONDITION_OCCURRENCE', 'CONCEPT')
cdmTableCsvLoc <- system.file(file.path("csv", paste0("OMOP_CDMv", cdmVersion, "_Table_Level.csv")), package = "CommonDataModel", mustWork = TRUE)
cdmFieldCsvLoc <- system.file(file.path("csv", paste0("OMOP_CDMv", cdmVersion, "_Field_Level.csv")), package = "CommonDataModel", mustWork = TRUE)
tableSpecs <- read.csv(cdmTableCsvLoc, stringsAsFactors = FALSE)
cdmSpecs <- read.csv(cdmFieldCsvLoc, stringsAsFactors = FALSE)
mermaidDdlLines <- c()
mermaidFkLines <- c()
for (i in 1:nrow(tableSpecs)) {
table <- tableSpecs[i,]
tableName <- table$cdmTableName
if (!(table$schema %in% cdmPart)) {
next
}
if (!is.null(cdmTables) && !(table$cdmTableName %in% cdmTables)) {
next
}
mermaidDdlLines <- c(mermaidDdlLines,
sprintf(' %s {', tableName))
fields <- subset(cdmSpecs, cdmTableName == tableName)
for (j in 1:nrow(fields)) {
field <- fields[j,]
cdmFieldName <- field$cdmFieldName
cdmDataType <- field$cdmDatatype
if (startsWith(cdmDataType, 'varchar')) {
cdmDataType <- 'varchar'
}
if (cdmFieldName == '"offset"') {
cdmFieldName <- 'offset'
}
mermaidDdlLines <- c(mermaidDdlLines,
sprintf(' %s %s', cdmFieldName, cdmDataType))
if (field$isForeignKey == 'Yes') {
fkTable <- subset(tableSpecs, cdmTableName == field$fkTableName)
if (!(fkTable$schema %in% cdmPart)) {
next
}
if (!is.null(cdmTables) && !(fkTable$cdmTableName %in% cdmTables)) {
next
}
fkRelation <- sprintf(' %s ||--o{ %s : ""', tableName, field$fkTableName)
if (fkRelation %in% mermaidFkLines) {
next
}
mermaidFkLines <- c(mermaidFkLines,
fkRelation)
}
}
mermaidDdlLines <- c(mermaidDdlLines, ' }')
}
mermaidString <- paste(c('erDiagram', mermaidDdlLines, mermaidFkLines), collapse = '\n')
fileName <- sprintf('OMOP_CDMv%s_ER_Diagram.mmd', cdmVersion)
write(mermaidString, file.path('extras', fileName))

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README
------
v5.3 to v5.4 CDM conversion
NOTES
-----
The *_v53_to_v54_migration.sql scripts are SQL scripts that migrate a v5.3 CDM to a v5.4 CDM.
The changes implemented are found here: http://ohdsi.github.io/CommonDataModel/cdm54Changes.html.
Please replace @cdmDatabaseSchema with your schema name.
Links to database documentation are included in each script to facilitate debugging.

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-- http://ohdsi.github.io/CommonDataModel/cdm54Changes.html
-- BigQuery SQL references:
-- https://cloud.google.com/bigquery/docs/reference/standard-sql/data-definition-language#creating_a_new_table_from_an_existing_table
-- https://cloud.google.com/bigquery/docs/manually-changing-schemas
-- https://cloud.google.com/bigquery/docs/reference/standard-sql/data-definition-language#alter_column_set_data_type_statement
-- https://cloud.google.com/bigquery/docs/managing-tables#renaming-table
--
-- VISIT_OCCURRENCE
-- admitting_source_concept_id -> admitted_from_concept_id
-- admitting_source_value -> admitted_from_source_value
-- discharge_to_concept_id -> discharged_to_concept_id
-- discharge_to_source_value -> discharged_to_source_value
alter table @cdmDatabaseSchema.visit_occurrence rename to visit_occurrence_old;
create table @cdmDatabaseSchema.visit_occurrence
as
select * EXCEPT(admitting_source_concept_id,admitting_source_value,discharge_to_concept_id,discharge_to_source_value),
admitting_source_concept_id as admitted_from_concept_id,
admitting_source_value as admitted_from_source_value,
discharge_to_concept_id as discharged_to_concept_id,
discharge_to_source_value as discharged_to_source_value
from visit_occurrence_old;
--
-- VISIT_DETAIL
-- admitting_source_concept_id -> admitted_from_concept_id
-- admitting_source_value -> admitted_from_source_value
-- discharge_to_concept_id -> discharged_to_concept_id
-- discharge_to_source_value -> discharged_to_source_value
-- visit_detail_parent_id -> parent_visit_detail_id
alter table @cdmDatabaseSchema.visit_detail rename to visit_detail_old;
create table @cdmDatabaseSchema.visit_occurrence
as
select * EXCEPT(admitting_source_concept_id,admitting_source_value,discharge_to_concept_id,discharge_to_source_value,visit_detail_parent_id),
admitting_source_concept_id as admitted_from_concept_id,
admitting_source_value as admitted_from_source_value,
discharge_to_concept_id as discharged_to_concept_id,
discharge_to_source_value as discharged_to_source_value,
visit_detail_parent_id as parent_visit_detail_id
from visit_detail_old;
-- PROCEDURE_OCCURRENCE
-- + Procedure_end_date
-- + Procedure_end_datetime
alter table @cdmDatabaseSchema.procedure_occurrence add column procedure_end_date date;
alter table @cdmDatabaseSchema.procedure_occurrence add column procedure_end_datetime datetime;
-- DEVICE_EXPOSURE
-- Unique_device_id -> Changed to varchar(255) (already a STRING on bigquery)
-- + Production_id
-- + Unit_concept_id
-- + Unit_source_value
-- + Unit_source_concept_id
alter table @cdmDatabaseSchema.device_exposure add column production_id int64;
alter table @cdmDatabaseSchema.device_exposure add column unit_concept_id int64;
alter table @cdmDatabaseSchema.device_exposure add column unit_source_value string;
alter table @cdmDatabaseSchema.device_exposure add column unit_source_concept_id int64;
-- MEASUREMENT
-- + Unit_source_concept_id
-- + Measurement_event_id
-- + Meas_event_field_concept_id
alter table @cdmDatabaseSchema.measurement add column unit_source_concept_id int64;
alter table @cdmDatabaseSchema.measurement add column measurement_event_id int64;
alter table @cdmDatabaseSchema.measurement add column meas_event_field_concept_id int64;
-- OBSERVATION
-- + Value_source_value
-- + Observation_event_id
-- + Obs_event_field_concept_id
alter table @cdmDatabaseSchema.observation add column value_source_value string;
alter table @cdmDatabaseSchema.observation add column observation_event_id int64;
alter table @cdmDatabaseSchema.observation add column obs_event_field_concept_id int64;
-- NOTE
-- + Note_event_id
-- + Note_event_field_concept_id
alter table @cdmDatabaseSchema.note add column note_event_id int64;
alter table @cdmDatabaseSchema.note add column note_event_field_concept_id int64;
-- LOCATION
-- + Country_concept_id
-- + Country_source_value
-- + Latitude
-- + Longitude
alter table @cdmDatabaseSchema.location add column country_concept_id int64;
alter table @cdmDatabaseSchema.location add column country_source_value string;
alter table @cdmDatabaseSchema.location add column latitude float64;
alter table @cdmDatabaseSchema.location add column longitude float64;
-- EPISODE
create table @cdmDatabaseSchema.episode (
episode_id INT64 not null,
person_id INT64 not null,
episode_concept_id INT64 not null,
episode_start_date date not null,
episode_start_datetime datetime null,
episode_end_date date null,
episode_end_datetime datetime null,
episode_parent_id INT64,
episode_number INT64,
episode_object_concept_id INT64 not null,
episode_type_concept_id INT64 not null,
episode_source_value STRING,
episode_source_concept_id INT64 );
-- EPISODE_EVENT
CREATE TABLE @cdmDatabaseSchema.EPISODE_EVENT (
episode_id int64 NOT NULL,
event_id int64 NOT NULL,
episode_event_field_concept_id int64 NOT NULL );
-- METADATA
-- + Metadata_id
-- + Value_as_number
alter table @cdmDatabaseSchema.metadata add column metadata_id int64;
alter table @cdmDatabaseSchema.metadata add column value_as_number float64;
-- CDM_SOURCE
-- Cdm_source_name -> Mandatory field
-- Cdm_source_abbreviation -> Mandatory field
-- Cdm_holder -> Mandatory field
-- Source_release_date -> Mandatory field
-- Cdm_release_date -> Mandatory field
-- + Cdm_version_concept_id
alter table @cdmDatabaseSchema.cdm_source rename to cdm_source_v53;
CREATE TABLE @cdmDatabaseSchema.cdm_source (
cdm_source_name string NOT NULL,
cdm_source_abbreviation string NOT NULL,
cdm_holder string NOT NULL,
source_description string NULL,
source_documentation_reference string NULL,
cdm_etl_reference string NULL,
source_release_date datetime NOT NULL,
cdm_release_date datetime NOT NULL,
cdm_version string NULL,
cdm_version_concept_id int64 NOT NULL,
vocabulary_version string NOT NULL );
insert into @cdmDatabaseSchema.cdm_source
select cdm_source_name,cdm_source_abbreviation,cdm_holder,
source_description,source_documentation_reference,cdm_etl_reference,
source_release_date,cdm_release_date,'5.4',
756265,vocabulary_version
from @cdmDatabaseSchema.cdm_source_v53;
-- VOCABULARY
-- Vocabulary_reference -> Non-mandatory field
-- Vocabulary_version -> Non-mandatory field
alter table @cdmDatabaseSchema.vocabulary rename to vocabulary_v53;
CREATE TABLE @cdmDatabaseSchema.vocabulary (
vocabulary_id string NOT NULL,
vocabulary_name string NOT NULL,
vocabulary_reference string NULL,
vocabulary_version string NULL,
vocabulary_concept_id int64 NOT NULL );
insert into @cdmDatabaseSchema.vocabulary
select vocabulary_id,vocabulary_name,vocabulary_reference,
vocabulary_version, vocabulary_concept_id
from @cdmDatabaseSchema.vocabulary_v53;
-- ATTRIBUTE_DEFINITION
drop table @cdmDatabaseSchema.attribute_definition;
-- COHORT
CREATE TABLE @cdmDatabaseSchema.cohort (
cohort_definition_id int64 NOT NULL,
subject_id int64 NOT NULL,
cohort_start_date datetime NOT NULL,
cohort_end_date datetime NOT NULL );

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-- http://ohdsi.github.io/CommonDataModel/cdm54Changes.html
-- Impala SQL references:
-- https://docs.cloudera.com/documentation/enterprise/6/6.3/topics/impala_alter_table.html
--
-- VISIT_OCCURRENCE
-- admitting_source_concept_id -> admitted_from_concept_id
-- admitting_source_value -> admitted_from_source_value
-- discharge_to_concept_id -> discharged_to_concept_id
-- discharge_to_source_value -> discharged_to_source_value
alter table @cdmDatabaseSchema.visit_occurrence change admitting_source_concept_id admitted_from_concept_id int;
alter table @cdmDatabaseSchema.visit_occurrence change admitting_source_value admitted_from_source_value int;
alter table @cdmDatabaseSchema.visit_occurrence change discharge_to_concept_id discharged_to_concept_id int;
alter table @cdmDatabaseSchema.visit_occurrence change discharge_to_source_value discharged_to_source_value int;
--
-- VISIT_DETAIL
-- admitting_source_concept_id -> admitted_from_concept_id
-- admitting_source_value -> admitted_from_source_value
-- discharge_to_concept_id -> discharged_to_concept_id
-- discharge_to_source_value -> discharged_to_source_value
-- visit_detail_parent_id -> parent_visit_detail_id
alter table @cdmDatabaseSchema.visit_detail change admitting_source_concept_id admitted_from_concept_id int;
alter table @cdmDatabaseSchema.visit_detail change admitting_source_value admitted_from_source_value int;
alter table @cdmDatabaseSchema.visit_detail change discharge_to_concept_id discharged_to_concept_id int;
alter table @cdmDatabaseSchema.visit_detail change discharge_to_source_value discharged_to_source_value int;
alter table @cdmDatabaseSchema.visit_detail change visit_detail_parent_id parent_visit_detail_id int;
-- PROCEDURE_OCCURRENCE
-- + Procedure_end_date
-- + Procedure_end_datetime
alter table @cdmDatabaseSchema.procedure_occurrence add columns (procedure_end_date timestamp);
alter table @cdmDatabaseSchema.procedure_occurrence add columns (procedure_end_datetime timestamp);
-- DEVICE_EXPOSURE
-- Unique_device_id -> Changed to varchar(255)
-- + Production_id
-- + Unit_concept_id
-- + Unit_source_value
-- + Unit_source_concept_id
alter table @cdmDatabaseSchema.device_exposure change unique_device_id unique_device_id varchar(300);
alter table @cdmDatabaseSchema.device_exposure add columns (production_id int);
alter table @cdmDatabaseSchema.device_exposure add columns (unit_concept_id int);
alter table @cdmDatabaseSchema.device_exposure add columns (unit_source_value int);
alter table @cdmDatabaseSchema.device_exposure add columns (unit_source_concept_id int);
-- MEASUREMENT
-- + Unit_source_concept_id
-- + Measurement_event_id
-- + Meas_event_field_concept_id
alter table @cdmDatabaseSchema.measurement add columns (unit_source_concept_id int);
alter table @cdmDatabaseSchema.measurement add columns (measurement_event_id int);
alter table @cdmDatabaseSchema.measurement add columns (meas_event_field_concept_id int);
-- OBSERVATION
-- + Value_source_value
-- + Observation_event_id
-- + Obs_event_field_concept_id
alter table @cdmDatabaseSchema.observation add columns (value_source_value varchar(50));
alter table @cdmDatabaseSchema.observation add columns (observation_event_id int);
alter table @cdmDatabaseSchema.observation add columns (obs_event_field_concept_id int);
-- NOTE
-- + Note_event_id
-- + Note_event_field_concept_id
alter table @cdmDatabaseSchema.note add columns (note_event_id int);
alter table @cdmDatabaseSchema.note add columns (note_event_field_concept_id int);
-- LOCATION
-- + Country_concept_id
-- + Country_source_value
-- + Latitude
-- + Longitude
alter table @cdmDatabaseSchema.location add columns (country_concept_id int);
alter table @cdmDatabaseSchema.location add columns (country_source_value varchar(80));
alter table @cdmDatabaseSchema.location add columns (latitude float);
alter table @cdmDatabaseSchema.location add columns (longitude float);
-- EPISODE
CREATE TABLE @cdmDatabaseSchema.EPISODE (
episode_id int,
person_id int,
episode_concept_id int,
episode_start_date timestamp,
episode_start_datetime TIMESTAMP,
episode_end_date timestamp,
episode_end_datetime timestamp,
episode_parent_id int,
episode_number int,
episode_object_concept_id int,
episode_type_concept_id int,
episode_source_value varchar(50),
episode_source_concept_id int );
-- EPISODE_EVENT
CREATE TABLE @cdmDatabaseSchema.EPISODE_EVENT (
episode_id int,
event_id int,
episode_event_field_concept_id int );
-- METADATA
-- + Metadata_id
-- + Value_as_number
alter table @cdmDatabaseSchema.metadata add columns (metadata_id int);
alter table @cdmDatabaseSchema.metadata add columns (value_as_number float);
-- CDM_SOURCE
-- Cdm_source_name -> Mandatory field
-- Cdm_source_abbreviation -> Mandatory field
-- Cdm_holder -> Mandatory field
-- Source_release_date -> Mandatory field
-- Cdm_release_date -> Mandatory field
-- + Cdm_version_concept_id
alter table @cdmDatabaseSchema.cdm_source rename to cdm_source_v53;
CREATE TABLE @cdmDatabaseSchema.cdm_source (
cdm_source_name varchar(255),
cdm_source_abbreviation varchar(25),
cdm_holder varchar(255),
source_description varchar(max),
source_documentation_reference varchar(255),
cdm_etl_reference varchar(255),
source_release_date timestamp,
cdm_release_date timestamp,
cdm_version varchar(10),
cdm_version_concept_id int,
vocabulary_version varchar(20));
insert into @cdmDatabaseSchema.cdm_source
select cdm_source_name,cdm_source_abbreviation,cdm_holder,
source_description,source_documentation_reference,cdm_etl_reference,
source_release_date,cdm_release_date,'5.4',
756265,vocabulary_version
from @cdmDatabaseSchema.cdm_source_v53;
-- VOCABULARY
-- Vocabulary_reference -> Non-mandatory field
-- Vocabulary_version -> Non-mandatory field
alter table @cdmDatabaseSchema.vocabulary rename to vocabulary_v53;
CREATE TABLE @cdmDatabaseSchema.vocabulary (
vocabulary_id varchar(20),
vocabulary_name varchar(255),
vocabulary_reference varchar(255),
vocabulary_version varchar(255),
vocabulary_concept_id int );
insert into @cdmDatabaseSchema.vocabulary
select vocabulary_id,vocabulary_name,vocabulary_reference,
vocabulary_version, vocabulary_concept_id
from @cdmDatabaseSchema.vocabulary_v53;
-- ATTRIBUTE_DEFINITION
drop table @cdmDatabaseSchema.attribute_definition;
-- COHORT
CREATE TABLE @cdmDatabaseSchema.cohort (
cohort_definition_id int,
subject_id int,
cohort_start_date timestamp,
cohort_end_date timestamp );

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-- http://ohdsi.github.io/CommonDataModel/cdm54Changes.html
-- Netezza SQL references:
-- https://www.ibm.com/docs/en/psfa/7.2.1?topic=reference-alter-table
-- https://www.ibm.com/docs/en/psfa/7.2.1?topic=tables-add-drop-column
--
-- VISIT_OCCURRENCE
-- admitting_source_concept_id -> admitted_from_concept_id
-- admitting_source_value -> admitted_from_source_value
-- discharge_to_concept_id -> discharged_to_concept_id
-- discharge_to_source_value -> discharged_to_source_value
alter table @cdmDatabaseSchema.visit_occurrence rename column admitting_source_concept_id to admitted_from_concept_id;
alter table @cdmDatabaseSchema.visit_occurrence rename column admitting_source_value to admitted_from_source_value;
alter table @cdmDatabaseSchema.visit_occurrence rename column discharge_to_concept_id to discharged_to_concept_id;
alter table @cdmDatabaseSchema.visit_occurrence rename column discharge_to_source_value to discharged_to_source_value;
--
-- VISIT_DETAIL
-- admitting_source_concept_id -> admitted_from_concept_id
-- admitting_source_value -> admitted_from_source_value
-- discharge_to_concept_id -> discharged_to_concept_id
-- discharge_to_source_value -> discharged_to_source_value
-- visit_detail_parent_id -> parent_visit_detail_id
alter table @cdmDatabaseSchema.visit_detail rename column admitting_source_concept_id to admitted_from_concept_id;
alter table @cdmDatabaseSchema.visit_detail rename column admitting_source_value to admitted_from_source_value;
alter table @cdmDatabaseSchema.visit_detail rename column discharge_to_concept_id to discharged_to_concept_id;
alter table @cdmDatabaseSchema.visit_detail rename column discharge_to_source_value to discharged_to_source_value;
alter table @cdmDatabaseSchema.visit_detail rename column visit_detail_parent_id to parent_visit_detail_id;
-- PROCEDURE_OCCURRENCE
-- + Procedure_end_date
-- + Procedure_end_datetime
alter table @cdmDatabaseSchema.procedure_occurrence add column procedure_end_date timestamp null;
alter table @cdmDatabaseSchema.procedure_occurrence add column procedure_end_datetime timestamp null;
-- DEVICE_EXPOSURE
-- Unique_device_id -> Changed to varchar(255)
-- + Production_id
-- + Unit_concept_id
-- + Unit_source_value
-- + Unit_source_concept_id
alter table @cdmDatabaseSchema.device_exposure modify column (unique_device_id varchar(300);
alter table @cdmDatabaseSchema.device_exposure add column production_id integer null;
alter table @cdmDatabaseSchema.device_exposure add column unit_concept_id integer null;
alter table @cdmDatabaseSchema.device_exposure add column unit_source_value varchar(50) null;
alter table @cdmDatabaseSchema.device_exposure add column unit_source_concept_id integer null;
-- MEASUREMENT
-- + Unit_source_concept_id
-- + Measurement_event_id
-- + Meas_event_field_concept_id
alter table @cdmDatabaseSchema.measurement add column unit_source_concept_id integer default null;
alter table @cdmDatabaseSchema.measurement add column measurement_event_id bigint null;
alter table @cdmDatabaseSchema.measurement add column meas_event_field_concept_id integer null;
-- OBSERVATION
-- + Value_source_value
-- + Observation_event_id
-- + Obs_event_field_concept_id
alter table @cdmDatabaseSchema.observation add column value_source_value varchar(50) null;
alter table @cdmDatabaseSchema.observation add column observation_event_id bigint null;
alter table @cdmDatabaseSchema.observation add column obs_event_field_concept_id integer null;
-- NOTE
-- + Note_event_id
-- + Note_event_field_concept_id
alter table @cdmDatabaseSchema.note add column note_event_id bigint null;
alter table @cdmDatabaseSchema.note add column note_event_field_concept_id integer null;
-- LOCATION
-- + Country_concept_id
-- + Country_source_value
-- + Latitude
-- + Longitude
alter table @cdmDatabaseSchema.location add column country_concept_id integer null;
alter table @cdmDatabaseSchema.location add column country_source_value varchar(80) null;
alter table @cdmDatabaseSchema.location add column latitude float null;
alter table @cdmDatabaseSchema.location add column longitude float null;
-- EPISODE
CREATE TABLE @cdmDatabaseSchema.EPISODE (
episode_id bigint NOT NULL,
person_id bigint NOT NULL,
episode_concept_id integer NOT NULL,
episode_start_date timestamp NOT NULL,
episode_start_datetime TIMESTAMP NULL,
episode_end_date timestamp NULL,
episode_end_datetime TIMESTAMP NULL,
episode_parent_id bigint NULL,
episode_number integer NULL,
episode_object_concept_id integer NOT NULL,
episode_type_concept_id integer NOT NULL,
episode_source_value varchar(50) NULL,
episode_source_concept_id integer NULL );
-- EPISODE_EVENT
CREATE TABLE @cdmDatabaseSchema.EPISODE_EVENT (
episode_id bigint NOT NULL,
event_id bigint NOT NULL,
episode_event_field_concept_id integer NOT NULL );
-- METADATA
-- + Metadata_id
-- + Value_as_number
alter table @cdmDatabaseSchema.metadata add column metadata_id integer null;
alter table @cdmDatabaseSchema.metadata add column value_as_number float null;
-- CDM_SOURCE
-- Cdm_source_name -> Mandatory field
-- Cdm_source_abbreviation -> Mandatory field
-- Cdm_holder -> Mandatory field
-- Source_release_date -> Mandatory field
-- Cdm_release_date -> Mandatory field
-- + Cdm_version_concept_id
alter table @cdmDatabaseSchema.cdm_source rename to cdm_source_v53;
CREATE TABLE @cdmDatabaseSchema.cdm_source (
cdm_source_name varchar(255) NOT NULL,
cdm_source_abbreviation varchar(25) NOT NULL,
cdm_holder varchar(255) NOT NULL,
source_description varchar(1000) NULL,
source_documentation_reference varchar(255) NULL,
cdm_etl_reference varchar(255) NULL,
source_release_date timestamp NOT NULL,
cdm_release_date timestamp NOT NULL,
cdm_version varchar(10) NULL,
cdm_version_concept_id integer NOT NULL,
vocabulary_version varchar(20) NOT NULL );
insert into @cdmDatabaseSchema.cdm_source
select cdm_source_name,cdm_source_abbreviation,cdm_holder,
source_description,source_documentation_reference,cdm_etl_reference,
source_release_date,cdm_release_date,'5.4',
756265,vocabulary_version
from @cdmDatabaseSchema.cdm_source_v53;
-- VOCABULARY
-- Vocabulary_reference -> Non-mandatory field
-- Vocabulary_version -> Non-mandatory field
alter table @cdmDatabaseSchema.vocabulary rename to vocabulary_v53;
CREATE TABLE @cdmDatabaseSchema.vocabulary (
vocabulary_id varchar(20) NOT NULL,
vocabulary_name varchar(255) NOT NULL,
vocabulary_reference varchar(255) NULL,
vocabulary_version varchar(255) NULL,
vocabulary_concept_id integer NOT NULL );
insert into @cdmDatabaseSchema.vocabulary
select vocabulary_id,vocabulary_name,vocabulary_reference,
vocabulary_version, vocabulary_concept_id
from @cdmDatabaseSchema.vocabulary_v53;
-- ATTRIBUTE_DEFINITION
drop table @cdmDatabaseSchema.attribute_definition;
-- COHORT
CREATE TABLE @cdmDatabaseSchema.cohort (
cohort_definition_id integer NOT NULL,
subject_id integer NOT NULL,
cohort_start_date timestamp NOT NULL,
cohort_end_date timestamp NOT NULL );

View File

@ -0,0 +1,179 @@
-- http://ohdsi.github.io/CommonDataModel/cdm54Changes.html
-- Oracle SQL references:
-- https://docs.oracle.com/en/database/oracle/oracle-database/19/sqlrf/ALTER-TABLE.html#GUID-552E7373-BF93-477D-9DA3-B2C9386F2877
-- https://docs.oracle.com/en/database/oracle/oracle-database/19/sqlrf/Data-Types.html#GUID-0DC7FFAA-F03F-4448-8487-F2592496A510
-- https://docs.oracle.com/en/database/oracle/oracle-database/19/sqlrf/RENAME.html#GUID-573347CE-3EB8-42E5-B4D5-EF71CA06FAFC
--
-- VISIT_OCCURRENCE
-- admitting_source_concept_id -> admitted_from_concept_id
-- admitting_source_value -> admitted_from_source_value
-- discharge_to_concept_id -> discharged_to_concept_id
-- discharge_to_source_value -> discharged_to_source_value
alter table @cdmDatabaseSchema.visit_occurrence rename column admitting_source_concept_id to admitted_from_concept_id;
alter table @cdmDatabaseSchema.visit_occurrence rename column admitting_source_value to admitted_from_source_value;
alter table @cdmDatabaseSchema.visit_occurrence rename column discharge_to_concept_id to discharged_to_concept_id;
alter table @cdmDatabaseSchema.visit_occurrence rename column discharge_to_source_value to discharged_to_source_value;
--
-- VISIT_DETAIL
-- admitting_source_concept_id -> admitted_from_concept_id
-- admitting_source_value -> admitted_from_source_value
-- discharge_to_concept_id -> discharged_to_concept_id
-- discharge_to_source_value -> discharged_to_source_value
-- visit_detail_parent_id -> parent_visit_detail_id
alter table @cdmDatabaseSchema.visit_detail rename column admitting_source_concept_id to admitted_from_concept_id;
alter table @cdmDatabaseSchema.visit_detail rename column admitting_source_value to admitted_from_source_value;
alter table @cdmDatabaseSchema.visit_detail rename column discharge_to_concept_id to discharged_to_concept_id;
alter table @cdmDatabaseSchema.visit_detail rename column discharge_to_source_value to discharged_to_source_value;
alter table @cdmDatabaseSchema.visit_detail rename column visit_detail_parent_id to parent_visit_detail_id;
-- PROCEDURE_OCCURRENCE
-- + Procedure_end_date
-- + Procedure_end_datetime
alter table @cdmDatabaseSchema.procedure_occurrence add (procedure_end_date date default null);
alter table @cdmDatabaseSchema.procedure_occurrence add (procedure_end_datetime timestamp default null);
-- DEVICE_EXPOSURE
-- Unique_device_id -> Changed to varchar(255)
-- + Production_id
-- + Unit_concept_id
-- + Unit_source_value
-- + Unit_source_concept_id
alter table @cdmDatabaseSchema.device_exposure modify (unique_device_id varchar2(300));
alter table @cdmDatabaseSchema.device_exposure add (production_id number default null);
alter table @cdmDatabaseSchema.device_exposure add (unit_concept_id number default null);
alter table @cdmDatabaseSchema.device_exposure add (unit_source_value varchar2(50) default null);
alter table @cdmDatabaseSchema.device_exposure add (unit_source_concept_id number default null);
-- MEASUREMENT
-- + Unit_source_concept_id
-- + Measurement_event_id
-- + Meas_event_field_concept_id
alter table @cdmDatabaseSchema.measurement add (unit_source_concept_id number default null);
alter table @cdmDatabaseSchema.measurement add (measurement_event_id number default null);
alter table @cdmDatabaseSchema.measurement add (meas_event_field_concept_id number default null);
-- OBSERVATION
-- + Value_source_value
-- + Observation_event_id
-- + Obs_event_field_concept_id
alter table @cdmDatabaseSchema.observation add (value_source_value varchar2(50) default null);
alter table @cdmDatabaseSchema.observation add (observation_event_id number default null);
alter table @cdmDatabaseSchema.observation add (obs_event_field_concept_id number default null);
-- NOTE
-- + Note_event_id
-- + Note_event_field_concept_id
alter table @cdmDatabaseSchema.note add (note_event_id number default null);
alter table @cdmDatabaseSchema.note add (note_event_field_concept_id number default null);
-- LOCATION
-- + Country_concept_id
-- + Country_source_value
-- + Latitude
-- + Longitude
alter table @cdmDatabaseSchema.location add (country_concept_id number default null);
alter table @cdmDatabaseSchema.location add (country_source_value varchar2(80) default null);
alter table @cdmDatabaseSchema.location add (latitude float default null);
alter table @cdmDatabaseSchema.location add (longitude float default null);
-- EPISODE
CREATE TABLE @cdmDatabaseSchema.EPISODE (
episode_id number NOT NULL,
person_id number NOT NULL,
episode_concept_id number NOT NULL,
episode_start_date date NOT NULL,
episode_start_datetime TIMESTAMP NULL,
episode_end_date date NULL,
episode_end_datetime TIMESTAMP NULL,
episode_parent_id number NULL,
episode_number number NULL,
episode_object_concept_id number NOT NULL,
episode_type_concept_id number NOT NULL,
episode_source_value varchar2(50) NULL,
episode_source_concept_id number NULL );
-- EPISODE_EVENT
CREATE TABLE @cdmDatabaseSchema.EPISODE_EVENT (
episode_id number NOT NULL,
event_id number NOT NULL,
episode_event_field_concept_id number NOT NULL );
-- METADATA
-- + Metadata_id
-- + Value_as_number
alter table @cdmDatabaseSchema.metadata add (metadata_id number default null);
alter table @cdmDatabaseSchema.metadata add (value_as_number float default null);
-- CDM_SOURCE
-- Cdm_source_name -> Mandatory field
-- Cdm_source_abbreviation -> Mandatory field
-- Cdm_holder -> Mandatory field
-- Source_release_date -> Mandatory field
-- Cdm_release_date -> Mandatory field
-- + Cdm_version_concept_id
rename @cdmDatabaseSchema.cdm_source to cdm_source_v53;
CREATE TABLE @cdmDatabaseSchema.cdm_source (
cdm_source_name varchar2(255) NOT NULL,
cdm_source_abbreviation varchar2(25) NOT NULL,
cdm_holder varchar2(255) NOT NULL,
-- 32767 bytes if MAX_STRING_SIZE = EXTENDED
-- 4000 bytes if MAX_STRING_SIZE = STANDARD
source_description varchar2(32767) NULL,
source_documentation_reference varchar2(255) NULL,
cdm_etl_reference varchar2(255) NULL,
source_release_date date NOT NULL,
cdm_release_date date NOT NULL,
cdm_version varchar2(10) NULL,
cdm_version_concept_id number NOT NULL,
vocabulary_version varchar2(20) NOT NULL );
insert into @cdmDatabaseSchema.cdm_source
select cdm_source_name,cdm_source_abbreviation,cdm_holder,
source_description,source_documentation_reference,cdm_etl_reference,
source_release_date,cdm_release_date,'5.4',
756265,vocabulary_version
from @cdmDatabaseSchema.cdm_source_v53;
-- VOCABULARY
-- Vocabulary_reference -> Non-mandatory field
-- Vocabulary_version -> Non-mandatory field
rename @cdmDatabaseSchema.vocabulary to vocabulary_v53;
CREATE TABLE @cdmDatabaseSchema.vocabulary (
vocabulary_id varchar2(20) NOT NULL,
vocabulary_name varchar2(255) NOT NULL,
vocabulary_reference varchar2(255) NULL,
vocabulary_version varchar2(255) NULL,
vocabulary_concept_id number NOT NULL );
insert into @cdmDatabaseSchema.vocabulary
select vocabulary_id,vocabulary_name,vocabulary_reference,
vocabulary_version, vocabulary_concept_id
from @cdmDatabaseSchema.vocabulary_v53;
-- ATTRIBUTE_DEFINITION
drop table @cdmDatabaseSchema.attribute_definition;
-- COHORT
CREATE TABLE @cdmDatabaseSchema.cohort (
cohort_definition_id number NOT NULL,
subject_id number NOT NULL,
cohort_start_date date NOT NULL,
cohort_end_date date NOT NULL );

View File

@ -0,0 +1,175 @@
-- http://ohdsi.github.io/CommonDataModel/cdm54Changes.html
-- PostgreSQL SQL references:
-- https://www.postgresql.org/docs/current/sql-altertable.html
--
-- VISIT_OCCURRENCE
-- admitting_source_concept_id -> admitted_from_concept_id
-- admitting_source_value -> admitted_from_source_value
-- discharge_to_concept_id -> discharged_to_concept_id
-- discharge_to_source_value -> discharged_to_source_value
alter table @cdmDatabaseSchema.visit_occurrence rename column admitting_source_concept_id to admitted_from_concept_id;
alter table @cdmDatabaseSchema.visit_occurrence rename column admitting_source_value to admitted_from_source_value;
alter table @cdmDatabaseSchema.visit_occurrence rename column discharge_to_concept_id to discharged_to_concept_id;
alter table @cdmDatabaseSchema.visit_occurrence rename column discharge_to_source_value to discharged_to_source_value;
--
-- VISIT_DETAIL
-- admitting_source_concept_id -> admitted_from_concept_id
-- admitting_source_value -> admitted_from_source_value
-- discharge_to_concept_id -> discharged_to_concept_id
-- discharge_to_source_value -> discharged_to_source_value
-- visit_detail_parent_id -> parent_visit_detail_id
alter table @cdmDatabaseSchema.visit_detail rename column admitting_source_concept_id to admitted_from_concept_id;
alter table @cdmDatabaseSchema.visit_detail rename column admitting_source_value to admitted_from_source_value;
alter table @cdmDatabaseSchema.visit_detail rename column discharge_to_concept_id to discharged_to_concept_id;
alter table @cdmDatabaseSchema.visit_detail rename column discharge_to_source_value to discharged_to_source_value;
alter table @cdmDatabaseSchema.visit_detail rename column visit_detail_parent_id to parent_visit_detail_id;
-- PROCEDURE_OCCURRENCE
-- + Procedure_end_date
-- + Procedure_end_datetime
alter table @cdmDatabaseSchema.procedure_occurrence add column procedure_end_date date default null;
alter table @cdmDatabaseSchema.procedure_occurrence add column procedure_end_datetime timestamp default null;
-- DEVICE_EXPOSURE
-- Unique_device_id -> Changed to varchar(255)
-- + Production_id
-- + Unit_concept_id
-- + Unit_source_value
-- + Unit_source_concept_id
alter table @cdmDatabaseSchema.device_exposure alter column unique_device_id type varchar(300);
alter table @cdmDatabaseSchema.device_exposure add column production_id integer default null;
alter table @cdmDatabaseSchema.device_exposure add column unit_concept_id integer default null;
alter table @cdmDatabaseSchema.device_exposure add column unit_source_value varchar(50) default null;
alter table @cdmDatabaseSchema.device_exposure add column unit_source_concept_id integer default null;
-- MEASUREMENT
-- + Unit_source_concept_id
-- + Measurement_event_id
-- + Meas_event_field_concept_id
alter table @cdmDatabaseSchema.measurement add column unit_source_concept_id integer default null;
alter table @cdmDatabaseSchema.measurement add column measurement_event_id bigint default null;
alter table @cdmDatabaseSchema.measurement add column meas_event_field_concept_id integer default null;
-- OBSERVATION
-- + Value_source_value
-- + Observation_event_id
-- + Obs_event_field_concept_id
alter table @cdmDatabaseSchema.observation add column value_source_value varchar(50) default null;
alter table @cdmDatabaseSchema.observation add column observation_event_id bigint default null;
alter table @cdmDatabaseSchema.observation add column obs_event_field_concept_id integer default null;
-- NOTE
-- + Note_event_id
-- + Note_event_field_concept_id
alter table @cdmDatabaseSchema.note add column note_event_id bigint default null;
alter table @cdmDatabaseSchema.note add column note_event_field_concept_id integer default null;
-- LOCATION
-- + Country_concept_id
-- + Country_source_value
-- + Latitude
-- + Longitude
alter table @cdmDatabaseSchema.location add column country_concept_id integer default null;
alter table @cdmDatabaseSchema.location add column country_source_value varchar(80) default null;
alter table @cdmDatabaseSchema.location add column latitude numeric default null;
alter table @cdmDatabaseSchema.location add column longitude numeric default null;
-- EPISODE
CREATE TABLE @cdmDatabaseSchema.EPISODE (
episode_id bigint NOT NULL,
person_id bigint NOT NULL,
episode_concept_id integer NOT NULL,
episode_start_date date NOT NULL,
episode_start_datetime TIMESTAMP NULL,
episode_end_date date NULL,
episode_end_datetime TIMESTAMP NULL,
episode_parent_id bigint NULL,
episode_number integer NULL,
episode_object_concept_id integer NOT NULL,
episode_type_concept_id integer NOT NULL,
episode_source_value varchar(50) NULL,
episode_source_concept_id integer NULL );
-- EPISODE_EVENT
CREATE TABLE @cdmDatabaseSchema.EPISODE_EVENT (
episode_id bigint NOT NULL,
event_id bigint NOT NULL,
episode_event_field_concept_id integer NOT NULL );
-- METADATA
-- + Metadata_id
-- + Value_as_number
alter table @cdmDatabaseSchema.metadata add column metadata_id integer default null;
alter table @cdmDatabaseSchema.metadata add column value_as_number numeric default null;
-- CDM_SOURCE
-- Cdm_source_name -> Mandatory field
-- Cdm_source_abbreviation -> Mandatory field
-- Cdm_holder -> Mandatory field
-- Source_release_date -> Mandatory field
-- Cdm_release_date -> Mandatory field
-- + Cdm_version_concept_id
alter table @cdmDatabaseSchema.cdm_source rename to cdm_source_v53;
CREATE TABLE @cdmDatabaseSchema.cdm_source (
cdm_source_name varchar(255) NOT NULL,
cdm_source_abbreviation varchar(25) NOT NULL,
cdm_holder varchar(255) NOT NULL,
source_description text NULL,
source_documentation_reference varchar(255) NULL,
cdm_etl_reference varchar(255) NULL,
source_release_date date NOT NULL,
cdm_release_date date NOT NULL,
cdm_version varchar(10) NULL,
cdm_version_concept_id integer NOT NULL,
vocabulary_version varchar(20) NOT NULL );
insert into @cdmDatabaseSchema.cdm_source
select cdm_source_name,cdm_source_abbreviation,cdm_holder,
source_description,source_documentation_reference,cdm_etl_reference,
source_release_date,cdm_release_date,'5.4',
756265,vocabulary_version
from @cdmDatabaseSchema.cdm_source_v53;
-- VOCABULARY
-- Vocabulary_reference -> Non-mandatory field
-- Vocabulary_version -> Non-mandatory field
alter table @cdmDatabaseSchema.vocabulary rename to vocabulary_v53;
CREATE TABLE @cdmDatabaseSchema.vocabulary (
vocabulary_id varchar(20) NOT NULL,
vocabulary_name varchar(255) NOT NULL,
vocabulary_reference varchar(255) NULL,
vocabulary_version varchar(255) NULL,
vocabulary_concept_id integer NOT NULL );
insert into @cdmDatabaseSchema.vocabulary
select vocabulary_id,vocabulary_name,vocabulary_reference,
vocabulary_version, vocabulary_concept_id
from @cdmDatabaseSchema.vocabulary_v53;
-- ATTRIBUTE_DEFINITION
drop table @cdmDatabaseSchema.attribute_definition;
-- COHORT
CREATE TABLE @cdmDatabaseSchema.cohort (
cohort_definition_id integer NOT NULL,
subject_id integer NOT NULL,
cohort_start_date date NOT NULL,
cohort_end_date date NOT NULL );

View File

@ -0,0 +1,176 @@
-- http://ohdsi.github.io/CommonDataModel/cdm54Changes.html
-- Redshift SQL references:
-- https://docs.aws.amazon.com/redshift/latest/dg/r_ALTER_TABLE_examples_basic.html
-- https://docs.aws.amazon.com/redshift/latest/dg/r_ALTER_TABLE_COL_ex-add-drop.html
--
-- VISIT_OCCURRENCE
-- admitting_source_concept_id -> admitted_from_concept_id
-- admitting_source_value -> admitted_from_source_value
-- discharge_to_concept_id -> discharged_to_concept_id
-- discharge_to_source_value -> discharged_to_source_value
alter table @cdmDatabaseSchema.visit_occurrence rename column admitting_source_concept_id to admitted_from_concept_id;
alter table @cdmDatabaseSchema.visit_occurrence rename column admitting_source_value to admitted_from_source_value;
alter table @cdmDatabaseSchema.visit_occurrence rename column discharge_to_concept_id to discharged_to_concept_id;
alter table @cdmDatabaseSchema.visit_occurrence rename column discharge_to_source_value to discharged_to_source_value;
--
-- VISIT_DETAIL
-- admitting_source_concept_id -> admitted_from_concept_id
-- admitting_source_value -> admitted_from_source_value
-- discharge_to_concept_id -> discharged_to_concept_id
-- discharge_to_source_value -> discharged_to_source_value
-- visit_detail_parent_id -> parent_visit_detail_id
alter table @cdmDatabaseSchema.visit_detail rename column admitting_source_concept_id to admitted_from_concept_id;
alter table @cdmDatabaseSchema.visit_detail rename column admitting_source_value to admitted_from_source_value;
alter table @cdmDatabaseSchema.visit_detail rename column discharge_to_concept_id to discharged_to_concept_id;
alter table @cdmDatabaseSchema.visit_detail rename column discharge_to_source_value to discharged_to_source_value;
alter table @cdmDatabaseSchema.visit_detail rename column visit_detail_parent_id to parent_visit_detail_id;
-- PROCEDURE_OCCURRENCE
-- + Procedure_end_date
-- + Procedure_end_datetime
alter table @cdmDatabaseSchema.procedure_occurrence add column procedure_end_date date default null;
alter table @cdmDatabaseSchema.procedure_occurrence add column procedure_end_datetime timestamp default null;
-- DEVICE_EXPOSURE
-- Unique_device_id -> Changed to varchar(255)
-- + Production_id
-- + Unit_concept_id
-- + Unit_source_value
-- + Unit_source_concept_id
alter table @cdmDatabaseSchema.device_exposure alter column unique_device_id varchar(300);
alter table @cdmDatabaseSchema.device_exposure add column production_id integer default null;
alter table @cdmDatabaseSchema.device_exposure add column unit_concept_id integer default null;
alter table @cdmDatabaseSchema.device_exposure add column unit_source_value varchar(50) default null;
alter table @cdmDatabaseSchema.device_exposure add column unit_source_concept_id integer default null;
-- MEASUREMENT
-- + Unit_source_concept_id
-- + Measurement_event_id
-- + Meas_event_field_concept_id
alter table @cdmDatabaseSchema.measurement add column unit_source_concept_id integer default null;
alter table @cdmDatabaseSchema.measurement add column measurement_event_id bigint default null;
alter table @cdmDatabaseSchema.measurement add column meas_event_field_concept_id integer default null;
-- OBSERVATION
-- + Value_source_value
-- + Observation_event_id
-- + Obs_event_field_concept_id
alter table @cdmDatabaseSchema.observation add column value_source_value varchar(50) default null;
alter table @cdmDatabaseSchema.observation add column observation_event_id bigint default null;
alter table @cdmDatabaseSchema.observation add column obs_event_field_concept_id integer default null;
-- NOTE
-- + Note_event_id
-- + Note_event_field_concept_id
alter table @cdmDatabaseSchema.note add column note_event_id bigint default null;
alter table @cdmDatabaseSchema.note add column note_event_field_concept_id integer default null;
-- LOCATION
-- + Country_concept_id
-- + Country_source_value
-- + Latitude
-- + Longitude
alter table @cdmDatabaseSchema.location add column country_concept_id integer default null;
alter table @cdmDatabaseSchema.location add column country_source_value varchar(80) default null;
alter table @cdmDatabaseSchema.location add column latitude float default null;
alter table @cdmDatabaseSchema.location add column longitude float default null;
-- EPISODE
CREATE TABLE @cdmDatabaseSchema.EPISODE (
episode_id bigint NOT NULL,
person_id bigint NOT NULL,
episode_concept_id integer NOT NULL,
episode_start_date date NOT NULL,
episode_start_datetime TIMESTAMP NULL,
episode_end_date date NULL,
episode_end_datetime TIMESTAMP NULL,
episode_parent_id bigint NULL,
episode_number integer NULL,
episode_object_concept_id integer NOT NULL,
episode_type_concept_id integer NOT NULL,
episode_source_value varchar(50) NULL,
episode_source_concept_id integer NULL );
-- EPISODE_EVENT
CREATE TABLE @cdmDatabaseSchema.EPISODE_EVENT (
episode_id bigint NOT NULL,
event_id bigint NOT NULL,
episode_event_field_concept_id integer NOT NULL );
-- METADATA
-- + Metadata_id
-- + Value_as_number
alter table @cdmDatabaseSchema.metadata add column metadata_id integer default null;
alter table @cdmDatabaseSchema.metadata add column value_as_number float default null;
-- CDM_SOURCE
-- Cdm_source_name -> Mandatory field
-- Cdm_source_abbreviation -> Mandatory field
-- Cdm_holder -> Mandatory field
-- Source_release_date -> Mandatory field
-- Cdm_release_date -> Mandatory field
-- + Cdm_version_concept_id
alter table @cdmDatabaseSchema.cdm_source rename to cdm_source_v53;
CREATE TABLE @cdmDatabaseSchema.cdm_source (
cdm_source_name varchar(255) NOT NULL,
cdm_source_abbreviation varchar(25) NOT NULL,
cdm_holder varchar(255) NOT NULL,
source_description varchar(MAX) NULL,
source_documentation_reference varchar(255) NULL,
cdm_etl_reference varchar(255) NULL,
source_release_date date NOT NULL,
cdm_release_date date NOT NULL,
cdm_version varchar(10) NULL,
cdm_version_concept_id integer NOT NULL,
vocabulary_version varchar(20) NOT NULL );
insert into @cdmDatabaseSchema.cdm_source
select cdm_source_name,cdm_source_abbreviation,cdm_holder,
source_description,source_documentation_reference,cdm_etl_reference,
source_release_date,cdm_release_date,'5.4',
756265,vocabulary_version
from @cdmDatabaseSchema.cdm_source_v53;
-- VOCABULARY
-- Vocabulary_reference -> Non-mandatory field
-- Vocabulary_version -> Non-mandatory field
alter table @cdmDatabaseSchema.vocabulary rename to vocabulary_v53;
CREATE TABLE @cdmDatabaseSchema.vocabulary (
vocabulary_id varchar(20) NOT NULL,
vocabulary_name varchar(255) NOT NULL,
vocabulary_reference varchar(255) NULL,
vocabulary_version varchar(255) NULL,
vocabulary_concept_id integer NOT NULL );
insert into @cdmDatabaseSchema.vocabulary
select vocabulary_id,vocabulary_name,vocabulary_reference,
vocabulary_version, vocabulary_concept_id
from @cdmDatabaseSchema.vocabulary_v53;
-- ATTRIBUTE_DEFINITION
drop table @cdmDatabaseSchema.attribute_definition;
-- COHORT
CREATE TABLE @cdmDatabaseSchema.cohort (
cohort_definition_id integer NOT NULL,
subject_id integer NOT NULL,
cohort_start_date date NOT NULL,
cohort_end_date date NOT NULL );

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@ -0,0 +1,179 @@
-- http://ohdsi.github.io/CommonDataModel/cdm54Changes.html
-- SQL SERVER SQL References:
-- https://docs.microsoft.com/en-us/sql/relational-databases/tables/rename-columns-database-engine?view=sql-server-ver15
-- https://docs.microsoft.com/en-us/sql/relational-databases/system-stored-procedures/sp-rename-transact-sql?view=sql-server-ver15
-- https://docs.microsoft.com/en-us/sql/relational-databases/tables/add-columns-to-a-table-database-engine?view=sql-server-ver15
-- https://docs.microsoft.com/en-us/sql/relational-databases/tables/modify-columns-database-engine?view=sql-server-ver15
-- https://docs.microsoft.com/en-us/sql/t-sql/data-types/data-types-transact-sql?view=sql-server-ver15
--
-- VISIT_OCCURRENCE
-- admitting_source_concept_id -> admitted_from_concept_id
-- admitting_source_value -> admitted_from_source_value
-- discharge_to_concept_id -> discharged_to_concept_id
-- discharge_to_source_value -> discharged_to_source_value
EXEC sp_rename '@cdmDatabaseSchema.visit_occurrence.admitting_source_concept_id', 'admitted_from_concept_id', 'COLUMN';
EXEC sp_rename '@cdmDatabaseSchema.visit_occurrence.admitting_source_value', 'admitted_from_source_value', 'COLUMN';
EXEC sp_rename '@cdmDatabaseSchema.visit_occurrence.discharge_to_concept_id', 'discharged_to_concept_id', 'COLUMN';
EXEC sp_rename '@cdmDatabaseSchema.visit_occurrence.discharge_to_source_value', 'discharged_to_source_value', 'COLUMN';
--
-- VISIT_DETAIL
-- admitting_source_concept_id -> admitted_from_concept_id
-- admitting_source_value -> admitted_from_source_value
-- discharge_to_concept_id -> discharged_to_concept_id
-- discharge_to_source_value -> discharged_to_source_value
-- visit_detail_parent_id -> parent_visit_detail_id
EXEC sp_rename '@cdmDatabaseSchema.visit_detail.admitting_source_concept_id', 'admitted_from_concept_id', 'COLUMN';
EXEC sp_rename '@cdmDatabaseSchema.visit_detail.admitting_source_value', 'admitted_from_source_value', 'COLUMN';
EXEC sp_rename '@cdmDatabaseSchema.visit_detail.discharge_to_concept_id', 'discharged_to_concept_id', 'COLUMN';
EXEC sp_rename '@cdmDatabaseSchema.visit_detail.discharge_to_source_value', 'discharged_to_source_value', 'COLUMN';
EXEC sp_rename '@cdmDatabaseSchema.visit_detail.visit_detail_parent_id', 'parent_visit_detail_id', 'COLUMN';
-- PROCEDURE_OCCURRENCE
-- + Procedure_end_date
-- + Procedure_end_datetime
alter table @cdmDatabaseSchema.procedure_occurrence add procedure_end_date date null;
alter table @cdmDatabaseSchema.procedure_occurrence add procedure_end_datetime datetime null;
-- DEVICE_EXPOSURE
-- Unique_device_id -> Changed to varchar(255)
-- + Production_id
-- + Unit_concept_id
-- + Unit_source_value
-- + Unit_source_concept_id
alter table @cdmDatabaseSchema.device_exposure alter column unique_device_id varchar(300);
alter table @cdmDatabaseSchema.device_exposure add production_id int null;
alter table @cdmDatabaseSchema.device_exposure add unit_concept_id int null;
alter table @cdmDatabaseSchema.device_exposure add unit_source_value varchar(50) null;
alter table @cdmDatabaseSchema.device_exposure add unit_source_concept_id int null;
-- MEASUREMENT
-- + Unit_source_concept_id
-- + Measurement_event_id
-- + Meas_event_field_concept_id
alter table @cdmDatabaseSchema.measurement add unit_source_concept_id int null;
alter table @cdmDatabaseSchema.measurement add measurement_event_id bigint null;
alter table @cdmDatabaseSchema.measurement add meas_event_field_concept_id int null;
-- OBSERVATION
-- + Value_source_value
-- + Observation_event_id
-- + Obs_event_field_concept_id
alter table @cdmDatabaseSchema.observation add value_source_value varchar(50) null;
alter table @cdmDatabaseSchema.observation add observation_event_id bigint null;
alter table @cdmDatabaseSchema.observation add obs_event_field_concept_id int null;
-- NOTE
-- + Note_event_id
-- + Note_event_field_concept_id
alter table @cdmDatabaseSchema.note add note_event_id bigint null;
alter table @cdmDatabaseSchema.note add note_event_field_concept_id int null;
-- LOCATION
-- + Country_concept_id
-- + Country_source_value
-- + Latitude
-- + Longitude
alter table @cdmDatabaseSchema.location add country_concept_id int null;
alter table @cdmDatabaseSchema.location add country_source_value varchar(80) null;
alter table @cdmDatabaseSchema.location add latitude numeric null;
alter table @cdmDatabaseSchema.location add longitude numeric null;
-- EPISODE
CREATE TABLE @cdmDatabaseSchema.EPISODE (
episode_id bigint NOT NULL,
person_id bigint NOT NULL,
episode_concept_id int NOT NULL,
episode_start_date date NOT NULL,
episode_start_datetime datetime NULL,
episode_end_date date NULL,
episode_end_datetime datetime NULL,
episode_parent_id bigint NULL,
episode_number int NULL,
episode_object_concept_id int NOT NULL,
episode_type_concept_id int NOT NULL,
episode_source_value varchar(50) NULL,
episode_source_concept_id int NULL );
-- EPISODE_EVENT
CREATE TABLE @cdmDatabaseSchema.EPISODE_EVENT (
episode_id bigint NOT NULL,
event_id bigint NOT NULL,
episode_event_field_concept_id int NOT NULL );
-- METADATA
-- + Metadata_id
-- + Value_as_number
alter table @cdmDatabaseSchema.metadata add metadata_id int null;
alter table @cdmDatabaseSchema.metadata add value_as_number numeric null;
-- CDM_SOURCE
-- Cdm_source_name -> Mandatory field
-- Cdm_source_abbreviation -> Mandatory field
-- Cdm_holder -> Mandatory field
-- Source_release_date -> Mandatory field
-- Cdm_release_date -> Mandatory field
-- + Cdm_version_concept_id
EXEC sp_rename '@cdmDatabaseSchema.cdm_source', 'cdm_source_v53';
CREATE TABLE @cdmDatabaseSchema.cdm_source (
cdm_source_name varchar(255) NOT NULL,
cdm_source_abbreviation varchar(25) NOT NULL,
cdm_holder varchar(255) NOT NULL,
source_description varchar(MAX) NULL,
source_documentation_reference varchar(255) NULL,
cdm_etl_reference varchar(255) NULL,
source_release_date date NOT NULL,
cdm_release_date date NOT NULL,
cdm_version varchar(10) NULL,
cdm_version_concept_id int NOT NULL,
vocabulary_version varchar(20) NOT NULL );
insert into @cdmDatabaseSchema.cdm_source
select cdm_source_name,cdm_source_abbreviation,cdm_holder,
source_description,source_documentation_reference,cdm_etl_reference,
source_release_date,cdm_release_date,'5.4',
756265,vocabulary_version
from @cdmDatabaseSchema.cdm_source_v53;
-- VOCABULARY
-- Vocabulary_reference -> Non-mandatory field
-- Vocabulary_version -> Non-mandatory field
EXEC sp_rename '@cdmDatabaseSchema.vocabulary', 'vocabulary_v53';
CREATE TABLE @cdmDatabaseSchema.vocabulary (
vocabulary_id varchar(20) NOT NULL,
vocabulary_name varchar(255) NOT NULL,
vocabulary_reference varchar(255) NULL,
vocabulary_version varchar(255) NULL,
vocabulary_concept_id int NOT NULL );
insert into @cdmDatabaseSchema.vocabulary
select vocabulary_id,vocabulary_name,vocabulary_reference,
vocabulary_version, vocabulary_concept_id
from @cdmDatabaseSchema.vocabulary_v53;
-- ATTRIBUTE_DEFINITION
drop table @cdmDatabaseSchema.attribute_definition;
-- COHORT
CREATE TABLE @cdmDatabaseSchema.cohort (
cohort_definition_id int NOT NULL,
subject_id int NOT NULL,
cohort_start_date date NOT NULL,
cohort_end_date date NOT NULL );

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with cdm_v540 as (
select *
from information_schema.columns
where table_schema = 'cdm_v540' --> ENTER YOUR V5.4 CDM HERE
and table_name not in ('cohort','cohort_attribute','cohort_definition')
), cdm_v601 as (
select *
from information_schema.columns
where table_schema = 'cdm_v601' --> ENTER YOUR V6.0 CDM HERE
and table_name not in ('cohort','cohort_attribute','cohort_definition')
)
select a.table_name,
a.column_name,
a.is_nullable v54_nullable,
b.is_nullable v60_nullable,
a.data_type v54_datatype,
b.data_type v60_datatype
from cdm_v540 a
join cdm_v601 b
on a.table_name = b.table_name
and a.column_name = b.column_name
and (a.is_nullable != b.is_nullable or a.data_type != b.data_type)
order by 1,2;

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--
-- RETRIEVE TABLE AND COLUMN NAMES FOR V5.4 AND V6.0 CDMS.
-- SUPPLY THE NAME OF EACH SCHEMA WHERE INDICATED.
-- THE "STATUS" COLUMN:
-- "IN BOTH": INDICATES COLUMN IS IN BOTH 5.4 AND 6.0
-- "MISSING FROM v6.0.1": INDICATES COLUMN IS IN BOTH 5.4 BUT NOT 6.0 AND NEEDS TO BE ADDED OR RENAMED
-- "MISSING FROM v5.4.0": INDICATES COLUMN IS IN BOTH 6.0 BUT NOT 5.4 AND NEED TO BE DROPPED OR RENAMED
with cdm_v540 as (
select *
from information_schema.columns
where table_schema = 'cdm_v540' --> YOUR V5.4 CDM SCHEMA NAME HERE
and table_name not in ('_version','cohort','cohort_attribute','cohort_definition')
), cdm_v601 as (
select *
from information_schema.columns
where table_schema = 'cdm_v601' --> YOUR V6.0 CDM SCHEMA NAME HERE
and table_name not in ('_version','cohort','cohort_attribute','cohort_definition')
)
select a.table_name,
a.column_name,
'IN BOTH' status
from cdm_v540 a
join cdm_v601 b
on a.table_name = b.table_name
and a.column_name = b.column_name
union all
select a.table_name,
a.column_name,
'MISSING FROM v6.0.1' status
from cdm_v540 a
left join cdm_v601 b
on a.table_name = b.table_name
and a.column_name = b.column_name
where b.column_name is null
union all
select b.table_name,
b.column_name,
'MISSING FROM v5.4.0' status
from cdm_v540 a
right join cdm_v601 b
on a.table_name = b.table_name
and a.column_name = b.column_name
where a.column_name is null
order by 1,3;

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table_name | column_name | v54_nullable | v60_nullable | v54_datatype | v60_datatype
----------------------+--------------------------------+--------------+--------------+-----------------------------+----------------------------
care_site | care_site_id | YES | NO | bigint | bigint
care_site | place_of_service_concept_id | YES | NO | integer | integer
cdm_source | cdm_holder | NO | YES | character varying | character varying
cdm_source | cdm_release_date | NO | YES | date | date
cdm_source | cdm_source_abbreviation | NO | YES | character varying | character varying
cdm_source | source_release_date | NO | YES | date | date
cdm_source | vocabulary_version | NO | YES | character varying | character varying
concept | concept_class_id | YES | NO | character varying | character varying
concept | concept_code | YES | NO | character varying | character varying
concept | concept_id | YES | NO | integer | integer
concept | concept_name | YES | NO | character varying | character varying
concept | domain_id | YES | NO | character varying | character varying
concept | valid_end_date | YES | NO | date | date
concept | valid_start_date | YES | NO | date | date
concept | vocabulary_id | YES | NO | character varying | character varying
concept_ancestor | ancestor_concept_id | YES | NO | integer | integer
concept_ancestor | descendant_concept_id | YES | NO | integer | integer
concept_ancestor | max_levels_of_separation | YES | NO | integer | integer
concept_ancestor | min_levels_of_separation | YES | NO | integer | integer
concept_class | concept_class_concept_id | YES | NO | integer | integer
concept_class | concept_class_id | YES | NO | character varying | character varying
concept_class | concept_class_name | YES | NO | character varying | character varying
concept_relationship | concept_id_1 | YES | NO | integer | integer
concept_relationship | concept_id_2 | YES | NO | integer | integer
concept_relationship | relationship_id | YES | NO | character varying | character varying
concept_relationship | valid_end_date | YES | NO | date | date
concept_relationship | valid_start_date | YES | NO | date | date
concept_synonym | concept_id | YES | NO | integer | integer
concept_synonym | concept_synonym_name | YES | NO | character varying | character varying
concept_synonym | language_concept_id | YES | NO | integer | integer
condition_era | condition_concept_id | YES | NO | integer | integer
condition_era | condition_era_id | YES | NO | bigint | bigint
condition_era | person_id | YES | NO | bigint | bigint
condition_occurrence | condition_concept_id | YES | NO | integer | integer
condition_occurrence | condition_occurrence_id | YES | NO | bigint | bigint
condition_occurrence | condition_source_concept_id | YES | NO | integer | integer
condition_occurrence | condition_start_date | YES | NO | date | date
condition_occurrence | condition_status_concept_id | YES | NO | integer | integer
condition_occurrence | condition_type_concept_id | YES | NO | integer | integer
condition_occurrence | person_id | YES | NO | bigint | bigint
cost | cost_event_id | YES | NO | bigint | bigint
cost | cost_id | YES | NO | bigint | bigint
cost | payer_plan_period_id | YES | YES | integer | bigint
device_exposure | device_concept_id | YES | NO | integer | integer
device_exposure | device_exposure_id | YES | NO | bigint | bigint
device_exposure | device_exposure_start_date | YES | NO | date | date
device_exposure | device_source_concept_id | YES | NO | integer | integer
device_exposure | device_type_concept_id | YES | NO | integer | integer
device_exposure | person_id | YES | NO | bigint | bigint
domain | domain_concept_id | YES | NO | integer | integer
domain | domain_id | YES | NO | character varying | character varying
domain | domain_name | YES | NO | character varying | character varying
dose_era | dose_era_id | YES | NO | bigint | bigint
dose_era | dose_value | YES | NO | double precision | double precision
dose_era | drug_concept_id | YES | NO | integer | integer
dose_era | person_id | YES | NO | bigint | bigint
dose_era | unit_concept_id | YES | NO | integer | integer
drug_era | drug_concept_id | YES | NO | integer | integer
drug_era | drug_era_id | YES | NO | bigint | bigint
drug_era | person_id | YES | NO | bigint | bigint
drug_exposure | drug_concept_id | YES | NO | integer | integer
drug_exposure | drug_exposure_end_date | YES | NO | date | date
drug_exposure | drug_exposure_id | YES | NO | bigint | bigint
drug_exposure | drug_exposure_start_date | YES | NO | date | date
drug_exposure | drug_source_concept_id | YES | NO | integer | integer
drug_exposure | drug_type_concept_id | YES | NO | integer | integer
drug_exposure | person_id | YES | NO | bigint | bigint
drug_strength | drug_concept_id | YES | NO | integer | integer
drug_strength | ingredient_concept_id | YES | NO | integer | integer
drug_strength | valid_end_date | YES | NO | date | date
drug_strength | valid_start_date | YES | NO | date | date
fact_relationship | domain_concept_id_1 | YES | NO | integer | integer
fact_relationship | domain_concept_id_2 | YES | NO | integer | integer
fact_relationship | fact_id_1 | YES | NO | bigint | bigint
fact_relationship | fact_id_2 | YES | NO | bigint | bigint
fact_relationship | relationship_concept_id | YES | NO | integer | integer
location | location_id | YES | NO | bigint | bigint
measurement | measurement_concept_id | YES | NO | integer | integer
measurement | measurement_date | YES | NO | date | date
measurement | measurement_id | YES | NO | bigint | bigint
measurement | measurement_source_concept_id | YES | NO | integer | integer
measurement | measurement_time | YES | YES | timestamp without time zone | character varying
measurement | measurement_type_concept_id | YES | NO | integer | integer
measurement | person_id | YES | NO | bigint | bigint
metadata | metadata_concept_id | YES | NO | integer | integer
metadata | metadata_type_concept_id | YES | NO | integer | integer
metadata | name | YES | NO | character varying | character varying
note | encoding_concept_id | YES | NO | integer | integer
note | language_concept_id | YES | NO | integer | integer
note | note_class_concept_id | YES | NO | integer | integer
note | note_date | YES | NO | date | date
note | note_id | YES | NO | bigint | integer
note | note_text | YES | NO | character varying | character varying
note | note_type_concept_id | YES | NO | integer | integer
note | person_id | YES | NO | bigint | bigint
note | provider_id | YES | YES | integer | bigint
note_nlp | lexical_variant | YES | NO | character varying | character varying
note_nlp | nlp_date | YES | NO | date | date
note_nlp | note_id | YES | NO | bigint | integer
note_nlp | note_nlp_id | YES | NO | bigint | bigint
observation | observation_concept_id | YES | NO | integer | integer
observation | observation_datetime | YES | NO | timestamp without time zone | timestamp without time zone
observation | observation_id | YES | NO | bigint | bigint
observation | observation_source_concept_id | YES | NO | integer | integer
observation | observation_type_concept_id | YES | NO | integer | integer
observation | person_id | YES | NO | bigint | bigint
observation_period | observation_period_end_date | YES | NO | date | date
observation_period | observation_period_id | YES | NO | bigint | bigint
observation_period | observation_period_start_date | YES | NO | date | date
observation_period | period_type_concept_id | YES | NO | integer | integer
observation_period | person_id | YES | NO | bigint | bigint
payer_plan_period | payer_concept_id | YES | NO | integer | integer
payer_plan_period | payer_plan_period_end_date | YES | NO | date | date
payer_plan_period | payer_plan_period_id | YES | NO | integer | bigint
payer_plan_period | payer_plan_period_start_date | YES | NO | date | date
payer_plan_period | payer_source_concept_id | YES | NO | integer | integer
payer_plan_period | person_id | YES | NO | integer | bigint
payer_plan_period | plan_concept_id | YES | NO | integer | integer
payer_plan_period | plan_source_concept_id | YES | NO | integer | integer
payer_plan_period | sponsor_concept_id | YES | NO | integer | integer
person | ethnicity_concept_id | YES | NO | integer | integer
person | ethnicity_source_concept_id | YES | NO | integer | integer
person | gender_concept_id | YES | NO | integer | integer
person | gender_source_concept_id | YES | NO | integer | integer
person | person_id | YES | NO | bigint | bigint
person | race_concept_id | YES | NO | integer | integer
person | race_source_concept_id | YES | NO | integer | integer
person | year_of_birth | YES | NO | integer | integer
procedure_occurrence | person_id | YES | NO | bigint | bigint
procedure_occurrence | procedure_concept_id | YES | NO | integer | integer
procedure_occurrence | procedure_datetime | YES | NO | timestamp without time zone | timestamp without time zone
procedure_occurrence | procedure_occurrence_id | YES | NO | bigint | bigint
procedure_occurrence | procedure_source_concept_id | YES | NO | integer | integer
procedure_occurrence | procedure_type_concept_id | YES | NO | integer | integer
provider | gender_concept_id | YES | NO | integer | integer
provider | gender_source_concept_id | YES | NO | integer | integer
provider | provider_id | YES | NO | bigint | bigint
provider | specialty_concept_id | YES | NO | integer | integer
provider | specialty_source_concept_id | YES | NO | integer | integer
provider | year_of_birth | YES | YES | bigint | integer
relationship | defines_ancestry | YES | NO | character varying | character varying
relationship | is_hierarchical | YES | NO | character varying | character varying
relationship | relationship_concept_id | YES | NO | integer | integer
relationship | relationship_id | YES | NO | character varying | character varying
relationship | relationship_name | YES | NO | character varying | character varying
relationship | reverse_relationship_id | YES | NO | character varying | character varying
source_to_concept_map | source_code | YES | NO | character varying | character varying
source_to_concept_map | source_concept_id | YES | NO | integer | integer
source_to_concept_map | source_vocabulary_id | YES | NO | character varying | character varying
source_to_concept_map | target_concept_id | YES | NO | integer | integer
source_to_concept_map | target_vocabulary_id | YES | NO | character varying | character varying
source_to_concept_map | valid_end_date | YES | NO | date | date
source_to_concept_map | valid_start_date | YES | NO | date | date
specimen | person_id | YES | NO | bigint | bigint
specimen | specimen_concept_id | YES | NO | integer | integer
specimen | specimen_date | YES | NO | date | date
specimen | specimen_id | YES | NO | bigint | bigint
specimen | specimen_type_concept_id | YES | NO | integer | integer
visit_detail | admitted_from_concept_id | YES | YES | integer | character varying
visit_detail | admitted_from_source_value | YES | NO | character varying | integer
visit_detail | care_site_id | YES | YES | integer | bigint
visit_detail | person_id | YES | NO | bigint | bigint
visit_detail | preceding_visit_detail_id | YES | YES | integer | bigint
visit_detail | provider_id | YES | YES | integer | bigint
visit_detail | visit_detail_concept_id | YES | NO | integer | integer
visit_detail | visit_detail_end_date | YES | NO | date | date
visit_detail | visit_detail_id | YES | NO | bigint | bigint
visit_detail | visit_detail_source_concept_id | YES | NO | integer | integer
visit_detail | visit_detail_start_date | YES | NO | date | date
visit_detail | visit_detail_type_concept_id | YES | NO | integer | integer
visit_detail | visit_occurrence_id | YES | NO | bigint | bigint
visit_occurrence | admitted_from_concept_id | YES | NO | integer | integer
visit_occurrence | person_id | YES | NO | bigint | bigint
visit_occurrence | visit_concept_id | YES | NO | integer | integer
visit_occurrence | visit_end_datetime | YES | NO | timestamp without time zone | timestamp without time zone
visit_occurrence | visit_occurrence_id | YES | NO | bigint | bigint
visit_occurrence | visit_source_concept_id | YES | NO | integer | integer
visit_occurrence | visit_start_datetime | YES | NO | timestamp without time zone | timestamp without time zone
visit_occurrence | visit_type_concept_id | YES | NO | integer | integer
vocabulary | vocabulary_reference | YES | NO | character varying | character varying

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table_name | column_name | status
----------------------+--------------------------------+--------------------
care_site | care_site_id | IN BOTH
care_site | place_of_service_concept_id | IN BOTH
care_site | location_id | IN BOTH
care_site | care_site_name | IN BOTH
care_site | care_site_source_value | IN BOTH
care_site | place_of_service_source_value | IN BOTH
cdm_source | cdm_source_name | IN BOTH
cdm_source | cdm_source_abbreviation | IN BOTH
cdm_source | cdm_holder | IN BOTH
cdm_source | source_description | IN BOTH
cdm_source | source_documentation_reference | IN BOTH
cdm_source | cdm_etl_reference | IN BOTH
cdm_source | source_release_date | IN BOTH
cdm_source | cdm_release_date | IN BOTH
cdm_source | cdm_version | IN BOTH
cdm_source | vocabulary_version | IN BOTH
cdm_source | cdm_version_concept_id | MISSING FROM v6.0.1
concept | concept_id | IN BOTH
concept | valid_start_date | IN BOTH
concept | valid_end_date | IN BOTH
concept | concept_name | IN BOTH
concept | domain_id | IN BOTH
concept | vocabulary_id | IN BOTH
concept | concept_class_id | IN BOTH
concept | standard_concept | IN BOTH
concept | concept_code | IN BOTH
concept | invalid_reason | IN BOTH
concept_ancestor | ancestor_concept_id | IN BOTH
concept_ancestor | descendant_concept_id | IN BOTH
concept_ancestor | min_levels_of_separation | IN BOTH
concept_ancestor | max_levels_of_separation | IN BOTH
concept_class | concept_class_concept_id | IN BOTH
concept_class | concept_class_id | IN BOTH
concept_class | concept_class_name | IN BOTH
concept_relationship | concept_id_1 | IN BOTH
concept_relationship | concept_id_2 | IN BOTH
concept_relationship | valid_start_date | IN BOTH
concept_relationship | valid_end_date | IN BOTH
concept_relationship | relationship_id | IN BOTH
concept_relationship | invalid_reason | IN BOTH
concept_synonym | concept_id | IN BOTH
concept_synonym | language_concept_id | IN BOTH
concept_synonym | concept_synonym_name | IN BOTH
condition_era | condition_era_id | IN BOTH
condition_era | person_id | IN BOTH
condition_era | condition_concept_id | IN BOTH
condition_era | condition_occurrence_count | IN BOTH
condition_era | condition_era_start_datetime | MISSING FROM v5.4.0
condition_era | condition_era_end_datetime | MISSING FROM v5.4.0
condition_era | condition_era_start_date | MISSING FROM v6.0.1
condition_era | condition_era_end_date | MISSING FROM v6.0.1
condition_occurrence | condition_occurrence_id | IN BOTH
condition_occurrence | person_id | IN BOTH
condition_occurrence | condition_concept_id | IN BOTH
condition_occurrence | condition_start_date | IN BOTH
condition_occurrence | condition_start_datetime | IN BOTH
condition_occurrence | condition_end_date | IN BOTH
condition_occurrence | condition_end_datetime | IN BOTH
condition_occurrence | condition_type_concept_id | IN BOTH
condition_occurrence | provider_id | IN BOTH
condition_occurrence | visit_occurrence_id | IN BOTH
condition_occurrence | visit_detail_id | IN BOTH
condition_occurrence | condition_source_concept_id | IN BOTH
condition_occurrence | condition_status_concept_id | IN BOTH
condition_occurrence | stop_reason | IN BOTH
condition_occurrence | condition_source_value | IN BOTH
condition_occurrence | condition_status_source_value | IN BOTH
cost | cost_id | IN BOTH
cost | cost_event_id | IN BOTH
cost | cost_type_concept_id | IN BOTH
cost | currency_concept_id | IN BOTH
cost | payer_plan_period_id | IN BOTH
cost | revenue_code_concept_id | IN BOTH
cost | drg_concept_id | IN BOTH
cost | drg_source_value | IN BOTH
cost | person_id | MISSING FROM v5.4.0
cost | cost_event_field_concept_id | MISSING FROM v5.4.0
cost | cost_concept_id | MISSING FROM v5.4.0
cost | cost_source_concept_id | MISSING FROM v5.4.0
cost | cost_source_value | MISSING FROM v5.4.0
cost | cost | MISSING FROM v5.4.0
cost | incurred_date | MISSING FROM v5.4.0
cost | billed_date | MISSING FROM v5.4.0
cost | paid_date | MISSING FROM v5.4.0
cost | revenue_code_source_value | MISSING FROM v5.4.0
cost | total_charge | MISSING FROM v6.0.1
cost | total_cost | MISSING FROM v6.0.1
cost | total_paid | MISSING FROM v6.0.1
cost | paid_by_payer | MISSING FROM v6.0.1
cost | paid_by_patient | MISSING FROM v6.0.1
cost | paid_patient_copay | MISSING FROM v6.0.1
cost | paid_patient_coinsurance | MISSING FROM v6.0.1
cost | paid_patient_deductible | MISSING FROM v6.0.1
cost | paid_by_primary | MISSING FROM v6.0.1
cost | paid_ingredient_cost | MISSING FROM v6.0.1
cost | paid_dispensing_fee | MISSING FROM v6.0.1
cost | amount_allowed | MISSING FROM v6.0.1
cost | cost_domain_id | MISSING FROM v6.0.1
cost | reveue_code_source_value | MISSING FROM v6.0.1
death | person_id | MISSING FROM v6.0.1
death | death_date | MISSING FROM v6.0.1
death | death_datetime | MISSING FROM v6.0.1
death | death_type_concept_id | MISSING FROM v6.0.1
death | cause_concept_id | MISSING FROM v6.0.1
death | cause_source_concept_id | MISSING FROM v6.0.1
death | cause_source_value | MISSING FROM v6.0.1
device_exposure | device_exposure_id | IN BOTH
device_exposure | person_id | IN BOTH
device_exposure | device_concept_id | IN BOTH
device_exposure | device_exposure_start_date | IN BOTH
device_exposure | device_exposure_start_datetime | IN BOTH
device_exposure | device_exposure_end_date | IN BOTH
device_exposure | device_exposure_end_datetime | IN BOTH
device_exposure | device_type_concept_id | IN BOTH
device_exposure | quantity | IN BOTH
device_exposure | provider_id | IN BOTH
device_exposure | visit_occurrence_id | IN BOTH
device_exposure | visit_detail_id | IN BOTH
device_exposure | device_source_concept_id | IN BOTH
device_exposure | device_source_value | IN BOTH
device_exposure | unique_device_id | IN BOTH
device_exposure | production_id | MISSING FROM v6.0.1
device_exposure | unit_concept_id | MISSING FROM v6.0.1
device_exposure | unit_source_value | MISSING FROM v6.0.1
device_exposure | unit_source_concept_id | MISSING FROM v6.0.1
domain | domain_concept_id | IN BOTH
domain | domain_id | IN BOTH
domain | domain_name | IN BOTH
dose_era | dose_era_id | IN BOTH
dose_era | person_id | IN BOTH
dose_era | drug_concept_id | IN BOTH
dose_era | unit_concept_id | IN BOTH
dose_era | dose_value | IN BOTH
dose_era | dose_era_start_datetime | MISSING FROM v5.4.0
dose_era | dose_era_end_datetime | MISSING FROM v5.4.0
dose_era | dose_era_start_date | MISSING FROM v6.0.1
dose_era | dose_era_end_date | MISSING FROM v6.0.1
drug_era | drug_era_id | IN BOTH
drug_era | person_id | IN BOTH
drug_era | drug_concept_id | IN BOTH
drug_era | drug_exposure_count | IN BOTH
drug_era | gap_days | IN BOTH
drug_era | drug_era_start_datetime | MISSING FROM v5.4.0
drug_era | drug_era_end_datetime | MISSING FROM v5.4.0
drug_era | drug_era_start_date | MISSING FROM v6.0.1
drug_era | drug_era_end_date | MISSING FROM v6.0.1
drug_exposure | drug_exposure_id | IN BOTH
drug_exposure | person_id | IN BOTH
drug_exposure | drug_concept_id | IN BOTH
drug_exposure | drug_exposure_start_date | IN BOTH
drug_exposure | drug_exposure_start_datetime | IN BOTH
drug_exposure | drug_exposure_end_date | IN BOTH
drug_exposure | drug_exposure_end_datetime | IN BOTH
drug_exposure | verbatim_end_date | IN BOTH
drug_exposure | drug_type_concept_id | IN BOTH
drug_exposure | refills | IN BOTH
drug_exposure | quantity | IN BOTH
drug_exposure | days_supply | IN BOTH
drug_exposure | route_concept_id | IN BOTH
drug_exposure | provider_id | IN BOTH
drug_exposure | visit_occurrence_id | IN BOTH
drug_exposure | visit_detail_id | IN BOTH
drug_exposure | drug_source_concept_id | IN BOTH
drug_exposure | stop_reason | IN BOTH
drug_exposure | sig | IN BOTH
drug_exposure | lot_number | IN BOTH
drug_exposure | drug_source_value | IN BOTH
drug_exposure | route_source_value | IN BOTH
drug_exposure | dose_unit_source_value | IN BOTH
drug_strength | drug_concept_id | IN BOTH
drug_strength | ingredient_concept_id | IN BOTH
drug_strength | amount_value | IN BOTH
drug_strength | amount_unit_concept_id | IN BOTH
drug_strength | numerator_value | IN BOTH
drug_strength | numerator_unit_concept_id | IN BOTH
drug_strength | denominator_value | IN BOTH
drug_strength | denominator_unit_concept_id | IN BOTH
drug_strength | box_size | IN BOTH
drug_strength | valid_start_date | IN BOTH
drug_strength | valid_end_date | IN BOTH
drug_strength | invalid_reason | IN BOTH
episode | episode_id | MISSING FROM v6.0.1
episode | person_id | MISSING FROM v6.0.1
episode | episode_concept_id | MISSING FROM v6.0.1
episode | episode_start_date | MISSING FROM v6.0.1
episode | episode_start_datetime | MISSING FROM v6.0.1
episode | episode_end_date | MISSING FROM v6.0.1
episode | episode_end_datetime | MISSING FROM v6.0.1
episode | episode_parent_id | MISSING FROM v6.0.1
episode | episode_number | MISSING FROM v6.0.1
episode | episode_object_concept_id | MISSING FROM v6.0.1
episode | episode_type_concept_id | MISSING FROM v6.0.1
episode | episode_source_value | MISSING FROM v6.0.1
episode | episode_source_concept_id | MISSING FROM v6.0.1
episode_event | episode_id | MISSING FROM v6.0.1
episode_event | event_id | MISSING FROM v6.0.1
episode_event | episode_event_field_concept_id | MISSING FROM v6.0.1
fact_relationship | domain_concept_id_1 | IN BOTH
fact_relationship | fact_id_1 | IN BOTH
fact_relationship | domain_concept_id_2 | IN BOTH
fact_relationship | fact_id_2 | IN BOTH
fact_relationship | relationship_concept_id | IN BOTH
location | location_id | IN BOTH
location | address_1 | IN BOTH
location | address_2 | IN BOTH
location | city | IN BOTH
location | state | IN BOTH
location | zip | IN BOTH
location | county | IN BOTH
location | location_source_value | IN BOTH
location | latitude | IN BOTH
location | longitude | IN BOTH
location | country_concept_id | MISSING FROM v6.0.1
location | country_source_value | MISSING FROM v6.0.1
location_history | location_id | MISSING FROM v5.4.0
location_history | relationship_type_concept_id | MISSING FROM v5.4.0
location_history | domain_id | MISSING FROM v5.4.0
location_history | entity_id | MISSING FROM v5.4.0
location_history | start_date | MISSING FROM v5.4.0
location_history | end_date | MISSING FROM v5.4.0
measurement | measurement_id | IN BOTH
measurement | person_id | IN BOTH
measurement | measurement_concept_id | IN BOTH
measurement | measurement_date | IN BOTH
measurement | measurement_datetime | IN BOTH
measurement | measurement_time | IN BOTH
measurement | measurement_type_concept_id | IN BOTH
measurement | operator_concept_id | IN BOTH
measurement | value_as_number | IN BOTH
measurement | value_as_concept_id | IN BOTH
measurement | unit_concept_id | IN BOTH
measurement | range_low | IN BOTH
measurement | range_high | IN BOTH
measurement | provider_id | IN BOTH
measurement | visit_occurrence_id | IN BOTH
measurement | visit_detail_id | IN BOTH
measurement | measurement_source_concept_id | IN BOTH
measurement | measurement_source_value | IN BOTH
measurement | unit_source_value | IN BOTH
measurement | value_source_value | IN BOTH
measurement | unit_source_id | MISSING FROM v6.0.1
measurement | measurement_event_id | MISSING FROM v6.0.1
measurement | meas_event_field_concept_id | MISSING FROM v6.0.1
metadata | metadata_concept_id | IN BOTH
metadata | metadata_type_concept_id | IN BOTH
metadata | value_as_concept_id | IN BOTH
metadata | metadata_date | IN BOTH
metadata | metadata_datetime | IN BOTH
metadata | name | IN BOTH
metadata | value_as_string | IN BOTH
metadata | metadata_id | MISSING FROM v6.0.1
metadata | value_as_number | MISSING FROM v6.0.1
note | note_id | IN BOTH
note | person_id | IN BOTH
note | note_date | IN BOTH
note | note_datetime | IN BOTH
note | note_type_concept_id | IN BOTH
note | note_class_concept_id | IN BOTH
note | encoding_concept_id | IN BOTH
note | language_concept_id | IN BOTH
note | provider_id | IN BOTH
note | visit_occurrence_id | IN BOTH
note | visit_detail_id | IN BOTH
note | note_title | IN BOTH
note | note_text | IN BOTH
note | note_source_value | IN BOTH
note | note_event_id | IN BOTH
note | note_event_field_concept_id | IN BOTH
note_nlp | note_nlp_id | IN BOTH
note_nlp | note_id | IN BOTH
note_nlp | section_concept_id | IN BOTH
note_nlp | note_nlp_concept_id | IN BOTH
note_nlp | note_nlp_source_concept_id | IN BOTH
note_nlp | nlp_date | IN BOTH
note_nlp | nlp_datetime | IN BOTH
note_nlp | snippet | IN BOTH
note_nlp | offset | IN BOTH
note_nlp | lexical_variant | IN BOTH
note_nlp | nlp_system | IN BOTH
note_nlp | term_exists | IN BOTH
note_nlp | term_temporal | IN BOTH
note_nlp | term_modifiers | IN BOTH
observation | observation_id | IN BOTH
observation | person_id | IN BOTH
observation | observation_concept_id | IN BOTH
observation | observation_date | IN BOTH
observation | observation_datetime | IN BOTH
observation | observation_type_concept_id | IN BOTH
observation | value_as_number | IN BOTH
observation | value_as_concept_id | IN BOTH
observation | qualifier_concept_id | IN BOTH
observation | unit_concept_id | IN BOTH
observation | provider_id | IN BOTH
observation | visit_occurrence_id | IN BOTH
observation | visit_detail_id | IN BOTH
observation | observation_source_concept_id | IN BOTH
observation | value_as_string | IN BOTH
observation | observation_source_value | IN BOTH
observation | unit_source_value | IN BOTH
observation | qualifier_source_value | IN BOTH
observation | observation_event_id | IN BOTH
observation | obs_event_field_concept_id | IN BOTH
observation | value_as_datetime | MISSING FROM v5.4.0
observation | value_source_value | MISSING FROM v6.0.1
observation_period | observation_period_id | IN BOTH
observation_period | person_id | IN BOTH
observation_period | observation_period_start_date | IN BOTH
observation_period | observation_period_end_date | IN BOTH
observation_period | period_type_concept_id | IN BOTH
payer_plan_period | payer_plan_period_id | IN BOTH
payer_plan_period | person_id | IN BOTH
payer_plan_period | payer_plan_period_start_date | IN BOTH
payer_plan_period | payer_plan_period_end_date | IN BOTH
payer_plan_period | payer_concept_id | IN BOTH
payer_plan_period | payer_source_concept_id | IN BOTH
payer_plan_period | plan_concept_id | IN BOTH
payer_plan_period | plan_source_concept_id | IN BOTH
payer_plan_period | sponsor_concept_id | IN BOTH
payer_plan_period | sponsor_source_concept_id | IN BOTH
payer_plan_period | stop_reason_concept_id | IN BOTH
payer_plan_period | stop_reason_source_concept_id | IN BOTH
payer_plan_period | payer_source_value | IN BOTH
payer_plan_period | plan_source_value | IN BOTH
payer_plan_period | sponsor_source_value | IN BOTH
payer_plan_period | family_source_value | IN BOTH
payer_plan_period | stop_reason_source_value | IN BOTH
payer_plan_period | contract_person_id | MISSING FROM v5.4.0
payer_plan_period | contract_concept_id | MISSING FROM v5.4.0
payer_plan_period | contract_source_value | MISSING FROM v5.4.0
payer_plan_period | contract_source_concept_id | MISSING FROM v5.4.0
person | person_id | IN BOTH
person | gender_concept_id | IN BOTH
person | year_of_birth | IN BOTH
person | month_of_birth | IN BOTH
person | day_of_birth | IN BOTH
person | birth_datetime | IN BOTH
person | race_concept_id | IN BOTH
person | ethnicity_concept_id | IN BOTH
person | location_id | IN BOTH
person | provider_id | IN BOTH
person | care_site_id | IN BOTH
person | gender_source_concept_id | IN BOTH
person | race_source_concept_id | IN BOTH
person | ethnicity_source_concept_id | IN BOTH
person | person_source_value | IN BOTH
person | gender_source_value | IN BOTH
person | race_source_value | IN BOTH
person | ethnicity_source_value | IN BOTH
person | death_datetime | MISSING FROM v5.4.0
procedure_occurrence | procedure_occurrence_id | IN BOTH
procedure_occurrence | person_id | IN BOTH
procedure_occurrence | procedure_concept_id | IN BOTH
procedure_occurrence | procedure_date | IN BOTH
procedure_occurrence | procedure_datetime | IN BOTH
procedure_occurrence | procedure_type_concept_id | IN BOTH
procedure_occurrence | modifier_concept_id | IN BOTH
procedure_occurrence | quantity | IN BOTH
procedure_occurrence | provider_id | IN BOTH
procedure_occurrence | visit_occurrence_id | IN BOTH
procedure_occurrence | visit_detail_id | IN BOTH
procedure_occurrence | procedure_source_concept_id | IN BOTH
procedure_occurrence | procedure_source_value | IN BOTH
procedure_occurrence | modifier_source_value | IN BOTH
procedure_occurrence | procedure_end_date | MISSING FROM v6.0.1
procedure_occurrence | procedure_end_datetime | MISSING FROM v6.0.1
provider | provider_id | IN BOTH
provider | specialty_concept_id | IN BOTH
provider | care_site_id | IN BOTH
provider | year_of_birth | IN BOTH
provider | gender_concept_id | IN BOTH
provider | specialty_source_concept_id | IN BOTH
provider | gender_source_concept_id | IN BOTH
provider | provider_name | IN BOTH
provider | npi | IN BOTH
provider | dea | IN BOTH
provider | provider_source_value | IN BOTH
provider | specialty_source_value | IN BOTH
provider | gender_source_value | IN BOTH
relationship | relationship_concept_id | IN BOTH
relationship | relationship_id | IN BOTH
relationship | relationship_name | IN BOTH
relationship | is_hierarchical | IN BOTH
relationship | defines_ancestry | IN BOTH
relationship | reverse_relationship_id | IN BOTH
source_to_concept_map | source_concept_id | IN BOTH
source_to_concept_map | target_concept_id | IN BOTH
source_to_concept_map | valid_start_date | IN BOTH
source_to_concept_map | valid_end_date | IN BOTH
source_to_concept_map | source_code | IN BOTH
source_to_concept_map | source_vocabulary_id | IN BOTH
source_to_concept_map | source_code_description | IN BOTH
source_to_concept_map | target_vocabulary_id | IN BOTH
source_to_concept_map | invalid_reason | IN BOTH
specimen | specimen_id | IN BOTH
specimen | person_id | IN BOTH
specimen | specimen_concept_id | IN BOTH
specimen | specimen_type_concept_id | IN BOTH
specimen | specimen_date | IN BOTH
specimen | specimen_datetime | IN BOTH
specimen | quantity | IN BOTH
specimen | unit_concept_id | IN BOTH
specimen | anatomic_site_concept_id | IN BOTH
specimen | disease_status_concept_id | IN BOTH
specimen | specimen_source_id | IN BOTH
specimen | specimen_source_value | IN BOTH
specimen | unit_source_value | IN BOTH
specimen | anatomic_site_source_value | IN BOTH
specimen | disease_status_source_value | IN BOTH
survey_conduct | survey_conduct_id | MISSING FROM v5.4.0
survey_conduct | person_id | MISSING FROM v5.4.0
survey_conduct | survey_concept_id | MISSING FROM v5.4.0
survey_conduct | survey_start_date | MISSING FROM v5.4.0
survey_conduct | survey_start_datetime | MISSING FROM v5.4.0
survey_conduct | survey_end_date | MISSING FROM v5.4.0
survey_conduct | survey_end_datetime | MISSING FROM v5.4.0
survey_conduct | provider_id | MISSING FROM v5.4.0
survey_conduct | assisted_concept_id | MISSING FROM v5.4.0
survey_conduct | respondent_type_concept_id | MISSING FROM v5.4.0
survey_conduct | timing_concept_id | MISSING FROM v5.4.0
survey_conduct | collection_method_concept_id | MISSING FROM v5.4.0
survey_conduct | assisted_source_value | MISSING FROM v5.4.0
survey_conduct | respondent_type_source_value | MISSING FROM v5.4.0
survey_conduct | timing_source_value | MISSING FROM v5.4.0
survey_conduct | collection_method_source_value | MISSING FROM v5.4.0
survey_conduct | survey_source_value | MISSING FROM v5.4.0
survey_conduct | survey_source_concept_id | MISSING FROM v5.4.0
survey_conduct | survey_source_identifier | MISSING FROM v5.4.0
survey_conduct | validated_survey_concept_id | MISSING FROM v5.4.0
survey_conduct | validated_survey_source_value | MISSING FROM v5.4.0
survey_conduct | survey_version_number | MISSING FROM v5.4.0
survey_conduct | visit_occurrence_id | MISSING FROM v5.4.0
survey_conduct | response_visit_occurrence_id | MISSING FROM v5.4.0
visit_detail | visit_detail_id | IN BOTH
visit_detail | person_id | IN BOTH
visit_detail | visit_detail_concept_id | IN BOTH
visit_detail | visit_detail_start_date | IN BOTH
visit_detail | visit_detail_start_datetime | IN BOTH
visit_detail | visit_detail_end_date | IN BOTH
visit_detail | visit_detail_end_datetime | IN BOTH
visit_detail | visit_detail_type_concept_id | IN BOTH
visit_detail | provider_id | IN BOTH
visit_detail | care_site_id | IN BOTH
visit_detail | preceding_visit_detail_id | IN BOTH
visit_detail | visit_detail_source_concept_id | IN BOTH
visit_detail | visit_occurrence_id | IN BOTH
visit_detail | visit_detail_source_value | IN BOTH
visit_detail | admitted_from_concept_id | IN BOTH
visit_detail | admitted_from_source_value | IN BOTH
visit_detail | discharge_to_source_value | MISSING FROM v5.4.0
visit_detail | discharge_to_concept_id | MISSING FROM v5.4.0
visit_detail | visit_detail_parent_id | MISSING FROM v5.4.0
visit_detail | discharged_to_concept_id | MISSING FROM v6.0.1
visit_detail | discharged_to_source_value | MISSING FROM v6.0.1
visit_detail | parent_visit_detail_id | MISSING FROM v6.0.1
visit_occurrence | visit_occurrence_id | IN BOTH
visit_occurrence | person_id | IN BOTH
visit_occurrence | visit_concept_id | IN BOTH
visit_occurrence | visit_start_date | IN BOTH
visit_occurrence | visit_start_datetime | IN BOTH
visit_occurrence | visit_end_date | IN BOTH
visit_occurrence | visit_end_datetime | IN BOTH
visit_occurrence | visit_type_concept_id | IN BOTH
visit_occurrence | provider_id | IN BOTH
visit_occurrence | care_site_id | IN BOTH
visit_occurrence | visit_source_concept_id | IN BOTH
visit_occurrence | preceding_visit_occurrence_id | IN BOTH
visit_occurrence | visit_source_value | IN BOTH
visit_occurrence | admitted_from_concept_id | IN BOTH
visit_occurrence | admitted_from_source_value | IN BOTH
visit_occurrence | discharge_to_concept_id | MISSING FROM v5.4.0
visit_occurrence | discharge_to_source_value | MISSING FROM v5.4.0
visit_occurrence | discharged_to_concept_id | MISSING FROM v6.0.1
visit_occurrence | discharged_to_source_value | MISSING FROM v6.0.1
vocabulary | vocabulary_id | IN BOTH
vocabulary | vocabulary_name | IN BOTH
vocabulary | vocabulary_reference | IN BOTH
vocabulary | vocabulary_version | IN BOTH
vocabulary | vocabulary_concept_id | IN BOTH

View File

@ -0,0 +1,134 @@
-- DEATH
CREATE TABLE DEATH ( person_id integer NOT NULL,
death_date date NOT NULL,
death_datetime TIMESTAMP NULL,
death_type_concept_id integer NULL,
cause_concept_id integer NULL,
cause_source_value varchar(50) NULL,
cause_source_concept_id integer NULL )
DISTKEY(person_id);
-- EPISODE
CREATE TABLE EPISODE (episode_id bigint NOT NULL,
person_id bigint NOT NULL,
episode_concept_id integer NOT NULL,
episode_start_date date NOT NULL,
episode_start_datetime TIMESTAMP NULL,
episode_end_date date NULL,
episode_end_datetime TIMESTAMP NULL,
episode_parent_id bigint NULL,
episode_number integer NULL,
episode_object_concept_id integer NOT NULL,
episode_type_concept_id integer NOT NULL,
episode_source_value varchar(50) NULL,
episode_source_concept_id integer NULL )
DISTKEY(person_id);
-- EPISODE_EVENT
CREATE TABLE EPISODE_EVENT (episode_id bigint NOT NULL,
event_id bigint NOT NULL,
episode_event_field_concept_id integer NOT NULL )
DISTSTYLE ALL;
-- PERSON
alter table person drop column death_datetime;
-- VISIT_OCCURRENCE
alter table visit_occurrence rename column discharge_to_concept_id to discharged_to_concept_id;
alter table visit_occurrence rename column discharge_to_source_value to discharged_to_source_value;
-- VISIT_DETAIL
alter table visit_detail rename column discharge_to_concept_id to discharged_to_concept_id;
alter table visit_detail rename column discharge_to_source_value to discharged_to_source_value;
alter table visit_detail rename column visit_detail_parent_id to parent_visit_detail_id;
-- PROCEDURE_OCCURRENCE
alter table procedure_occurrence add column procedure_end_date date;
alter table procedure_occurrence add column procedure_end_datetime timestamp;
-- DEVICE_EXPOSURE
alter table device_exposure add column production_id varchar(255);
alter table device_exposure add column unit_concept_id integer;
alter table device_exposure add column unit_source_value varchar(50);
alter table device_exposure add column unit_source_concept_id integer;
-- MEASUREMENT
alter table measurement add column unit_source_id integer;
alter table measurement add column measurement_event_id bigint;
alter table measurement add column meas_event_field_concept_id integer;
-- OBSERVATION
alter table observation add column value_source_value varchar(50);
alter table observation drop column value_as_datetime;
-- LOCATION
alter location add column country_concept_id integer;
alter location add column country_source_value varchar(80);
-- PAYER_PLAN_PERIOD
alter table payer_plan_period drop column contract_person_id;
alter table payer_plan_period drop column contract_concept_id;
alter table payer_plan_period drop column contract_source_value;
alter table payer_plan_period drop column contract_source_concept_id;
-- COST
alter table cost drop column person_id;
alter table cost drop column cost_event_field_concept_id;
alter table cost drop column cost_concept_id;
alter table cost drop column cost_source_concept_id;
alter table cost drop column cost_source_value;
alter table cost drop column cost;
alter table cost drop column incurred_date;
alter table cost drop column billed_date;
alter table cost drop column paid_date;
alter table cost drop column revenue_code_source_value;
alter cost add column total_charge float;
alter cost add column total_cost float;
alter cost add column total_paid float;
alter cost add column paid_by_payer float;
alter cost add column paid_by_patient float;
alter cost add column paid_by_primary float;
alter cost add column paid_patient_copay float;
alter cost add column paid_patient_coinsurance float;
alter cost add column paid_patient_deductible float;
alter cost add column paid_ingredient_cost float;
alter cost add column paid_dispensing_fee float;
alter cost add column amount_allowed float;
alter cost add column cost_domain_id varchar(20);
alter cost add column revenue_code_source_value varchar(50);
-- DRUG_ERA
alter table drug_era rename column drug_era_start_datetime to drug_era_start_date;
alter table drug_era rename column drug_era_end_datetime to drug_era_end_date;
alter table drug_era alter column drug_era_start_date date;
alter table drug_era alter column drug_era_end_date date;
-- DOSE_ERA
alter table dose_era rename column dose_era_start_datetime to dose_era_start_date;
alter table dose_era rename column dose_era_end_datetime to dose_era_end_date;
alter table dose_era alter column dose_era_start_date date;
alter table dose_era alter column dose_era_end_date date;
-- CONDITION_ERA
alter table condition_era rename column condition_era_start_datetime to condition_era_start_date;
alter table condition_era rename column condition_era_end_datetime to condition_era_end_date;
alter table condition_era alter column condition_era_start_date date;
alter table condition_era alter column condition_era_end_date date;
-- METADATA
alter table metadata add column metadata_id integer;
alter table metadata add column value_as_number float;
-- CDM_SOURCE
alter table cdm_source add column cdm_version_concept_id integer;

View File

@ -12,7 +12,7 @@ person,provider_id,No,integer,The Provider refers to the last known primary care
person,care_site_id,No,integer,The Care Site refers to where the Provider typically provides the primary care.,NA,No,Yes,CARE_SITE,CARE_SITE_ID,NA,NA,NA
person,person_source_value,No,varchar(50),Use this field to link back to persons in the source data. This is typically used for error checking of ETL logic.,Some use cases require the ability to link back to persons in the source data. This field allows for the storing of the person value as it appears in the source. This field is not required but strongly recommended.,No,No,NA,NA,NA,NA,NA
person,gender_source_value,No,varchar(50),This field is used to store the biological sex of the person from the source data. It is not intended for use in standard analytics but for reference only.,Put the assigned sex at birth of the person as it appears in the source data.,No,No,NA,NA,NA,NA,NA
person,gender_source_concept_id,No,integer,"Due to the small number of options, this tends to be zero.","If the source data codes asigned sex at birth in a non-standard vocabulary, store the concept_id here.",No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
person,gender_source_concept_id,No,integer,"Due to the small number of options, this tends to be zero.","If the source data codes assigned sex at birth in a non-standard vocabulary, store the concept_id here.",No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
person,race_source_value,No,varchar(50),This field is used to store the race of the person from the source data. It is not intended for use in standard analytics but for reference only.,Put the race of the person as it appears in the source data.,No,No,NA,NA,NA,NA,NA
person,race_source_concept_id,No,integer,"Due to the small number of options, this tends to be zero.",If the source data codes race in an OMOP supported vocabulary store the concept_id here.,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
person,ethnicity_source_value,No,varchar(50),This field is used to store the ethnicity of the person from the source data. It is not intended for use in standard analytics but for reference only.,"If the person has an ethnicity other than the OMB standard of ""Hispanic"" or ""Not Hispanic"" store that value from the source data here.",No,No,NA,NA,NA,NA,NA
@ -27,12 +27,12 @@ visit_occurrence,person_id,Yes,integer,NA,NA,No,Yes,PERSON,PERSON_ID,NA,NA,NA
visit_occurrence,visit_concept_id,Yes,integer,"This field contains a concept id representing the kind of visit, like inpatient or outpatient. All concepts in this field should be standard and belong to the Visit domain.","Populate this field based on the kind of visit that took place for the person. For example this could be ""Inpatient Visit"", ""Outpatient Visit"", ""Ambulatory Visit"", etc. This table will contain standard concepts in the Visit domain. These concepts are arranged in a hierarchical structure to facilitate cohort definitions by rolling up to generally familiar Visits adopted in most healthcare systems worldwide. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Visit&standardConcept=Standard&page=1&pageSize=15&query=).",No,Yes,CONCEPT,CONCEPT_ID,Visit,NA,NA
visit_occurrence,visit_start_date,Yes,date,"For inpatient visits, the start date is typically the admission date. For outpatient visits the start date and end date will be the same.","When populating VISIT_START_DATE, you should think about the patient experience to make decisions on how to define visits. In the case of an inpatient visit this should be the date the patient was admitted to the hospital or institution. In all other cases this should be the date of the patient-provider interaction. If this information is not available the record should be dropped.",No,No,NA,NA,NA,NA,NA
visit_occurrence,visit_start_datetime,No,datetime,NA,"If no time is given for the start date of a visit, set it to midnight (00:00:0000).",No,No,NA,NA,NA,NA,NA
visit_occurrence,visit_end_date,Yes,date,For inpatient visits the end date is typically the discharge date.,"Visit end dates are mandatory. If end dates are not provided in the source there are three ways in which to derive them:
- Outpatient Visit: visit_end_datetime = visit_start_datetime
- Emergency Room Visit: visit_end_datetime = visit_start_datetime
- Inpatient Visit: Usually there is information about discharge. If not, you should be able to derive the end date from the sudden decline of activity or from the absence of inpatient procedures/drugs.
- Non-hospital institution Visits: Particularly for claims data, if end dates are not provided assume the visit is for the duration of month that it occurs.
For Inpatient Visits ongoing at the date of ETL, put date of processing the data into visit_end_datetime and visit_type_concept_id with 32220 ""Still patient"" to identify the visit as incomplete.
visit_occurrence,visit_end_date,Yes,date,For inpatient visits the end date is typically the discharge date.,"Visit end dates are mandatory. If end dates are not provided in the source there are three ways in which to derive them:
- Outpatient Visit: visit_end_datetime = visit_start_datetime
- Emergency Room Visit: visit_end_datetime = visit_start_datetime
- Inpatient Visit: Usually there is information about discharge. If not, you should be able to derive the end date from the sudden decline of activity or from the absence of inpatient procedures/drugs.
- Non-hospital institution Visits: Particularly for claims data, if end dates are not provided assume the visit is for the duration of month that it occurs.
For Inpatient Visits ongoing at the date of ETL, put date of processing the data into visit_end_datetime and visit_type_concept_id with 32220 ""Still patient"" to identify the visit as incomplete.
- All other Visits: visit_end_datetime = visit_start_datetime. If this is a one-day visit the end date should match the start date.",No,No,NA,NA,NA,NA,NA
visit_occurrence,visit_end_datetime,No,datetime,NA,"If no time is given for the end date of a visit, set it to midnight (00:00:0000).",No,No,NA,NA,NA,NA,NA
visit_occurrence,visit_type_concept_id,Yes,Integer,"Use this field to understand the provenance of the visit record, or where the record comes from.","Populate this field based on the provenance of the visit record, as in whether it came from an EHR record or billing claim. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Type+Concept&standardConcept=Standard&page=1&pageSize=15&query=). A more detailed explanation of each Type Concept can be found on the [vocabulary wiki](https://github.com/OHDSI/Vocabulary-v5.0/wiki/Vocab.-TYPE_CONCEPT).",No,Yes,CONCEPT,CONCEPT_ID,Type Concept,NA,NA
@ -50,12 +50,12 @@ visit_detail,person_id,Yes,integer,NA,NA,No,Yes,PERSON,PERSON_ID,NA,NA,NA
visit_detail,visit_detail_concept_id,Yes,integer,"This field contains a concept id representing the kind of visit detail, like inpatient or outpatient. All concepts in this field should be standard and belong to the Visit domain.","Populate this field based on the kind of visit that took place for the person. For example this could be ""Inpatient Visit"", ""Outpatient Visit"", ""Ambulatory Visit"", etc. This table will contain standard concepts in the Visit domain. These concepts are arranged in a hierarchical structure to facilitate cohort definitions by rolling up to generally familiar Visits adopted in most healthcare systems worldwide. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Visit&standardConcept=Standard&page=1&pageSize=15&query=).",No,Yes,CONCEPT,CONCEPT_ID,Visit,NA,NA
visit_detail,visit_detail_start_date,Yes,date,This is the date of the start of the encounter. This may or may not be equal to the date of the Visit the Visit Detail is associated with.,"When populating VISIT_DETAIL_START_DATE, you should think about the patient experience to make decisions on how to define visits. Most likely this should be the date of the patient-provider interaction.",No,No,NA,NA,NA,NA,NA
visit_detail,visit_detail_start_datetime,No,datetime,NA,"If no time is given for the start date of a visit, set it to midnight (00:00:0000).",No,No,NA,NA,NA,NA,NA
visit_detail,visit_detail_end_date,Yes,date,This the end date of the patient-provider interaction.,"Visit Detail end dates are mandatory. If end dates are not provided in the source there are three ways in which to derive them:<br>
- Outpatient Visit Detail: visit_detail_end_datetime = visit_detail_start_datetime
- Emergency Room Visit Detail: visit_detail_end_datetime = visit_detail_start_datetime
- Inpatient Visit Detail: Usually there is information about discharge. If not, you should be able to derive the end date from the sudden decline of activity or from the absence of inpatient procedures/drugs.
- Non-hospital institution Visit Details: Particularly for claims data, if end dates are not provided assume the visit is for the duration of month that it occurs.<br>
For Inpatient Visit Details ongoing at the date of ETL, put date of processing the data into visit_detai_end_datetime and visit_detail_type_concept_id with 32220 ""Still patient"" to identify the visit as incomplete.
visit_detail,visit_detail_end_date,Yes,date,This the end date of the patient-provider interaction.,"Visit Detail end dates are mandatory. If end dates are not provided in the source there are three ways in which to derive them:<br>
- Outpatient Visit Detail: visit_detail_end_datetime = visit_detail_start_datetime
- Emergency Room Visit Detail: visit_detail_end_datetime = visit_detail_start_datetime
- Inpatient Visit Detail: Usually there is information about discharge. If not, you should be able to derive the end date from the sudden decline of activity or from the absence of inpatient procedures/drugs.
- Non-hospital institution Visit Details: Particularly for claims data, if end dates are not provided assume the visit is for the duration of month that it occurs.<br>
For Inpatient Visit Details ongoing at the date of ETL, put date of processing the data into visit_detai_end_datetime and visit_detail_type_concept_id with 32220 ""Still patient"" to identify the visit as incomplete.
All other Visits Details: visit_detail_end_datetime = visit_detail_start_datetime.",No,No,NA,NA,NA,NA,NA
visit_detail,visit_detail_end_datetime,No,datetime,NA,"If no time is given for the end date of a visit, set it to midnight (00:00:0000).",No,No,NA,NA,NA,NA,NA
visit_detail,visit_detail_type_concept_id,Yes,integer,"Use this field to understand the provenance of the visit detail record, or where the record comes from.","Populate this field based on the provenance of the visit detail record, as in whether it came from an EHR record or billing claim. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Type+Concept&standardConcept=Standard&page=1&pageSize=15&query=). A more detailed explanation of each Type Concept can be found on the [vocabulary wiki](https://github.com/OHDSI/Vocabulary-v5.0/wiki/Vocab.-TYPE_CONCEPT).",No,Yes,CONCEPT,CONCEPT_ID,Type Concept,NA,NA
@ -88,17 +88,17 @@ condition_occurrence,condition_source_concept_id,No,integer,"This is the concept
condition_occurrence,condition_status_source_value,No,varchar(50),This field houses the verbatim value from the source data representing the condition status.,This information may be called something different in the source data but the field is meant to contain a value indicating when and how a diagnosis was given to a patient. This source value is mapped to a standard concept which is stored in the CONDITION_STATUS_CONCEPT_ID field.,No,No,NA,NA,NA,NA,NA
drug_exposure,drug_exposure_id,Yes,integer,The unique key given to records of drug dispensings or administrations for a person. Refer to the ETL for how duplicate drugs during the same visit were handled.,"Each instance of a drug dispensing or administration present in the source data should be assigned this unique key. In some cases, a person can have multiple records of the same drug within the same visit. It is valid to keep these duplicates and assign them individual, unique, DRUG_EXPOSURE_IDs, though it is up to the ETL how they should be handled.",Yes,No,NA,NA,NA,NA,NA
drug_exposure,person_id,Yes,integer,The PERSON_ID of the PERSON for whom the drug dispensing or administration is recorded. This may be a system generated code.,NA,No,Yes,PERSON,PERSON_ID,NA,NA,NA
drug_exposure,drug_concept_id,Yes,integer,"The DRUG_CONCEPT_ID field is recommended for primary use in analyses, and must be used for network studies. This is the standard concept mapped from the source concept id which represents a drug product or molecule otherwise introduced to the body. The drug concepts can have a varying degree of information about drug strength and dose. This information is relevant in the context of quantity and administration information in the subsequent fields plus strength information from the DRUG_STRENGTH table, provided as part of the standard vocabulary download.","The CONCEPT_ID that the DRUG_SOURCE_VALUE maps to. The concept id should be derived either from mapping from the source concept id or by picking the drug concept representing the most amount of detail you have. Records whose source values map to standard concepts with a domain of Drug should go in this table. When the Drug Source Value of the code cannot be translated into Standard Drug Concept IDs, a Drug exposure entry is stored with only the corresponding SOURCE_CONCEPT_ID and DRUG_SOURCE_VALUE and a DRUG_CONCEPT_ID of 0. The Drug Concept with the most detailed content of information is preferred during the mapping process. These are indicated in the CONCEPT_CLASS_ID field of the Concept and are recorded in the following order of precedence: ÒMarketed ProductÓ, ÒBranded PackÓ, ÒClinical PackÓ, ÒBranded DrugÓ, ÒClinical DrugÓ, ÒBranded Drug ComponentÓ, ÒClinical Drug ComponentÓ, ÒBranded Drug FormÓ, ÒClinical Drug FormÓ, and only if no other information is available ÒIngredientÓ. Note: If only the drug class is known, the DRUG_CONCEPT_ID field should contain 0. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Drug&standardConcept=Standard&page=1&pageSize=15&query=).",No,Yes,CONCEPT,CONCEPT_ID,Drug,NA,NA
drug_exposure,drug_concept_id,Yes,integer,"The DRUG_CONCEPT_ID field is recommended for primary use in analyses, and must be used for network studies. This is the standard concept mapped from the source concept id which represents a drug product or molecule otherwise introduced to the body. The drug concepts can have a varying degree of information about drug strength and dose. This information is relevant in the context of quantity and administration information in the subsequent fields plus strength information from the DRUG_STRENGTH table, provided as part of the standard vocabulary download.","The CONCEPT_ID that the DRUG_SOURCE_VALUE maps to. The concept id should be derived either from mapping from the source concept id or by picking the drug concept representing the most amount of detail you have. Records whose source values map to standard concepts with a domain of Drug should go in this table. When the Drug Source Value of the code cannot be translated into Standard Drug Concept IDs, a Drug exposure entry is stored with only the corresponding SOURCE_CONCEPT_ID and DRUG_SOURCE_VALUE and a DRUG_CONCEPT_ID of 0. The Drug Concept with the most detailed content of information is preferred during the mapping process. These are indicated in the CONCEPT_CLASS_ID field of the Concept and are recorded in the following order of precedence: <EFBFBD>Marketed Product<63>, <20>Branded Pack<63>, <20>Clinical Pack<63>, <20>Branded Drug<75>, <20>Clinical Drug<75>, <20>Branded Drug Component<6E>, <20>Clinical Drug Component<6E>, <20>Branded Drug Form<72>, <20>Clinical Drug Form<72>, and only if no other information is available <20>Ingredient<6E>. Note: If only the drug class is known, the DRUG_CONCEPT_ID field should contain 0. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Drug&standardConcept=Standard&page=1&pageSize=15&query=).",No,Yes,CONCEPT,CONCEPT_ID,Drug,NA,NA
drug_exposure,drug_exposure_start_date,Yes,date,Use this date to determine the start date of the drug record.,"Valid entries include a start date of a prescription, the date a prescription was filled, or the date on which a Drug administration was recorded. It is a valid ETL choice to use the date the drug was ordered as the DRUG_EXPOSURE_START_DATE.",No,No,NA,NA,NA,NA,NA
drug_exposure,drug_exposure_start_datetime,No,datetime,NA,"This is not required, though it is in v6. If a source does not specify datetime the convention is to set the time to midnight (00:00:0000)",No,No,NA,NA,NA,NA,NA
drug_exposure,drug_exposure_end_date,Yes,date,The DRUG_EXPOSURE_END_DATE denotes the day the drug exposure ended for the patient.,"If this information is not explicitly available in the data, infer the end date using the following methods:<br><br> 1. Start first with duration or days supply using the calculation drug start date + days supply -1 day. 2. Use quantity divided by daily dose that you may obtain from the sig or a source field (or assumed daily dose of 1) for solid, indivisibile, drug products. If quantity represents ingredient amount, quantity divided by daily dose * concentration (from drug_strength) drug concept id tells you the dose form. 3. If it is an administration record, set drug end date equal to drug start date. If the record is a written prescription then set end date to start date + 29. If the record is a mail-order prescription set end date to start date + 89. The end date must be equal to or greater than the start date. Ibuprofen 20mg/mL oral solution concept tells us this is oral solution. Calculate duration as quantity (200 example) * daily dose (5mL) /concentration (20mg/mL) 200*5/20 = 50 days. [Examples by dose form](https://ohdsi.github.io/CommonDataModel/drug_dose.html)<br><br>For detailed conventions for how to populate this field, please see the [THEMIS repository](https://ohdsi.github.io/Themis/tag_drug_exposure.html).",No,No,NA,NA,NA,NA,NA
drug_exposure,drug_exposure_end_date,Yes,date,The DRUG_EXPOSURE_END_DATE denotes the day the drug exposure ended for the patient.,"If this information is not explicitly available in the data, infer the end date from start date and duration.<br>For detailed conventions for how to populate this field, please see the [THEMIS repository](https://ohdsi.github.io/Themis/tag_drug_exposure.html).",No,No,NA,NA,NA,NA,NA
drug_exposure,drug_exposure_end_datetime,No,datetime,NA,"This is not required, though it is in v6. If a source does not specify datetime the convention is to set the time to midnight (00:00:0000)",No,No,NA,NA,NA,NA,NA
drug_exposure,verbatim_end_date,No,date,"This is the end date of the drug exposure as it appears in the source data, if it is given",Put the end date or discontinuation date as it appears from the source data or leave blank if unavailable.,No,No,NA,NA,NA,NA,NA
drug_exposure,drug_type_concept_id,Yes,integer,"You can use the TYPE_CONCEPT_ID to delineate between prescriptions written vs. prescriptions dispensed vs. medication history vs. patient-reported exposure, etc.","Choose the drug_type_concept_id that best represents the provenance of the record, for example whether it came from a record of a prescription written or physician administered drug. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Type+Concept&standardConcept=Standard&page=1&pageSize=15&query=). A more detailed explanation of each Type Concept can be found on the [vocabulary wiki](https://github.com/OHDSI/Vocabulary-v5.0/wiki/Vocab.-TYPE_CONCEPT).",No,Yes,CONCEPT,CONCEPT_ID,Type Concept,NA,NA
drug_exposure,stop_reason,No,varchar(20),"The reason a person stopped a medication as it is represented in the source. Reasons include regimen completed, changed, removed, etc. This field will be retired in v6.0.",This information is often not populated in source data and it is a valid etl choice to leave it blank if the information does not exist.,No,No,NA,NA,NA,NA,NA
drug_exposure,refills,No,integer,This is only filled in when the record is coming from a prescription written this field is meant to represent intended refills at time of the prescription.,NA,No,No,NA,NA,NA,NA,NA
drug_exposure,quantity,No,float,NA,"To find the dose form of a drug the RELATIONSHIP table can be used where the relationship_id is 'Has dose form'. If liquid, quantity stands for the total amount dispensed or ordered of ingredient in the units given by the drug_strength table. If the unit from the source data does not align with the unit in the DRUG_STRENGTH table the quantity should be converted to the correct unit given in DRUG_STRENGTH. For clinical drugs with fixed dose forms (tablets etc.) the quantity is the number of units/tablets/capsules prescribed or dispensed (can be partial, but then only 1/2 or 1/3, not 0.01). Clinical drugs with divisible dose forms (injections) the quantity is the amount of ingredient the patient got. For example, if the injection is 2mg/mL but the patient got 80mL then quantity is reported as 160.
Quantified clinical drugs with divisible dose forms (prefilled syringes), the quantity is the amount of ingredient similar to clinical drugs. Please see [how to calculate drug dose](https://ohdsi.github.io/CommonDataModel/drug_dose.html) for more information.
drug_exposure,quantity,No,float,NA,"To find the dose form of a drug the RELATIONSHIP table can be used where the relationship_id is 'Has dose form'. If liquid, quantity stands for the total amount dispensed or ordered of ingredient in the units given by the drug_strength table. If the unit from the source data does not align with the unit in the DRUG_STRENGTH table the quantity should be converted to the correct unit given in DRUG_STRENGTH. For clinical drugs with fixed dose forms (tablets etc.) the quantity is the number of units/tablets/capsules prescribed or dispensed (can be partial, but then only 1/2 or 1/3, not 0.01). Clinical drugs with divisible dose forms (injections) the quantity is the amount of ingredient the patient got. For example, if the injection is 2mg/mL but the patient got 80mL then quantity is reported as 160.
Quantified clinical drugs with divisible dose forms (prefilled syringes), the quantity is the amount of ingredient similar to clinical drugs. Please see [how to calculate drug dose](https://ohdsi.github.io/CommonDataModel/drug_dose.html) for more information.
",No,No,NA,NA,NA,NA,NA
drug_exposure,days_supply,No,integer,The number of days of supply of the medication as recorded in the original prescription or dispensing record. Days supply can differ from actual drug duration (i.e. prescribed days supply vs actual exposure).,"The field should be left empty if the source data does not contain a verbatim days_supply, and should not be calculated from other fields.<br><br>Negative values are not allowed. If the source has negative days supply the record should be dropped as it is unknown if the patient actually took the drug. Several actions are possible: 1) record is not trustworthy and we remove the record entirely. 2) we trust the record and leave days_supply empty or 3) record needs to be combined with other record (e.g. reversal of prescription). High values (>365 days) should be investigated. If considered an error in the source data (e.g. typo), the value needs to be excluded to prevent creation of unrealistic long eras.",No,No,NA,NA,NA,NA,NA
drug_exposure,sig,No,varchar(MAX),This is the verbatim instruction for the drug as written by the provider.,"Put the written out instructions for the drug as it is verbatim in the source, if available.",No,No,NA,NA,NA,NA,NA
@ -142,7 +142,7 @@ device_exposure,device_source_value,No,varchar(50),"This field houses the verbat
device_exposure,device_source_concept_id,No,integer,"This is the concept representing the device source value and may not necessarily be standard. This field is discouraged from use in analysis because it is not required to contain Standard Concepts that are used across the OHDSI community, and should only be used when Standard Concepts do not adequately represent the source detail for the Device necessary for a given analytic use case. Consider using DEVICE_CONCEPT_ID instead to enable standardized analytics that can be consistent across the network.",If the DEVICE_SOURCE_VALUE is coded in the source data using an OMOP supported vocabulary put the concept id representing the source value here.,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
measurement,measurement_id,Yes,integer,The unique key given to a Measurement record for a Person. Refer to the ETL for how duplicate Measurements during the same Visit were handled.,"Each instance of a measurement present in the source data should be assigned this unique key. In some cases, a person can have multiple records of the same measurement within the same visit. It is valid to keep these duplicates and assign them individual, unique, MEASUREMENT_IDs, though it is up to the ETL how they should be handled.",Yes,No,NA,NA,NA,NA,NA
measurement,person_id,Yes,integer,The PERSON_ID of the Person for whom the Measurement is recorded. This may be a system generated code.,NA,No,Yes,PERSON,PERSON_ID,NA,NA,NA
measurement,measurement_concept_id,Yes,integer,"The MEASUREMENT_CONCEPT_ID field is recommended for primary use in analyses, and must be used for network studies. This is the standard concept mapped from the source value which represents a measurement.",The CONCEPT_ID that the MEASUREMENT_SOURCE_VALUE maps to. Only records whose source values map to concepts with a domain of ÒMeasurementÓ should go in this table.,No,Yes,CONCEPT,CONCEPT_ID,Measurement,NA,NA
measurement,measurement_concept_id,Yes,integer,"The MEASUREMENT_CONCEPT_ID field is recommended for primary use in analyses, and must be used for network studies. This is the standard concept mapped from the source value which represents a measurement.",The CONCEPT_ID that the MEASUREMENT_SOURCE_VALUE maps to. Only records whose source values map to concepts with a domain of <EFBFBD>Measurement<EFBFBD> should go in this table.,No,Yes,CONCEPT,CONCEPT_ID,Measurement,NA,NA
measurement,measurement_date,Yes,date,Use this date to determine the date of the measurement.,"If there are multiple dates in the source data associated with a record such as order_date, draw_date, and result_date, choose the one that is closest to the date the sample was drawn from the patient.",No,No,NA,NA,NA,NA,NA
measurement,measurement_datetime,No,datetime,NA,"This is not required, though it is in v6. If a source does not specify datetime the convention is to set the time to midnight (00:00:0000)",No,No,NA,NA,NA,NA,NA
measurement,measurement_time,No,varchar(10),NA,This is present for backwards compatibility and will be deprecated in an upcoming version.,No,No,NA,NA,NA,NA,NA
@ -190,7 +190,7 @@ note,person_id,Yes,integer,NA,NA,No,Yes,PERSON,PERSON_ID,NA,NA,NA
note,note_date,Yes,date,The date the note was recorded.,NA,No,No,NA,NA,NA,NA,NA
note,note_datetime,No,datetime,NA,If time is not given set the time to midnight.,No,No,NA,NA,NA,NA,NA
note,note_type_concept_id,Yes,integer,The provenance of the note. Most likely this will be EHR.,"Put the source system of the note, as in EHR record. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?standardConcept=Standard&domain=Type+Concept&page=1&pageSize=15&query=). A more detailed explanation of each Type Concept can be found on the [vocabulary wiki](https://github.com/OHDSI/Vocabulary-v5.0/wiki/Vocab.-TYPE_CONCEPT).",No,Yes,CONCEPT,CONCEPT_ID,Type Concept,NA,NA
note,note_class_concept_id,Yes,integer,"A Standard Concept Id representing the HL7 LOINC
note,note_class_concept_id,Yes,integer,"A Standard Concept Id representing the HL7 LOINC
Document Type Vocabulary classification of the note.",Map the note classification to a Standard Concept. For more information see the ETL Conventions in the description of the NOTE table. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?standardConcept=Standard&conceptClass=Doc+Kind&conceptClass=Doc+Role&conceptClass=Doc+Setting&conceptClass=Doc+Subject+Matter&conceptClass=Doc+Type+of+Service&domain=Meas+Value&page=1&pageSize=15&query=). This Concept can alternatively be represented by concepts with the relationship 'Kind of (LOINC)' to [706391](https://athena.ohdsi.org/search-terms/terms/706391) (Note).,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
note,note_title,No,varchar(250),The title of the note.,NA,No,No,NA,NA,NA,NA,NA
note,note_text,Yes,varchar(MAX),The content of the note.,NA,No,No,NA,NA,NA,NA,NA
@ -211,22 +211,22 @@ note_nlp,note_nlp_source_concept_id,No,integer,NA,NA,No,Yes,CONCEPT,CONCEPT_ID,N
note_nlp,nlp_system,No,varchar(250),NA,Name and version of the NLP system that extracted the term. Useful for data provenance.,No,No,NA,NA,NA,NA,NA
note_nlp,nlp_date,Yes,date,The date of the note processing.,NA,No,No,NA,NA,NA,NA,NA
note_nlp,nlp_datetime,No,datetime,The date and time of the note processing.,NA,No,No,NA,NA,NA,NA,NA
note_nlp,term_exists,No,varchar(1),NA,"Term_exists is defined as a flag that indicates if the patient actually has or had the condition. Any of the following modifiers would make Term_exists false:
Negation = true
Subject = [anything other than the patient]
Conditional = true/li>
Rule_out = true
Uncertain = very low certainty or any lower certainties
A complete lack of modifiers would make Term_exists true.
note_nlp,term_exists,No,varchar(1),NA,"Term_exists is defined as a flag that indicates if the patient actually has or had the condition. Any of the following modifiers would make Term_exists false:
Negation = true
Subject = [anything other than the patient]
Conditional = true/li>
Rule_out = true
Uncertain = very low certainty or any lower certainties
A complete lack of modifiers would make Term_exists true.
",No,No,NA,NA,NA,NA,NA
note_nlp,term_temporal,No,varchar(50),NA,"Term_temporal is to indicate if a condition is present or just in the past. The following would be past:<br><br>
- History = true
note_nlp,term_temporal,No,varchar(50),NA,"Term_temporal is to indicate if a condition is present or just in the past. The following would be past:<br><br>
- History = true
- Concept_date = anything before the time of the report",No,No,NA,NA,NA,NA,NA
note_nlp,term_modifiers,No,varchar(2000),NA,"For the modifiers that are there, they would have to have these values:<br><br>
- Negation = false
- Subject = patient
- Conditional = false
- Rule_out = false
note_nlp,term_modifiers,No,varchar(2000),NA,"For the modifiers that are there, they would have to have these values:<br><br>
- Negation = false
- Subject = patient
- Conditional = false
- Rule_out = false
- Uncertain = true or high or moderate or even low (could argue about low). Term_modifiers will concatenate all modifiers for different types of entities (conditions, drugs, labs etc) into one string. Lab values will be saved as one of the modifiers.",No,No,NA,NA,NA,NA,NA
specimen,specimen_id,Yes,integer,Unique identifier for each specimen.,NA,Yes,No,NA,NA,NA,NA,NA
specimen,person_id,Yes,integer,The person from whom the specimen is collected.,NA,No,Yes,PERSON,PERSON_ID,NA,NA,NA
@ -318,9 +318,9 @@ drug_era,drug_era_id,Yes,integer,NA,NA,Yes,No,NA,NA,NA,NA,NA
drug_era,person_id,Yes,integer,NA,NA,No,Yes,PERSON,PERSON_ID,NA,NA,NA
drug_era,drug_concept_id,Yes,integer,The drug_concept_id should conform to the concept class 'ingredient' as the drug_era is an era of time where a person is exposed to a particular drug ingredient.,NA,No,Yes,CONCEPT,CONCEPT_ID,Drug,Ingredient,NA
drug_era,drug_era_start_date,Yes,date,NA,"The Drug Era Start Date is the start date of the first Drug Exposure for a given ingredient, with at least 31 days since the previous exposure.",No,No,NA,NA,NA,NA,NA
drug_era,drug_era_end_date,Yes,date,NA,"The Drug Era End Date is the end date of the last Drug Exposure. The End Date of each Drug Exposure is either taken from the field drug_exposure_end_date or, as it is typically not available, inferred using the following rules:
For pharmacy prescription data, the date when the drug was dispensed plus the number of days of supply are used to extrapolate the End Date for the Drug Exposure. Depending on the country-specific healthcare system, this supply information is either explicitly provided in the day_supply field or inferred from package size or similar information.
For Procedure Drugs, usually the drug is administered on a single date (i.e., the administration date).
drug_era,drug_era_end_date,Yes,date,NA,"The Drug Era End Date is the end date of the last Drug Exposure. The End Date of each Drug Exposure is either taken from the field drug_exposure_end_date or, as it is typically not available, inferred using the following rules:
For pharmacy prescription data, the date when the drug was dispensed plus the number of days of supply are used to extrapolate the End Date for the Drug Exposure. Depending on the country-specific healthcare system, this supply information is either explicitly provided in the day_supply field or inferred from package size or similar information.
For Procedure Drugs, usually the drug is administered on a single date (i.e., the administration date).
A standard Persistence Window of 30 days (gap, slack) is permitted between two subsequent such extrapolated DRUG_EXPOSURE records to be considered to be merged into a single Drug Era.",No,No,NA,NA,NA,NA,NA
drug_era,drug_exposure_count,No,integer,The count of grouped DRUG_EXPOSURE records that were included in the DRUG_ERA row,NA,No,No,NA,NA,NA,NA,NA
drug_era,gap_days,No,integer,NA,"The Gap Days determine how many total drug-free days are observed between all Drug Exposure events that contribute to a DRUG_ERA record. It is assumed that the drugs are ""not stockpiled"" by the patient, i.e. that if a new drug prescription or refill is observed (a new DRUG_EXPOSURE record is written), the remaining supply from the previous events is abandoned. The difference between Persistence Window and Gap Days is that the former is the maximum drug-free time allowed between two subsequent DRUG_EXPOSURE records, while the latter is the sum of actual drug-free days for the given Drug Era under the above assumption of non-stockpiling.",No,No,NA,NA,NA,NA,NA
@ -334,20 +334,20 @@ dose_era,dose_era_end_date,Yes,date,NA,The date the Person was no longer exposed
condition_era,condition_era_id,Yes,integer,NA,NA,Yes,No,NA,NA,NA,NA,NA
condition_era,person_id,Yes,integer,NA,NA,No,No,PERSON,PERSON_ID,NA,NA,NA
condition_era,condition_concept_id,Yes,integer,The Concept Id representing the Condition.,NA,No,Yes,CONCEPT,CONCEPT_ID,Condition,NA,NA
condition_era,condition_era_start_date,Yes,date,"The start date for the Condition Era
constructed from the individual
instances of Condition Occurrences.
It is the start date of the very first
chronologically recorded instance of
condition_era,condition_era_start_date,Yes,date,"The start date for the Condition Era
constructed from the individual
instances of Condition Occurrences.
It is the start date of the very first
chronologically recorded instance of
the condition with at least 31 days since any prior record of the same Condition.",NA,No,No,NA,NA,NA,NA,NA
condition_era,condition_era_end_date,Yes,date,"The end date for the Condition Era
constructed from the individual
instances of Condition Occurrences.
It is the end date of the final
continuously recorded instance of the
condition_era,condition_era_end_date,Yes,date,"The end date for the Condition Era
constructed from the individual
instances of Condition Occurrences.
It is the end date of the final
continuously recorded instance of the
Condition.",NA,No,No,NA,NA,NA,NA,NA
condition_era,condition_occurrence_count,No,integer,"The number of individual Condition
Occurrences used to construct the
condition_era,condition_occurrence_count,No,integer,"The number of individual Condition
Occurrences used to construct the
condition era.",NA,No,No,NA,NA,NA,NA,NA
metadata,metadata_concept_id,Yes,integer,NA,NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
metadata,metadata_type_concept_id,Yes,integer,NA,NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
@ -369,57 +369,57 @@ cdm_source,vocabulary_version,No,varchar(20),NA,NA,No,No,NA,NA,NA,NA,NA
concept,concept_id,Yes,integer,A unique identifier for each Concept across all domains.,NA,Yes,No,NA,NA,NA,NA,NA
concept,concept_name,Yes,varchar(255),"An unambiguous, meaningful and descriptive name for the Concept.",NA,No,No,NA,NA,NA,NA,NA
concept,domain_id,Yes,varchar(20),A foreign key to the [DOMAIN](https://ohdsi.github.io/CommonDataModel/cdm531.html#domain) table the Concept belongs to.,NA,No,Yes,DOMAIN,DOMAIN_ID,NA,NA,NA
concept,vocabulary_id,Yes,varchar(20),"A foreign key to the [VOCABULARY](https://ohdsi.github.io/CommonDataModel/cdm531.html#vocabulary)
table indicating from which source the
concept,vocabulary_id,Yes,varchar(20),"A foreign key to the [VOCABULARY](https://ohdsi.github.io/CommonDataModel/cdm531.html#vocabulary)
table indicating from which source the
Concept has been adapted.",NA,No,Yes,VOCABULARY,VOCABULARY_ID,NA,NA,NA
concept,concept_class_id,Yes,varchar(20),"The attribute or concept class of the
Concept. Examples are 'Clinical Drug',
concept,concept_class_id,Yes,varchar(20),"The attribute or concept class of the
Concept. Examples are 'Clinical Drug',
'Ingredient', 'Clinical Finding' etc.",NA,No,Yes,CONCEPT_CLASS,CONCEPT_CLASS_ID,NA,NA,NA
concept,standard_concept,No,varchar(1),"This flag determines where a Concept is
a Standard Concept, i.e. is used in the
data, a Classification Concept, or a
non-standard Source Concept. The
allowable values are 'S' (Standard
Concept) and 'C' (Classification
concept,standard_concept,No,varchar(1),"This flag determines where a Concept is
a Standard Concept, i.e. is used in the
data, a Classification Concept, or a
non-standard Source Concept. The
allowable values are 'S' (Standard
Concept) and 'C' (Classification
Concept), otherwise the content is NULL.",NA,No,No,NA,NA,NA,NA,NA
concept,concept_code,Yes,varchar(50),"The concept code represents the identifier
of the Concept in the source vocabulary,
such as SNOMED-CT concept IDs,
RxNorm RXCUIs etc. Note that concept
concept,concept_code,Yes,varchar(50),"The concept code represents the identifier
of the Concept in the source vocabulary,
such as SNOMED-CT concept IDs,
RxNorm RXCUIs etc. Note that concept
codes are not unique across vocabularies.",NA,No,No,NA,NA,NA,NA,NA
concept,valid_start_date,Yes,date,"The date when the Concept was first
recorded. The default value is
1-Jan-1970, meaning, the Concept has no
concept,valid_start_date,Yes,date,"The date when the Concept was first
recorded. The default value is
1-Jan-1970, meaning, the Concept has no
(known) date of inception.",NA,No,No,NA,NA,NA,NA,NA
concept,valid_end_date,Yes,date,"The date when the Concept became
invalid because it was deleted or
superseded (updated) by a new concept.
The default value is 31-Dec-2099,
meaning, the Concept is valid until it
concept,valid_end_date,Yes,date,"The date when the Concept became
invalid because it was deleted or
superseded (updated) by a new concept.
The default value is 31-Dec-2099,
meaning, the Concept is valid until it
becomes deprecated.",NA,No,No,NA,NA,NA,NA,NA
concept,invalid_reason,No,varchar(1),"Reason the Concept was invalidated.
Possible values are D (deleted), U
(replaced with an update) or NULL when
concept,invalid_reason,No,varchar(1),"Reason the Concept was invalidated.
Possible values are D (deleted), U
(replaced with an update) or NULL when
valid_end_date has the default value.",NA,No,No,NA,NA,NA,NA,NA
vocabulary,vocabulary_id,Yes,varchar(20),"A unique identifier for each Vocabulary, such
vocabulary,vocabulary_id,Yes,varchar(20),"A unique identifier for each Vocabulary, such
as ICD9CM, SNOMED, Visit.",NA,Yes,No,NA,NA,NA,NA,NA
vocabulary,vocabulary_name,Yes,varchar(255),"The name describing the vocabulary, for
example, International Classification of
Diseases, Ninth Revision, Clinical
vocabulary,vocabulary_name,Yes,varchar(255),"The name describing the vocabulary, for
example, International Classification of
Diseases, Ninth Revision, Clinical
Modification, Volume 1 and 2 (NCHS) etc.",NA,No,No,NA,NA,NA,NA,NA
vocabulary,vocabulary_reference,Yes,varchar(255),"External reference to documentation or
available download of the about the
vocabulary,vocabulary_reference,Yes,varchar(255),"External reference to documentation or
available download of the about the
vocabulary.",NA,No,No,NA,NA,NA,NA,NA
vocabulary,vocabulary_version,No,varchar(255),"Version of the Vocabulary as indicated in
vocabulary,vocabulary_version,No,varchar(255),"Version of the Vocabulary as indicated in
the source.",NA,No,No,NA,NA,NA,NA,NA
vocabulary,vocabulary_concept_id,Yes,integer,A Concept that represents the Vocabulary the VOCABULARY record belongs to.,NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
domain,domain_id,Yes,varchar(20),A unique key for each domain.,NA,Yes,No,NA,NA,NA,NA,NA
domain,domain_name,Yes,varchar(255),"The name describing the Domain, e.g.
Condition, Procedure, Measurement
domain,domain_name,Yes,varchar(255),"The name describing the Domain, e.g.
Condition, Procedure, Measurement
etc.",NA,No,No,NA,NA,NA,NA,NA
domain,domain_concept_id,Yes,integer,A Concept representing the Domain Concept the DOMAIN record belongs to.,NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
concept_class,concept_class_id,Yes,varchar(20),A unique key for each class.,NA,Yes,No,NA,NA,NA,NA,NA
concept_class,concept_class_name,Yes,varchar(255),"The name describing the Concept Class, e.g.
concept_class,concept_class_name,Yes,varchar(255),"The name describing the Concept Class, e.g.
Clinical Finding, Ingredient, etc.",NA,No,No,NA,NA,NA,NA,NA
concept_class,concept_class_concept_id,Yes,integer,A Concept that represents the Concept Class.,NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
concept_relationship,concept_id_1,Yes,integer,NA,NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
@ -428,63 +428,63 @@ concept_relationship,relationship_id,Yes,varchar(20),The relationship between CO
concept_relationship,valid_start_date,Yes,date,The date when the relationship is first recorded.,NA,No,No,NA,NA,NA,NA,NA
concept_relationship,valid_end_date,Yes,date,The date when the relationship is invalidated.,NA,No,No,NA,NA,NA,NA,NA
concept_relationship,invalid_reason,No,varchar(1),"Reason the relationship was invalidated. Possible values are 'D' (deleted), 'U' (updated) or NULL.",NA,No,No,NA,NA,NA,NA,NA
relationship,relationship_id,Yes,varchar(20),"The type of relationship captured by the
relationship,relationship_id,Yes,varchar(20),"The type of relationship captured by the
relationship record.",NA,Yes,No,NA,NA,NA,NA,NA
relationship,relationship_name,Yes,varchar(255),NA,NA,No,No,NA,NA,NA,NA,NA
relationship,is_hierarchical,Yes,varchar(1),"Defines whether a relationship defines
concepts into classes or hierarchies. Values
relationship,is_hierarchical,Yes,varchar(1),"Defines whether a relationship defines
concepts into classes or hierarchies. Values
are 1 for hierarchical relationship or 0 if not.",NA,No,No,NA,NA,NA,NA,NA
relationship,defines_ancestry,Yes,varchar(1),"Defines whether a hierarchical relationship
contributes to the concept_ancestor table.
These are subsets of the hierarchical
relationship,defines_ancestry,Yes,varchar(1),"Defines whether a hierarchical relationship
contributes to the concept_ancestor table.
These are subsets of the hierarchical
relationships. Valid values are 1 or 0.",NA,No,No,NA,NA,NA,NA,NA
relationship,reverse_relationship_id,Yes,varchar(20),"The identifier for the relationship used to
define the reverse relationship between two
relationship,reverse_relationship_id,Yes,varchar(20),"The identifier for the relationship used to
define the reverse relationship between two
concepts.",NA,No,No,NA,NA,NA,NA,NA
relationship,relationship_concept_id,Yes,integer,"A foreign key that refers to an identifier in
the [CONCEPT](https://ohdsi.github.io/CommonDataModel/cdm531.html#concept) table for the unique
relationship,relationship_concept_id,Yes,integer,"A foreign key that refers to an identifier in
the [CONCEPT](https://ohdsi.github.io/CommonDataModel/cdm531.html#concept) table for the unique
relationship concept.",NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
concept_synonym,concept_id,Yes,integer,NA,NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
concept_synonym,concept_synonym_name,Yes,varchar(1000),NA,NA,No,No,NA,NA,NA,NA,NA
concept_synonym,language_concept_id,Yes,integer,NA,NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
concept_ancestor,ancestor_concept_id,Yes,integer,"The Concept Id for the higher-level concept
concept_ancestor,ancestor_concept_id,Yes,integer,"The Concept Id for the higher-level concept
that forms the ancestor in the relationship.",NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
concept_ancestor,descendant_concept_id,Yes,integer,"The Concept Id for the lower-level concept
that forms the descendant in the
concept_ancestor,descendant_concept_id,Yes,integer,"The Concept Id for the lower-level concept
that forms the descendant in the
relationship.",NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
concept_ancestor,min_levels_of_separation,Yes,integer,"The minimum separation in number of
levels of hierarchy between ancestor and
descendant concepts. This is an attribute
concept_ancestor,min_levels_of_separation,Yes,integer,"The minimum separation in number of
levels of hierarchy between ancestor and
descendant concepts. This is an attribute
that is used to simplify hierarchic analysis.",NA,No,No,NA,NA,NA,NA,NA
concept_ancestor,max_levels_of_separation,Yes,integer,"The maximum separation in number of
levels of hierarchy between ancestor and
descendant concepts. This is an attribute
concept_ancestor,max_levels_of_separation,Yes,integer,"The maximum separation in number of
levels of hierarchy between ancestor and
descendant concepts. This is an attribute
that is used to simplify hierarchic analysis.",NA,No,No,NA,NA,NA,NA,NA
source_to_concept_map,source_code,Yes,varchar(50),"The source code being translated
source_to_concept_map,source_code,Yes,varchar(50),"The source code being translated
into a Standard Concept.",NA,No,No,NA,NA,NA,NA,NA
source_to_concept_map,source_concept_id,Yes,integer,"A foreign key to the Source
Concept that is being translated
source_to_concept_map,source_concept_id,Yes,integer,"A foreign key to the Source
Concept that is being translated
into a Standard Concept.","This is either 0 or should be a number above 2 billion, which are the Concepts reserved for site-specific codes and mappings.",No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
source_to_concept_map,source_vocabulary_id,Yes,varchar(20),"A foreign key to the
VOCABULARY table defining the
vocabulary of the source code that
is being translated to a Standard
source_to_concept_map,source_vocabulary_id,Yes,varchar(20),"A foreign key to the
VOCABULARY table defining the
vocabulary of the source code that
is being translated to a Standard
Concept.",NA,No,No,NA,NA,NA,NA,NA
source_to_concept_map,source_code_description,No,varchar(255),"An optional description for the
source code. This is included as a
convenience to compare the
description of the source code to
source_to_concept_map,source_code_description,No,varchar(255),"An optional description for the
source code. This is included as a
convenience to compare the
description of the source code to
the name of the concept.",NA,No,No,NA,NA,NA,NA,NA
source_to_concept_map,target_concept_id,Yes,integer,"The target Concept
to which the source code is being
source_to_concept_map,target_concept_id,Yes,integer,"The target Concept
to which the source code is being
mapped.",NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
source_to_concept_map,target_vocabulary_id,Yes,varchar(20),The Vocabulary of the target Concept.,NA,No,Yes,VOCABULARY,VOCABULARY_ID,NA,NA,NA
source_to_concept_map,valid_start_date,Yes,date,"The date when the mapping
source_to_concept_map,valid_start_date,Yes,date,"The date when the mapping
instance was first recorded.",NA,No,No,NA,NA,NA,NA,NA
source_to_concept_map,valid_end_date,Yes,date,"The date when the mapping
instance became invalid because it
was deleted or superseded
(updated) by a new relationship.
source_to_concept_map,valid_end_date,Yes,date,"The date when the mapping
instance became invalid because it
was deleted or superseded
(updated) by a new relationship.
Default value is 31-Dec-2099.",NA,No,No,NA,NA,NA,NA,NA
source_to_concept_map,invalid_reason,No,varchar(1),"Reason the mapping instance was invalidated. Possible values are D (deleted), U (replaced with an update) or NULL when valid_end_date has the default value.",NA,No,No,NA,NA,NA,NA,NA
drug_strength,drug_concept_id,Yes,integer,The Concept representing the Branded Drug or Clinical Drug Product.,NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
@ -496,8 +496,8 @@ drug_strength,numerator_unit_concept_id,No,integer,The Concept representing the
drug_strength,denominator_value,No,float,"The amount of total liquid (or other divisible product, such as ointment, gel, spray, etc.).",NA,No,No,NA,NA,NA,NA,NA
drug_strength,denominator_unit_concept_id,No,integer,The Concept representing the denominator unit for the concentration of active ingredient.,NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
drug_strength,box_size,No,integer,The number of units of Clinical Branded Drug or Quantified Clinical or Branded Drug contained in a box as dispensed to the patient.,NA,No,No,NA,NA,NA,NA,NA
drug_strength,valid_start_date,Yes,date,"The date when the Concept was first
recorded. The default value is
drug_strength,valid_start_date,Yes,date,"The date when the Concept was first
recorded. The default value is
1-Jan-1970.",NA,No,No,NA,NA,NA,NA,NA
drug_strength,valid_end_date,Yes,date,The date when then Concept became invalid.,NA,No,No,NA,NA,NA,NA,NA
drug_strength,invalid_reason,No,varchar(1),"Reason the concept was invalidated. Possible values are D (deleted), U (replaced with an update) or NULL when valid_end_date has the default value.",NA,No,No,NA,NA,NA,NA,NA

1 cdmTableName cdmFieldName isRequired cdmDatatype userGuidance etlConventions isPrimaryKey isForeignKey fkTableName fkFieldName fkDomain fkClass unique DQ identifiers
12 person care_site_id No integer The Care Site refers to where the Provider typically provides the primary care. NA No Yes CARE_SITE CARE_SITE_ID NA NA NA
13 person person_source_value No varchar(50) Use this field to link back to persons in the source data. This is typically used for error checking of ETL logic. Some use cases require the ability to link back to persons in the source data. This field allows for the storing of the person value as it appears in the source. This field is not required but strongly recommended. No No NA NA NA NA NA
14 person gender_source_value No varchar(50) This field is used to store the biological sex of the person from the source data. It is not intended for use in standard analytics but for reference only. Put the assigned sex at birth of the person as it appears in the source data. No No NA NA NA NA NA
15 person gender_source_concept_id No integer Due to the small number of options, this tends to be zero. If the source data codes asigned sex at birth in a non-standard vocabulary, store the concept_id here. If the source data codes assigned sex at birth in a non-standard vocabulary, store the concept_id here. No Yes CONCEPT CONCEPT_ID NA NA NA
16 person race_source_value No varchar(50) This field is used to store the race of the person from the source data. It is not intended for use in standard analytics but for reference only. Put the race of the person as it appears in the source data. No No NA NA NA NA NA
17 person race_source_concept_id No integer Due to the small number of options, this tends to be zero. If the source data codes race in an OMOP supported vocabulary store the concept_id here. No Yes CONCEPT CONCEPT_ID NA NA NA
18 person ethnicity_source_value No varchar(50) This field is used to store the ethnicity of the person from the source data. It is not intended for use in standard analytics but for reference only. If the person has an ethnicity other than the OMB standard of "Hispanic" or "Not Hispanic" store that value from the source data here. No No NA NA NA NA NA
27 visit_occurrence visit_concept_id Yes integer This field contains a concept id representing the kind of visit, like inpatient or outpatient. All concepts in this field should be standard and belong to the Visit domain. Populate this field based on the kind of visit that took place for the person. For example this could be "Inpatient Visit", "Outpatient Visit", "Ambulatory Visit", etc. This table will contain standard concepts in the Visit domain. These concepts are arranged in a hierarchical structure to facilitate cohort definitions by rolling up to generally familiar Visits adopted in most healthcare systems worldwide. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Visit&standardConcept=Standard&page=1&pageSize=15&query=). No Yes CONCEPT CONCEPT_ID Visit NA NA
28 visit_occurrence visit_start_date Yes date For inpatient visits, the start date is typically the admission date. For outpatient visits the start date and end date will be the same. When populating VISIT_START_DATE, you should think about the patient experience to make decisions on how to define visits. In the case of an inpatient visit this should be the date the patient was admitted to the hospital or institution. In all other cases this should be the date of the patient-provider interaction. If this information is not available the record should be dropped. No No NA NA NA NA NA
29 visit_occurrence visit_start_datetime No datetime NA If no time is given for the start date of a visit, set it to midnight (00:00:0000). No No NA NA NA NA NA
30 visit_occurrence visit_end_date Yes date For inpatient visits the end date is typically the discharge date. Visit end dates are mandatory. If end dates are not provided in the source there are three ways in which to derive them: - Outpatient Visit: visit_end_datetime = visit_start_datetime - Emergency Room Visit: visit_end_datetime = visit_start_datetime - Inpatient Visit: Usually there is information about discharge. If not, you should be able to derive the end date from the sudden decline of activity or from the absence of inpatient procedures/drugs. - Non-hospital institution Visits: Particularly for claims data, if end dates are not provided assume the visit is for the duration of month that it occurs. For Inpatient Visits ongoing at the date of ETL, put date of processing the data into visit_end_datetime and visit_type_concept_id with 32220 "Still patient" to identify the visit as incomplete. - All other Visits: visit_end_datetime = visit_start_datetime. If this is a one-day visit the end date should match the start date. No No NA NA NA NA NA
31 visit_occurrence visit_end_datetime No datetime NA If no time is given for the end date of a visit, set it to midnight (00:00:0000). No No NA NA NA NA NA
32 visit_occurrence visit_type_concept_id Yes Integer Use this field to understand the provenance of the visit record, or where the record comes from. Populate this field based on the provenance of the visit record, as in whether it came from an EHR record or billing claim. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Type+Concept&standardConcept=Standard&page=1&pageSize=15&query=). A more detailed explanation of each Type Concept can be found on the [vocabulary wiki](https://github.com/OHDSI/Vocabulary-v5.0/wiki/Vocab.-TYPE_CONCEPT). No Yes CONCEPT CONCEPT_ID Type Concept NA NA
33 visit_occurrence provider_id No integer There will only be one provider per visit record and the ETL document should clearly state how they were chosen (attending, admitting, etc.). If there are multiple providers associated with a visit in the source, this can be reflected in the event tables (CONDITION_OCCURRENCE, PROCEDURE_OCCURRENCE, etc.) or in the VISIT_DETAIL table. If there are multiple providers associated with a visit, you will need to choose which one to put here. The additional providers can be stored in the [VISIT_DETAIL](https://ohdsi.github.io/CommonDataModel/cdm531.html#visit_detail) table. No Yes PROVIDER PROVIDER_ID NA NA NA
34 visit_occurrence care_site_id No integer This field provides information about the Care Site where the Visit took place. There should only be one Care Site associated with a Visit. No Yes CARE_SITE CARE_SITE_ID NA NA NA
35 visit_occurrence visit_source_value No varchar(50) This field houses the verbatim value from the source data representing the kind of visit that took place (inpatient, outpatient, emergency, etc.) If there is information about the kind of visit in the source data that value should be stored here. If a visit is an amalgamation of visits from the source then use a hierarchy to choose the visit source value, such as IP -> ER-> OP. This should line up with the logic chosen to determine how visits are created. No No NA NA NA NA NA
36 visit_occurrence visit_source_concept_id No integer NA If the visit source value is coded in the source data using an OMOP supported vocabulary put the concept id representing the source value here. No Yes CONCEPT CONCEPT_ID NA NA NA
37 visit_occurrence admitting_source_concept_id No integer Use this field to determine where the patient was admitted from. This concept is part of the visit domain and can indicate if a patient was admitted to the hospital from a long-term care facility, for example. If available, map the admitting_source_value to a standard concept in the visit domain. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Visit&standardConcept=Standard&page=1&pageSize=15&query=). If a person was admitted from home or was self-referred, set this to 0. No Yes CONCEPT CONCEPT_ID Visit NA NA
38 visit_occurrence admitting_source_value No varchar(50) NA This information may be called something different in the source data but the field is meant to contain a value indicating where a person was admitted from. Typically this applies only to visits that have a length of stay, like inpatient visits or long-term care visits. No No NA NA NA NA NA
50 visit_detail provider_id No integer There will only be one provider per **visit** record and the ETL document should clearly state how they were chosen (attending, admitting, etc.). This is a typical reason for leveraging the VISIT_DETAIL table as even though each VISIT_DETAIL record can only have one provider, there is no limit to the number of VISIT_DETAIL records that can be associated to a VISIT_OCCURRENCE record. The additional providers associated to a Visit can be stored in this table where each VISIT_DETAIL record represents a different provider. No Yes PROVIDER PROVIDER_ID NA NA NA
51 visit_detail care_site_id No integer This field provides information about the Care Site where the Visit Detail took place. There should only be one Care Site associated with a Visit Detail. No Yes CARE_SITE CARE_SITE_ID NA NA NA
52 visit_detail visit_detail_source_value No varchar(50) This field houses the verbatim value from the source data representing the kind of visit detail that took place (inpatient, outpatient, emergency, etc.) If there is information about the kind of visit detail in the source data that value should be stored here. If a visit is an amalgamation of visits from the source then use a hierarchy to choose the VISIT_DETAIL_SOURCE_VALUE, such as IP -> ER-> OP. This should line up with the logic chosen to determine how visits are created. No No NA NA NA NA NA
53 visit_detail visit_detail_source_concept_id No Integer NA If the VISIT_DETAIL_SOURCE_VALUE is coded in the source data using an OMOP supported vocabulary put the concept id representing the source value here. No Yes CONCEPT CONCEPT_ID NA NA NA
54 visit_detail admitting_source_value No Varchar(50) NA This information may be called something different in the source data but the field is meant to contain a value indicating where a person was admitted from. Typically this applies only to visits that have a length of stay, like inpatient visits or long-term care visits. No No NA NA NA NA NA
55 visit_detail admitting_source_concept_id No Integer Use this field to determine where the patient was admitted from. This concept is part of the visit domain and can indicate if a patient was admitted to the hospital from a long-term care facility, for example. If available, map the admitting_source_value to a standard concept in the visit domain. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Visit&standardConcept=Standard&page=1&pageSize=15&query=). If a person was admitted from home or was self-referred, set this to 0. No Yes CONCEPT CONCEPT_ID Visit NA NA
56 visit_detail discharge_to_source_value No Varchar(50) NA This information may be called something different in the source data but the field is meant to contain a value indicating where a person was discharged to after a visit, as in they went home or were moved to long-term care. Typically this applies only to visits that have a length of stay of a day or more. No No NA NA NA NA NA
57 visit_detail discharge_to_concept_id No integer Use this field to determine where the patient was discharged to after a visit detail record. This concept is part of the visit domain and can indicate if a patient was discharged to home or sent to a long-term care facility, for example. If available, map the DISCHARGE_TO_SOURCE_VALUE to a Standard Concept in the Visit domain. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Visit&standardConcept=Standard&page=1&pageSize=15&query=). No Yes CONCEPT CONCEPT_ID Visit NA NA
58 visit_detail preceding_visit_detail_id No integer Use this field to find the visit detail that occurred for the person prior to the given visit detail record. There could be a few days or a few years in between. The PRECEDING_VISIT_DETAIL_ID can be used to link a visit immediately preceding the current Visit Detail. Note this is not symmetrical, and there is no such thing as a "following_visit_id". No Yes VISIT_DETAIL VISIT_DETAIL_ID NA NA NA
59 visit_detail visit_detail_parent_id No integer Use this field to find the visit detail that subsumes the given visit detail record. This is used in the case that a visit detail record needs to be nested beyond the VISIT_OCCURRENCE/VISIT_DETAIL relationship. If there are multiple nested levels to how Visits are represented in the source, the VISIT_DETAIL_PARENT_ID can be used to record this relationship. No Yes VISIT_DETAIL VISIT_DETAIL_ID NA NA NA
60 visit_detail visit_occurrence_id Yes integer Use this field to link the VISIT_DETAIL record to its VISIT_OCCURRENCE. Put the VISIT_OCCURRENCE_ID that subsumes the VISIT_DETAIL record here. No Yes VISIT_OCCURRENCE VISIT_OCCURRENCE_ID NA NA NA
61 condition_occurrence condition_occurrence_id Yes integer The unique key given to a condition record for a person. Refer to the ETL for how duplicate conditions during the same visit were handled. Each instance of a condition present in the source data should be assigned this unique key. In some cases, a person can have multiple records of the same condition within the same visit. It is valid to keep these duplicates and assign them individual, unique, CONDITION_OCCURRENCE_IDs, though it is up to the ETL how they should be handled. Yes No NA NA NA NA NA
88 drug_exposure quantity No float NA To find the dose form of a drug the RELATIONSHIP table can be used where the relationship_id is 'Has dose form'. If liquid, quantity stands for the total amount dispensed or ordered of ingredient in the units given by the drug_strength table. If the unit from the source data does not align with the unit in the DRUG_STRENGTH table the quantity should be converted to the correct unit given in DRUG_STRENGTH. For clinical drugs with fixed dose forms (tablets etc.) the quantity is the number of units/tablets/capsules prescribed or dispensed (can be partial, but then only 1/2 or 1/3, not 0.01). Clinical drugs with divisible dose forms (injections) the quantity is the amount of ingredient the patient got. For example, if the injection is 2mg/mL but the patient got 80mL then quantity is reported as 160. Quantified clinical drugs with divisible dose forms (prefilled syringes), the quantity is the amount of ingredient similar to clinical drugs. Please see [how to calculate drug dose](https://ohdsi.github.io/CommonDataModel/drug_dose.html) for more information. No No NA NA NA NA NA
89 drug_exposure days_supply No integer The number of days of supply of the medication as recorded in the original prescription or dispensing record. Days supply can differ from actual drug duration (i.e. prescribed days supply vs actual exposure). The field should be left empty if the source data does not contain a verbatim days_supply, and should not be calculated from other fields.<br><br>Negative values are not allowed. If the source has negative days supply the record should be dropped as it is unknown if the patient actually took the drug. Several actions are possible: 1) record is not trustworthy and we remove the record entirely. 2) we trust the record and leave days_supply empty or 3) record needs to be combined with other record (e.g. reversal of prescription). High values (>365 days) should be investigated. If considered an error in the source data (e.g. typo), the value needs to be excluded to prevent creation of unrealistic long eras. No No NA NA NA NA NA
90 drug_exposure sig No varchar(MAX) This is the verbatim instruction for the drug as written by the provider. Put the written out instructions for the drug as it is verbatim in the source, if available. No No NA NA NA NA NA
91 drug_exposure route_concept_id No integer NA The standard CONCEPT_ID that the ROUTE_SOURCE_VALUE maps to in the route domain. No Yes CONCEPT CONCEPT_ID Route NA NA
92 drug_exposure lot_number No varchar(50) NA NA No No NA NA NA NA NA
93 drug_exposure provider_id No integer The Provider associated with drug record, e.g. the provider who wrote the prescription or the provider who administered the drug. The ETL may need to make a choice as to which PROVIDER_ID to put here. Based on what is available this may or may not be different than the provider associated with the overall VISIT_OCCURRENCE record, for example the ordering vs administering physician on an EHR record. No Yes PROVIDER PROVIDER_ID NA NA NA
94 drug_exposure visit_occurrence_id No integer The Visit during which the drug was prescribed, administered or dispensed. To populate this field drug exposures must be explicitly initiated in the visit. No Yes VISIT_OCCURRENCE VISIT_OCCURRENCE_ID NA NA NA
95 drug_exposure visit_detail_id No integer The VISIT_DETAIL record during which the drug exposure occurred. For example, if the person was in the ICU at the time of the drug administration the VISIT_OCCURRENCE record would reflect the overall hospital stay and the VISIT_DETAIL record would reflect the ICU stay during the hospital visit. Same rules apply as for the VISIT_OCCURRENCE_ID. No Yes VISIT_DETAIL VISIT_DETAIL_ID NA NA NA
96 drug_exposure drug_source_value No varchar(50) This field houses the verbatim value from the source data representing the drug exposure that occurred. For example, this could be an NDC or Gemscript code. This code is mapped to a Standard Drug Concept in the Standardized Vocabularies and the original code is stored here for reference. No No NA NA NA NA NA
97 drug_exposure drug_source_concept_id No integer This is the concept representing the drug source value and may not necessarily be standard. This field is discouraged from use in analysis because it is not required to contain Standard Concepts that are used across the OHDSI community, and should only be used when Standard Concepts do not adequately represent the source detail for the Drug necessary for a given analytic use case. Consider using DRUG_CONCEPT_ID instead to enable standardized analytics that can be consistent across the network. If the DRUG_SOURCE_VALUE is coded in the source data using an OMOP supported vocabulary put the concept id representing the source value here. No Yes CONCEPT CONCEPT_ID NA NA NA
98 drug_exposure route_source_value No varchar(50) This field houses the verbatim value from the source data representing the drug route. This information may be called something different in the source data but the field is meant to contain a value indicating when and how a drug was given to a patient. This source value is mapped to a standard concept which is stored in the ROUTE_CONCEPT_ID field. No No NA NA NA NA NA
99 drug_exposure dose_unit_source_value No varchar(50) This field houses the verbatim value from the source data representing the dose unit of the drug given. This information may be called something different in the source data but the field is meant to contain a value indicating the unit of dosage of drug given to the patient. This is an older column and will be deprecated in an upcoming version. No No NA NA NA NA NA
100 procedure_occurrence procedure_occurrence_id Yes integer The unique key given to a procedure record for a person. Refer to the ETL for how duplicate procedures during the same visit were handled. Each instance of a procedure occurrence in the source data should be assigned this unique key. In some cases, a person can have multiple records of the same procedure within the same visit. It is valid to keep these duplicates and assign them individual, unique, PROCEDURE_OCCURRENCE_IDs, though it is up to the ETL how they should be handled. Yes No NA NA NA NA NA
101 procedure_occurrence person_id Yes integer The PERSON_ID of the PERSON for whom the procedure is recorded. This may be a system generated code. NA No Yes PERSON PERSON_ID NA NA NA
102 procedure_occurrence procedure_concept_id Yes integer The PROCEDURE_CONCEPT_ID field is recommended for primary use in analyses, and must be used for network studies. This is the standard concept mapped from the source value which represents a procedure The CONCEPT_ID that the PROCEDURE_SOURCE_VALUE maps to. Only records whose source values map to standard concepts with a domain of "Procedure" should go in this table. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Procedure&standardConcept=Standard&page=1&pageSize=15&query=). No Yes CONCEPT CONCEPT_ID Procedure NA NA
103 procedure_occurrence procedure_date Yes date Use this date to determine the date the procedure occurred. If a procedure lasts more than a day, then it should be recorded as a separate record for each day the procedure occurred, this logic is in lieu of the procedure_end_date, which will be added in a future version of the CDM. No No NA NA NA NA NA
104 procedure_occurrence procedure_datetime No datetime NA This is not required, though it is in v6. If a source does not specify datetime the convention is to set the time to midnight (00:00:0000) No No NA NA NA NA NA
142 measurement provider_id No integer The provider associated with measurement record, e.g. the provider who ordered the test or the provider who recorded the result. The ETL may need to make a choice as to which PROVIDER_ID to put here. Based on what is available this may or may not be different than the provider associated with the overall VISIT_OCCURRENCE record. For example the admitting vs attending physician on an EHR record. No Yes PROVIDER PROVIDER_ID NA NA NA
143 measurement visit_occurrence_id No integer The visit during which the Measurement occurred. Depending on the structure of the source data, this may have to be determined based on dates. If a MEASUREMENT_DATE occurs within the start and end date of a Visit it is a valid ETL choice to choose the VISIT_OCCURRENCE_ID from the visit that subsumes it, even if not explicitly stated in the data. While not required, an attempt should be made to locate the VISIT_OCCURRENCE_ID of the measurement record. If a measurement is related to a visit explicitly in the source data, it is possible that the result date of the Measurement falls outside of the bounds of the Visit dates. No Yes VISIT_OCCURRENCE VISIT_OCCURRENCE_ID NA NA NA
144 measurement visit_detail_id No integer The VISIT_DETAIL record during which the Measurement occurred. For example, if the Person was in the ICU at the time the VISIT_OCCURRENCE record would reflect the overall hospital stay and the VISIT_DETAIL record would reflect the ICU stay during the hospital visit. Same rules apply as for the VISIT_OCCURRENCE_ID. No Yes VISIT_DETAIL VISIT_DETAIL_ID NA NA NA
145 measurement measurement_source_value No varchar(50) This field contains the exact value from the source data that represents the measurement that occurred. This value corresponds to a standardized CONCEPT_ID found in MEASUREMENT_CONCEPT_ID and in the 'Measurement' domain within the Standardized Vocabularies. The original code is retained here for reference purposes. No No NA NA NA NA NA
146 measurement measurement_source_concept_id No integer This is the concept representing the MEASUREMENT_SOURCE_VALUE and may not necessarily be standard. This field is discouraged from use in analysis because it is not required to contain Standard Concepts that are used across the OHDSI community, and should only be used when Standard Concepts do not adequately represent the source detail for the Measurement necessary for a given analytic use case. Consider using MEASUREMENT_CONCEPT_ID instead to enable standardized analytics that can be consistent across the network. If the MEASUREMENT_SOURCE_VALUE is coded in the source data using a vocabulary supported by OMOP Standardized Vocabularies, insert the CONCEPT_ID representing the source value here. No Yes CONCEPT CONCEPT_ID NA NA NA
147 measurement unit_source_value No varchar(50) This field contains the exact value from the source data that represents the unit of measurement used. This value corresponds to a standardized CONCEPT_ID found in UNIT_CONCEPT_ID and in the 'Unit' domain within the Standardized Vocabularies. The original code is retained here for reference purposes. No No NA NA NA NA NA
148 measurement value_source_value No varchar(50) This field houses the verbatim result value of the Measurement from the source data . If both a continuous and categorical result are given in the source data such that both VALUE_AS_NUMBER and VALUE_AS_CONCEPT_ID are both included, store the verbatim value that was mapped to VALUE_AS_CONCEPT_ID here. No No NA NA NA NA NA
190 note_nlp section_concept_id No integer NA The SECTION_CONCEPT_ID should be used to represent the note section contained in the NOTE_NLP record. These concepts can be found as parts of document panels and are based on the type of note written, i.e. a discharge summary. These panels can be found as concepts with the relationship 'Subsumes' to CONCEPT_ID [45875957](https://athena.ohdsi.org/search-terms/terms/45875957). No Yes CONCEPT CONCEPT_ID NA NA NA
191 note_nlp snippet No varchar(250) A small window of text surrounding the term NA No No NA NA NA NA NA
192 note_nlp "offset" No varchar(50) Character offset of the extracted term in the input note NA No No NA NA NA NA NA
193 note_nlp lexical_variant Yes varchar(250) Raw text extracted from the NLP tool. NA No No NA NA NA NA NA
194 note_nlp note_nlp_concept_id No integer NA NA No Yes CONCEPT CONCEPT_ID NA NA NA
195 note_nlp note_nlp_source_concept_id No integer NA NA No Yes CONCEPT CONCEPT_ID NA NA NA
196 note_nlp nlp_system No varchar(250) NA Name and version of the NLP system that extracted the term. Useful for data provenance. No No NA NA NA NA NA
211 specimen disease_status_concept_id No integer NA NA No Yes CONCEPT CONCEPT_ID NA NA NA
212 specimen specimen_source_id No varchar(50) This is the identifier for the specimen from the source system. NA No No NA NA NA NA NA
213 specimen specimen_source_value No varchar(50) NA NA No No NA NA NA NA NA
214 specimen unit_source_value No varchar(50) NA This unit for the quantity of the specimen, as represented in the source. No No NA NA NA NA NA
215 specimen anatomic_site_source_value No varchar(50) NA This is the site on the body where the specimen was taken from, as represented in the source. No No NA NA NA NA NA
216 specimen disease_status_source_value No varchar(50) NA NA No No NA NA NA NA NA
217 fact_relationship domain_concept_id_1 Yes integer NA NA No Yes CONCEPT CONCEPT_ID NA NA NA
218 fact_relationship fact_id_1 Yes integer NA NA No No NA NA NA NA NA
219 fact_relationship domain_concept_id_2 Yes integer NA NA No Yes CONCEPT CONCEPT_ID NA NA NA
220 fact_relationship fact_id_2 Yes integer NA NA No No NA NA NA NA NA
221 fact_relationship relationship_concept_id Yes integer NA NA No Yes CONCEPT CONCEPT_ID NA NA NA
222 location location_id Yes integer The unique key given to a unique Location. Each instance of a Location in the source data should be assigned this unique key. Yes No NA NA NA NA NA
223 location address_1 No varchar(50) This is the first line of the address. NA No No NA NA NA NA NA
224 location address_2 No varchar(50) This is the second line of the address NA No No NA NA NA NA NA
225 location city No varchar(50) NA NA No No NA NA NA NA NA
226 location state No varchar(2) NA NA No No NA NA NA NA NA
227 location zip No varchar(9) NA Zip codes are handled as strings of up to 9 characters length. For US addresses, these represent either a 3-digit abbreviated Zip code as provided by many sources for patient protection reasons, the full 5-digit Zip or the 9-digit (ZIP + 4) codes. Unless for specific reasons analytical methods should expect and utilize only the first 3 digits. For international addresses, different rules apply. No No NA NA NA NA NA
228 location county No varchar(20) NA NA No No NA NA NA NA NA
229 location location_source_value No varchar(50) NA Put the verbatim value for the location here, as it shows up in the source. No No NA NA NA NA NA
230 care_site care_site_id Yes integer NA Assign an id to each unique combination of location_id and place_of_service_source_value Yes No NA NA NA NA NA
231 care_site care_site_name No varchar(255) The name of the care_site as it appears in the source data NA No No NA NA NA NA NA
232 care_site place_of_service_concept_id No integer This is a high-level way of characterizing a Care Site. Typically, however, Care Sites can provide care in multiple settings (inpatient, outpatient, etc.) and this granularity should be reflected in the visit. Choose the concept in the visit domain that best represents the setting in which healthcare is provided in the Care Site. If most visits in a Care Site are Inpatient, then the place_of_service_concept_id should represent Inpatient. If information is present about a unique Care Site (e.g. Pharmacy) then a Care Site record should be created. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Visit&standardConcept=Standard&page=2&pageSize=15&query=). For information about how to populate this field please see the [THEMIS Conventions](https://ohdsi.github.io/Themis/tag_place_of_service.html). No Yes CONCEPT CONCEPT_ID NA NA NA
318 cdm_source source_description No varchar(MAX) The description of the CDM instance. NA No No NA NA NA NA NA
319 cdm_source source_documentation_reference No varchar(255) NA NA No No NA NA NA NA NA
320 cdm_source cdm_etl_reference No varchar(255) NA Version of the ETL script used. e.g. link to the Git release No No NA NA NA NA NA
321 cdm_source source_release_date No date The date the data was extracted from the source system. In some systems that is the same as the date the ETL was run. Typically the latest even date in the source is on the source_release_date. NA No No NA NA NA NA NA
322 cdm_source cdm_release_date No date The date the ETL script was completed. Typically this is after the source_release_date. NA No No NA NA NA NA NA
323 cdm_source cdm_version No varchar(10) Version of the OMOP CDM used as string. e.g. v5.4 NA No No NA NA NA NA NA
324 cdm_source vocabulary_version No varchar(20) NA NA No No NA NA NA NA NA
325 concept concept_id Yes integer A unique identifier for each Concept across all domains. NA Yes No NA NA NA NA NA
326 concept concept_name Yes varchar(255) An unambiguous, meaningful and descriptive name for the Concept. NA No No NA NA NA NA NA
334 concept invalid_reason No varchar(1) Reason the Concept was invalidated. Possible values are D (deleted), U (replaced with an update) or NULL when valid_end_date has the default value. NA No No NA NA NA NA NA
335 vocabulary vocabulary_id Yes varchar(20) A unique identifier for each Vocabulary, such as ICD9CM, SNOMED, Visit. NA Yes No NA NA NA NA NA
336 vocabulary vocabulary_name Yes varchar(255) The name describing the vocabulary, for example, International Classification of Diseases, Ninth Revision, Clinical Modification, Volume 1 and 2 (NCHS) etc. NA No No NA NA NA NA NA
337 vocabulary vocabulary_reference Yes varchar(255) External reference to documentation or available download of the about the vocabulary. NA No No NA NA NA NA NA
338 vocabulary vocabulary_version No varchar(255) Version of the Vocabulary as indicated in the source. NA No No NA NA NA NA NA
339 vocabulary vocabulary_concept_id Yes integer A Concept that represents the Vocabulary the VOCABULARY record belongs to. NA No Yes CONCEPT CONCEPT_ID NA NA NA
340 domain domain_id Yes varchar(20) A unique key for each domain. NA Yes No NA NA NA NA NA
341 domain domain_name Yes varchar(255) The name describing the Domain, e.g. Condition, Procedure, Measurement etc. NA No No NA NA NA NA NA
342 domain domain_concept_id Yes integer A Concept representing the Domain Concept the DOMAIN record belongs to. NA No Yes CONCEPT CONCEPT_ID NA NA NA
343 concept_class concept_class_id Yes varchar(20) A unique key for each class. NA Yes No NA NA NA NA NA
344 concept_class concept_class_name Yes varchar(255) The name describing the Concept Class, e.g. Clinical Finding, Ingredient, etc. NA No No NA NA NA NA NA
345 concept_class concept_class_concept_id Yes integer A Concept that represents the Concept Class. NA No Yes CONCEPT CONCEPT_ID NA NA NA
346 concept_relationship concept_id_1 Yes integer NA NA No Yes CONCEPT CONCEPT_ID NA NA NA
347 concept_relationship concept_id_2 Yes integer NA NA No Yes CONCEPT CONCEPT_ID NA NA NA
348 concept_relationship relationship_id Yes varchar(20) The relationship between CONCEPT_ID_1 and CONCEPT_ID_2. Please see the [Vocabulary Conventions](https://ohdsi.github.io/CommonDataModel/dataModelConventions.html#concept_relationships). for more information. NA No Yes RELATIONSHIP RELATIONSHIP_ID NA NA NA
349 concept_relationship valid_start_date Yes date The date when the relationship is first recorded. NA No No NA NA NA NA NA
350 concept_relationship valid_end_date Yes date The date when the relationship is invalidated. NA No No NA NA NA NA NA
351 concept_relationship invalid_reason No varchar(1) Reason the relationship was invalidated. Possible values are 'D' (deleted), 'U' (updated) or NULL. NA No No NA NA NA NA NA
352 relationship relationship_id Yes varchar(20) The type of relationship captured by the relationship record. NA Yes No NA NA NA NA NA
353 relationship relationship_name Yes varchar(255) NA NA No No NA NA NA NA NA
369 source_to_concept_map target_concept_id Yes integer The target Concept to which the source code is being mapped. NA No Yes CONCEPT CONCEPT_ID NA NA NA
370 source_to_concept_map target_vocabulary_id Yes varchar(20) The Vocabulary of the target Concept. NA No Yes VOCABULARY VOCABULARY_ID NA NA NA
371 source_to_concept_map valid_start_date Yes date The date when the mapping instance was first recorded. NA No No NA NA NA NA NA
372 source_to_concept_map valid_end_date Yes date The date when the mapping instance became invalid because it was deleted or superseded (updated) by a new relationship. Default value is 31-Dec-2099. NA No No NA NA NA NA NA
373 source_to_concept_map invalid_reason No varchar(1) Reason the mapping instance was invalidated. Possible values are D (deleted), U (replaced with an update) or NULL when valid_end_date has the default value. NA No No NA NA NA NA NA
374 drug_strength drug_concept_id Yes integer The Concept representing the Branded Drug or Clinical Drug Product. NA No Yes CONCEPT CONCEPT_ID NA NA NA
375 drug_strength ingredient_concept_id Yes integer The Concept representing the active ingredient contained within the drug product. Combination Drugs will have more than one record in this table, one for each active Ingredient. No Yes CONCEPT CONCEPT_ID NA NA NA
376 drug_strength amount_value No float The numeric value or the amount of active ingredient contained within the drug product. NA No No NA NA NA NA NA
377 drug_strength amount_unit_concept_id No integer The Concept representing the Unit of measure for the amount of active ingredient contained within the drug product. NA No Yes CONCEPT CONCEPT_ID NA NA NA
378 drug_strength numerator_value No float The concentration of the active ingredient contained within the drug product. NA No No NA NA NA NA NA
379 drug_strength numerator_unit_concept_id No integer The Concept representing the Unit of measure for the concentration of active ingredient. NA No Yes CONCEPT CONCEPT_ID NA NA NA
380 drug_strength denominator_value No float The amount of total liquid (or other divisible product, such as ointment, gel, spray, etc.). NA No No NA NA NA NA NA
381 drug_strength denominator_unit_concept_id No integer The Concept representing the denominator unit for the concentration of active ingredient. NA No Yes CONCEPT CONCEPT_ID NA NA NA
382 drug_strength box_size No integer The number of units of Clinical Branded Drug or Quantified Clinical or Branded Drug contained in a box as dispensed to the patient. NA No No NA NA NA NA NA
383 drug_strength valid_start_date Yes date The date when the Concept was first recorded. The default value is 1-Jan-1970. NA No No NA NA NA NA NA
384 drug_strength valid_end_date Yes date The date when then Concept became invalid. NA No No NA NA NA NA NA
385 drug_strength invalid_reason No varchar(1) Reason the concept was invalidated. Possible values are D (deleted), U (replaced with an update) or NULL when valid_end_date has the default value. NA No No NA NA NA NA NA
386 cohort_definition cohort_definition_id Yes integer This is the identifier given to the cohort, usually by the ATLAS application NA No No NA NA NA NA NA
387 cohort_definition cohort_definition_name Yes varchar(255) A short description of the cohort NA No No NA NA NA NA NA
388 cohort_definition cohort_definition_description No varchar(MAX) A complete description of the cohort. NA No No NA NA NA NA NA
389 cohort_definition definition_type_concept_id Yes integer Type defining what kind of Cohort Definition the record represents and how the syntax may be executed. NA No Yes CONCEPT CONCEPT_ID NA NA NA
390 cohort_definition cohort_definition_syntax No varchar(MAX) Syntax or code to operationalize the Cohort Definition. NA No No NA NA NA NA NA
391 cohort_definition subject_concept_id Yes integer This field contains a Concept that represents the domain of the subjects that are members of the cohort (e.g., Person, Provider, Visit). NA No Yes CONCEPT CONCEPT_ID NA NA NA
392 cohort_definition cohort_initiation_date No date A date to indicate when the Cohort was initiated in the COHORT table. NA No No NA NA NA NA NA
393 attribute_definition attribute_definition_id Yes integer NA NA No No NA NA NA NA NA
394 attribute_definition attribute_name Yes varchar(255) NA NA No No NA NA NA NA NA
395 attribute_definition attribute_description No varchar(MAX) NA NA No No NA NA NA NA NA
396 attribute_definition attribute_type_concept_id Yes integer NA NA No Yes CONCEPT CONCEPT_ID NA NA NA
397 attribute_definition attribute_syntax No varchar(MAX) NA NA No No NA NA NA NA NA
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@ -1,20 +1,20 @@
cdmTableName,schema,isRequired,conceptPrefix,measurePersonCompleteness,measurePersonCompletenessThreshold,validation,tableDescription,userGuidance,etlConventions
person,CDM,Yes,NA,No,NA,NA,"This table serves as the central identity management for all Persons in the database. It contains records that uniquely identify each person or patient, and some demographic information.",All records in this table are independent Persons.,"All Persons in a database needs one record in this table, unless they fail data quality requirements specified in the ETL. Persons with no Events should have a record nonetheless. If more than one data source contributes Events to the database, Persons must be reconciled, if possible, across the sources to create one single record per Person. The content of the BIRTH_DATETIME must be equivalent to the content of BIRTH_DAY, BIRTH_MONTH and BIRTH_YEAR.<br><br>For detailed conventions for how to populate this table, please refer to the [THEMIS repository](https://ohdsi.github.io/Themis/person.html)."
observation_period,CDM,Yes,NA,Yes,0,NA,"This table contains records which define spans of time during which two conditions are expected to hold: (i) Clinical Events that happened to the Person are recorded in the Event tables, and (ii) absence of records indicate such Events did not occur during this span of time.","For each Person, one or more OBSERVATION_PERIOD records may be present, but they will not overlap or be back to back to each other. Events may exist outside all of the time spans of the OBSERVATION_PERIOD records for a patient, however, absence of an Event outside these time spans cannot be construed as evidence of absence of an Event. Incidence or prevalence rates should only be calculated for the time of active OBSERVATION_PERIOD records. When constructing cohorts, outside Events can be used for inclusion criteria definition, but without any guarantee for the performance of these criteria. Also, OBSERVATION_PERIOD records can be as short as a single day, greatly disturbing the denominator of any rate calculation as part of cohort characterizations. To avoid that, apply minimal observation time as a requirement for any cohort definition.","Each Person needs to have at least one OBSERVATION_PERIOD record, which should represent time intervals with a high capture rate of Clinical Events. Some source data have very similar concepts, such as enrollment periods in insurance claims data. In other source data such as most EHR systems these time spans need to be inferred under a set of assumptions. It is the discretion of the ETL developer to define these assumptions. In many ETL solutions the start date of the first occurrence or the first high quality occurrence of a Clinical Event (Condition, Drug, Procedure, Device, Measurement, Visit) is defined as the start of the OBSERVATION_PERIOD record, and the end date of the last occurrence of last high quality occurrence of a Clinical Event, or the end of the database period becomes the end of the OBSERVATOIN_PERIOD for each Person. If a Person only has a single Clinical Event the OBSERVATION_PERIOD record can be as short as one day. Depending on these definitions it is possible that Clinical Events fall outside the time spans defined by OBSERVATION_PERIOD records. Family history or history of Clinical Events generally are not used to generate OBSERVATION_PERIOD records around the time they are referring to. Any two overlapping or adjacent OBSERVATION_PERIOD records have to be merged into one."
visit_occurrence,CDM,No,VISIT_,Yes,0,NA,"This table contains Events where Persons engage with the healthcare system for a duration of time. They are often also called ""Encounters"". Visits are defined by a configuration of circumstances under which they occur, such as (i) whether the patient comes to a healthcare institution, the other way around, or the interaction is remote, (ii) whether and what kind of trained medical staff is delivering the service during the Visit, and (iii) whether the Visit is transient or for a longer period involving a stay in bed.","The configuration defining the Visit are described by Concepts in the Visit Domain, which form a hierarchical structure, but rolling up to generally familiar Visits adopted in most healthcare systems worldwide:
- [Inpatient Visit](https://athena.ohdsi.org/search-terms/terms/9201): Person visiting hospital, at a Care Site, in bed, for duration of more than one day, with physicians and other Providers permanently available to deliver service around the clock
- [Emergency Room Visit](https://athena.ohdsi.org/search-terms/terms/9203): Person visiting dedicated healthcare institution for treating emergencies, at a Care Site, within one day, with physicians and Providers permanently available to deliver service around the clock
- [Emergency Room and Inpatient Visit](https://athena.ohdsi.org/search-terms/terms/262): Person visiting ER followed by a subsequent Inpatient Visit, where Emergency department is part of hospital, and transition from the ER to other hospital departments is undefined
- [Non-hospital institution Visit](https://athena.ohdsi.org/search-terms/terms/42898160): Person visiting dedicated institution for reasons of poor health, at a Care Site, long-term or permanently, with no physician but possibly other Providers permanently available to deliver service around the clock
- [Outpatient Visit](https://athena.ohdsi.org/search-terms/terms/9202): Person visiting dedicated ambulatory healthcare institution, at a Care Site, within one day, without bed, with physicians or medical Providers delivering service during Visit
- [Home Visit](https://athena.ohdsi.org/search-terms/terms/581476): Provider visiting Person, without a Care Site, within one day, delivering service
- [Telehealth Visit](https://athena.ohdsi.org/search-terms/terms/5083): Patient engages with Provider through communication media
- [Pharmacy Visit](https://athena.ohdsi.org/search-terms/terms/581458): Person visiting pharmacy for dispensing of Drug, at a Care Site, within one day
- [Laboratory Visit](https://athena.ohdsi.org/search-terms/terms/32036): Patient visiting dedicated institution, at a Care Site, within one day, for the purpose of a Measurement.
- [Ambulance Visit](https://athena.ohdsi.org/search-terms/terms/581478): Person using transportation service for the purpose of initiating one of the other Visits, without a Care Site, within one day, potentially with Providers accompanying the Visit and delivering service
- [Case Management Visit](https://athena.ohdsi.org/search-terms/terms/38004193): Person interacting with healthcare system, without a Care Site, within a day, with no Providers involved, for administrative purposes
visit_occurrence,CDM,No,VISIT_,Yes,0,NA,"This table contains Events where Persons engage with the healthcare system for a duration of time. They are often also called ""Encounters"". Visits are defined by a configuration of circumstances under which they occur, such as (i) whether the patient comes to a healthcare institution, the other way around, or the interaction is remote, (ii) whether and what kind of trained medical staff is delivering the service during the Visit, and (iii) whether the Visit is transient or for a longer period involving a stay in bed.","The configuration defining the Visit are described by Concepts in the Visit Domain, which form a hierarchical structure, but rolling up to generally familiar Visits adopted in most healthcare systems worldwide:
- [Inpatient Visit](https://athena.ohdsi.org/search-terms/terms/9201): Person visiting hospital, at a Care Site, in bed, for duration of more than one day, with physicians and other Providers permanently available to deliver service around the clock
- [Emergency Room Visit](https://athena.ohdsi.org/search-terms/terms/9203): Person visiting dedicated healthcare institution for treating emergencies, at a Care Site, within one day, with physicians and Providers permanently available to deliver service around the clock
- [Emergency Room and Inpatient Visit](https://athena.ohdsi.org/search-terms/terms/262): Person visiting ER followed by a subsequent Inpatient Visit, where Emergency department is part of hospital, and transition from the ER to other hospital departments is undefined
- [Non-hospital institution Visit](https://athena.ohdsi.org/search-terms/terms/42898160): Person visiting dedicated institution for reasons of poor health, at a Care Site, long-term or permanently, with no physician but possibly other Providers permanently available to deliver service around the clock
- [Outpatient Visit](https://athena.ohdsi.org/search-terms/terms/9202): Person visiting dedicated ambulatory healthcare institution, at a Care Site, within one day, without bed, with physicians or medical Providers delivering service during Visit
- [Home Visit](https://athena.ohdsi.org/search-terms/terms/581476): Provider visiting Person, without a Care Site, within one day, delivering service
- [Telehealth Visit](https://athena.ohdsi.org/search-terms/terms/5083): Patient engages with Provider through communication media
- [Pharmacy Visit](https://athena.ohdsi.org/search-terms/terms/581458): Person visiting pharmacy for dispensing of Drug, at a Care Site, within one day
- [Laboratory Visit](https://athena.ohdsi.org/search-terms/terms/32036): Patient visiting dedicated institution, at a Care Site, within one day, for the purpose of a Measurement.
- [Ambulance Visit](https://athena.ohdsi.org/search-terms/terms/581478): Person using transportation service for the purpose of initiating one of the other Visits, without a Care Site, within one day, potentially with Providers accompanying the Visit and delivering service
- [Case Management Visit](https://athena.ohdsi.org/search-terms/terms/38004193): Person interacting with healthcare system, without a Care Site, within a day, with no Providers involved, for administrative purposes
The Visit duration, or 'length of stay', is defined as VISIT_END_DATE - VISIT_START_DATE. For all Visits this is <1 day, except Inpatient Visits and Non-hospital institution Visits. The CDM also contains the VISIT_DETAIL table where additional information about the Visit is stored, for example, transfers between units during an inpatient Visit.","Visits can be derived easily if the source data contain coding systems for Place of Service or Procedures, like CPT codes for well visits. In those cases, the codes can be looked up and mapped to a Standard Visit Concept. Otherwise, Visit Concepts have to be identified in the ETL process. This table will contain concepts in the Visit domain. These concepts are arranged in a hierarchical structure to facilitate cohort definitions by rolling up to generally familiar Visits adopted in most healthcare systems worldwide. Visits can be adjacent to each other, i.e. the end date of one can be identical with the start date of the other. As a consequence, more than one-day Visits or their descendants can be recorded for the same day. Multi-day visits must not overlap, i.e. share days other than start and end days. It is often the case that some logic should be written for how to define visits and how to assign Visit_Concept_Id. For example, in US claims outpatient visits that appear to occur within the time period of an inpatient visit can be rolled into one with the same Visit_Occurrence_Id. In EHR data inpatient visits that are within one day of each other may be strung together to create one visit. It will all depend on the source data and how encounter records should be translated to visit occurrences. Providers can be associated with a Visit through the PROVIDER_ID field, or indirectly through PROCEDURE_OCCURRENCE records linked both to the VISIT and PROVIDER tables."
visit_detail,CDM,No,VISIT_DETAIL_,Yes,0,NA,The VISIT_DETAIL table is an optional table used to represents details of each record in the parent VISIT_OCCURRENCE table. A good example of this would be the movement between units in a hospital during an inpatient stay or claim lines associated with a one insurance claim. For every record in the VISIT_OCCURRENCE table there may be 0 or more records in the VISIT_DETAIL table with a 1:n relationship where n may be 0. The VISIT_DETAIL table is structurally very similar to VISIT_OCCURRENCE table and belongs to the visit domain.,"The configuration defining the Visit Detail is described by Concepts in the Visit Domain, which form a hierarchical structure. The Visit Detail record will have an associated to the Visit Occurrence record in two ways: <br> 1. The Visit Detail record will have the VISIT_OCCURRENCE_ID it is associated to 2. The VISIT_DETAIL_CONCEPT_ID will be a descendant of the VISIT_CONCEPT_ID for the Visit.","It is not mandatory that the VISIT_DETAIL table be filled in, but if you find that the logic to create VISIT_OCCURRENCE records includes the roll-up of multiple smaller records to create one picture of a Visit then it is a good idea to use VISIT_DETAIL. In EHR data, for example, a Person may be in the hospital but instead of one over-arching Visit their encounters are recorded as times they interacted with a health care provider. A Person in the hospital interacts with multiple providers multiple times a day so the encounters must be strung together using some heuristic (defined by the ETL) to identify the entire Visit. In this case the encounters would be considered Visit Details and the entire Visit would be the Visit Occurrence. In this example it is also possible to use the Vocabulary to distinguish Visit Details from a Visit Occurrence by setting the VISIT_CONCEPT_ID to [9201](https://athena.ohdsi.org/search-terms/terms/9201) and the VISIT_DETAIL_CONCEPT_IDs either to 9201 or its children to indicate where the patient was in the hospital at the time of care."
condition_occurrence,CDM,No,CONDITION_,Yes,0,NA,"This table contains records of Events of a Person suggesting the presence of a disease or medical condition stated as a diagnosis, a sign, or a symptom, which is either observed by a Provider or reported by the patient.","Conditions are defined by Concepts from the Condition domain, which form a complex hierarchy. As a result, the same Person with the same disease may have multiple Condition records, which belong to the same hierarchical family. Most Condition records are mapped from diagnostic codes, but recorded signs, symptoms and summary descriptions also contribute to this table. Rule out diagnoses should not be recorded in this table, but in reality their negating nature is not always captured in the source data, and other precautions must be taken when when identifying Persons who should suffer from the recorded Condition. Record all conditions as they exist in the source data. Any decisions about diagnosis/phenotype definitions would be done through cohort specifications. These cohorts can be housed in the [COHORT](https://ohdsi.github.io/CommonDataModel/cdm531.html#payer_plan_period) table. Conditions span a time interval from start to end, but are typically recorded as single snapshot records with no end date. The reason is twofold: (i) At the time of the recording the duration is not known and later not recorded, and (ii) the Persons typically cease interacting with the healthcare system when they feel better, which leads to incomplete capture of resolved Conditions. The [CONDITION_ERA](https://ohdsi.github.io/CommonDataModel/cdm531.html#condition_era) table addresses this issue. Family history and past diagnoses ('history of') are not recorded in this table. Instead, they are listed in the [OBSERVATION](https://ohdsi.github.io/CommonDataModel/cdm531.html#observation) table. Codes written in the process of establishing the diagnosis, such as 'question of' of and 'rule out', should not represented here. Instead, they should be recorded in the [OBSERVATION](https://ohdsi.github.io/CommonDataModel/cdm531.html#observation) table, if they are used for analyses. However, this information is not always available.",Source codes and source text fields mapped to Standard Concepts of the Condition Domain have to be recorded here.
@ -22,63 +22,63 @@ drug_exposure,CDM,No,DRUG_,Yes,0,NA,"This table captures records about the expos
procedure_occurrence,CDM,No,PROCEDURE_,Yes,0,NA,"This table contains records of activities or processes ordered by, or carried out by, a healthcare provider on the patient with a diagnostic or therapeutic purpose.","Lab tests are not a procedure, if something is observed with an expected resulting amount and unit then it should be a measurement. Phlebotomy is a procedure but so trivial that it tends to be rarely captured. It can be assumed that there is a phlebotomy procedure associated with many lab tests, therefore it is unnecessary to add them as separate procedures. If the user finds the same procedure over concurrent days, it is assumed those records are part of a procedure lasting more than a day. This logic is in lieu of the procedure_end_date, which will be added in a future version of the CDM.","If a procedure lasts more than 24 hours, then it should be recorded as a separate record for each day the procedure occurred, this logic is in lieu of the PROCEDURE_END_DATE, which will be added in a future version of the CDM. When dealing with duplicate records, the ETL must determine whether to sum them up into one record or keep them separate. Things to consider are: - Same Procedure - Same PROCEDURE_DATETIME - Same Visit Occurrence or Visit Detail - Same Provider - Same Modifier for Procedures. Source codes and source text fields mapped to Standard Concepts of the Procedure Domain have to be recorded here."
device_exposure,CDM,No,DEVICE_,Yes,0,NA,"The Device domain captures information about a person's exposure to a foreign physical object or instrument which is used for diagnostic or therapeutic purposes through a mechanism beyond chemical action. Devices include implantable objects (e.g. pacemakers, stents, artificial joints), medical equipment and supplies (e.g. bandages, crutches, syringes), other instruments used in medical procedures (e.g. sutures, defibrillators) and material used in clinical care (e.g. adhesives, body material, dental material, surgical material).","The distinction between Devices or supplies and Procedures are sometimes blurry, but the former are physical objects while the latter are actions, often to apply a Device or supply.",Source codes and source text fields mapped to Standard Concepts of the Device Domain have to be recorded here.
measurement,CDM,No,MEASUREMENT_,Yes,0,NA,"The MEASUREMENT table contains records of Measurements, i.e. structured values (numerical or categorical) obtained through systematic and standardized examination or testing of a Person or Person's sample. The MEASUREMENT table contains both orders and results of such Measurements as laboratory tests, vital signs, quantitative findings from pathology reports, etc. Measurements are stored as attribute value pairs, with the attribute as the Measurement Concept and the value representing the result. The value can be a Concept (stored in VALUE_AS_CONCEPT), or a numerical value (VALUE_AS_NUMBER) with a Unit (UNIT_CONCEPT_ID). The Procedure for obtaining the sample is housed in the PROCEDURE_OCCURRENCE table, though it is unnecessary to create a PROCEDURE_OCCURRENCE record for each measurement if one does not exist in the source data. Measurements differ from Observations in that they require a standardized test or some other activity to generate a quantitative or qualitative result. If there is no result, it is assumed that the lab test was conducted but the result was not captured.","Measurements are predominately lab tests with a few exceptions, like blood pressure or function tests. Results are given in the form of a value and unit combination. When investigating measurements, look for operator_concept_ids (<, >, etc.).","Only records where the source value maps to a Concept in the measurement domain should be included in this table. Even though each Measurement always has a result, the fields VALUE_AS_NUMBER and VALUE_AS_CONCEPT_ID are not mandatory as often the result is not given in the source data. When the result is not known, the Measurement record represents just the fact that the corresponding Measurement was carried out, which in itself is already useful information for some use cases. For some Measurement Concepts, the result is included in the test. For example, ICD10 CONCEPT_ID [45548980](https://athena.ohdsi.org/search-terms/terms/45548980) 'Abnormal level of unspecified serum enzyme' indicates a Measurement and the result (abnormal). In those situations, the CONCEPT_RELATIONSHIP table in addition to the 'Maps to' record contains a second record with the relationship_id set to 'Maps to value'. In this example, the 'Maps to' relationship directs to [4046263](https://athena.ohdsi.org/search-terms/terms/4046263) 'Enzyme measurement' as well as a 'Maps to value' record to [4135493](https://athena.ohdsi.org/search-terms/terms/4135493) 'Abnormal'."
observation,CDM,No,OBSERVATION_,Yes,0,NA,"The OBSERVATION table captures clinical facts about a Person obtained in the context of examination, questioning or a procedure. Any data that cannot be represented by any other domains, such as social and lifestyle facts, medical history, family history, etc. are recorded here.","Observations differ from Measurements in that they do not require a standardized test or some other activity to generate clinical fact. Typical observations are medical history, family history, the stated need for certain treatment, social circumstances, lifestyle choices, healthcare utilization patterns, etc. If the generation clinical facts requires a standardized testing such as lab testing or imaging and leads to a standardized result, the data item is recorded in the MEASUREMENT table. If the clinical fact observed determines a sign, symptom, diagnosis of a disease or other medical condition, it is recorded in the CONDITION_OCCURRENCE table. Valid Observation Concepts are not enforced to be from any domain but they must not belong to the Condition, Procedure, Drug, Device, Specimen, or Measurement domains and they must be Standard Concepts. <br><br>The observation table usually records the date or datetime of when the observation was obtained, not the date of the observation starting. For example, if the patient reports that they had a heart attack when they were 50, the observation date or datetime is the date of the report, the heart attack observation can have a value_as_concept which captures how long ago the observation applied to the patient.","Records whose Source Values map to any domain besides Condition, Procedure, Drug, Specimen, Measurement or Device should be stored in the Observation table. Observations can be stored as attribute value pairs, with the attribute as the Observation Concept and the value representing the clinical fact. This fact can be a Concept (stored in VALUE_AS_CONCEPT), a numerical value (VALUE_AS_NUMBER), a verbatim string (VALUE_AS_STRING), or a datetime (VALUE_AS_DATETIME). Even though Observations do not have an explicit result, the clinical fact can be stated separately from the type of Observation in the VALUE_AS_* fields. It is recommended for Observations that are suggestive statements of positive assertion should have a value of 'Yes' (concept_id=4188539), recorded, even though the null value is the equivalent."
observation,CDM,No,OBSERVATION_,Yes,0,NA,"The OBSERVATION table captures clinical facts about a Person obtained in the context of examination, questioning or a procedure. Any data that cannot be represented by any other domains, such as social and lifestyle facts, medical history, family history, etc. are recorded here.","Observations differ from Measurements in that they do not require a standardized test or some other activity to generate clinical fact. Typical observations are medical history, family history, the stated need for certain treatment, social circumstances, lifestyle choices, healthcare utilization patterns, etc. If the generation clinical facts requires a standardized testing such as lab testing or imaging and leads to a standardized result, the data item is recorded in the MEASUREMENT table. If the clinical fact observed determines a sign, symptom, diagnosis of a disease or other medical condition, it is recorded in the CONDITION_OCCURRENCE table. Valid Observation Concepts are not enforced to be from any domain but they must not belong to the Condition, Procedure, Drug, Device, Specimen, or Measurement domains and they must be Standard Concepts. <br><br>The observation table usually records the date or datetime of when the observation was obtained, not the date of the observation starting. For example, if the patient reports that they had a heart attack when they were 50, the observation date or datetime is the date of the report, the heart attack observation can have a value_as_concept which captures how long ago the observation applied to the patient.","Records whose Source Values map to any domain besides Condition, Procedure, Drug, Specimen, Measurement or Device should be stored in the Observation table. Observations can be stored as attribute value pairs, with the attribute as the Observation Concept and the value representing the clinical fact. This fact can be a Concept (stored in VALUE_AS_CONCEPT), a numerical value (VALUE_AS_NUMBER) or a verbatim string (VALUE_AS_STRING). Even though Observations do not have an explicit result, the clinical fact can be stated separately from the type of Observation in the VALUE_AS_* fields. It is recommended for Observations that are suggestive statements of positive assertion should have a value of 'Yes' (concept_id=4188539), recorded, even though the null value is the equivalent."
death,CDM,No,NA,No,NA,NA,"The death domain contains the clinical event for how and when a Person dies. A person can have up to one record if the source system contains evidence about the Death, such as: Condition in an administrative claim, status of enrollment into a health plan, or explicit record in EHR data.",NA,"For specific conventions on how to populate this table, please refer to the [THEMIS repository](https://ohdsi.github.io/Themis/death.html)."
note,CDM,No,NA,Yes,0,NA,"The NOTE table captures unstructured information that was recorded by a provider about a patient in free text (in ASCII, or preferably in UTF8 format) notes on a given date. The type of note_text is CLOB or varchar(MAX) depending on RDBMS.",NA,"HL7/LOINC CDO is a standard for consistent naming of documents to support a range of use cases: retrieval, organization, display, and exchange. It guides the creation of LOINC codes for clinical notes. CDO annotates each document with 5 dimensions:
- **Kind of Document**: Characterizes the general structure of the document at a macro level (e.g. Anesthesia Consent)
- **Type of Service**: Characterizes the kind of service or activity (e.g. evaluations, consultations, and summaries). The notion of time sequence, e.g., at the beginning (admission) at the end (discharge) is subsumed in this axis. Example: Discharge Teaching.
- **Setting**: Setting is an extension of CMS's definitions (e.g. Inpatient, Outpatient)
- **Subject Matter Domain (SMD)**: Characterizes the subject matter domain of a note (e.g. Anesthesiology)
- **Role**: Characterizes the training or professional level of the author of the document, but does not break down to specialty or subspecialty (e.g. Physician)
Each combination of these 5 dimensions rolls up to a unique LOINC code.
According to CDO requirements, only 2 of the 5 dimensions are required to properly annotate a document; Kind of Document and any one of the other 4 dimensions.
note,CDM,No,NA,Yes,0,NA,"The NOTE table captures unstructured information that was recorded by a provider about a patient in free text (in ASCII, or preferably in UTF8 format) notes on a given date. The type of note_text is CLOB or varchar(MAX) depending on RDBMS.",NA,"HL7/LOINC CDO is a standard for consistent naming of documents to support a range of use cases: retrieval, organization, display, and exchange. It guides the creation of LOINC codes for clinical notes. CDO annotates each document with 5 dimensions:
- **Kind of Document**: Characterizes the general structure of the document at a macro level (e.g. Anesthesia Consent)
- **Type of Service**: Characterizes the kind of service or activity (e.g. evaluations, consultations, and summaries). The notion of time sequence, e.g., at the beginning (admission) at the end (discharge) is subsumed in this axis. Example: Discharge Teaching.
- **Setting**: Setting is an extension of CMS's definitions (e.g. Inpatient, Outpatient)
- **Subject Matter Domain (SMD)**: Characterizes the subject matter domain of a note (e.g. Anesthesiology)
- **Role**: Characterizes the training or professional level of the author of the document, but does not break down to specialty or subspecialty (e.g. Physician)
Each combination of these 5 dimensions rolls up to a unique LOINC code.
According to CDO requirements, only 2 of the 5 dimensions are required to properly annotate a document; Kind of Document and any one of the other 4 dimensions.
However, not all the permutations of the CDO dimensions will necessarily yield an existing LOINC code. Each of these dimensions are contained in the OMOP Vocabulary under the domain of 'Meas Value' with each dimension represented as a Concept Class."
note_nlp,CDM,No,NA,No,NA,NA,The NOTE_NLP table encodes all output of NLP on clinical notes. Each row represents a single extracted term from a note.,NA,NA
specimen,CDM,No,SPECIMEN_,Yes,0,NA,The specimen domain contains the records identifying biological samples from a person.,NA,"Anatomic site is coded at the most specific level of granularity possible, such that higher level classifications can be derived using the Standardized Vocabularies."
fact_relationship,CDM,No,NA,No,NA,NA,"The FACT_RELATIONSHIP table contains records about the relationships between facts stored as records in any table of the CDM. Relationships can be defined between facts from the same domain, or different domains. Examples of Fact Relationships include: [Person relationships](https://athena.ohdsi.org/search-terms/terms?domain=Relationship&standardConcept=Standard&page=2&pageSize=15&query=) (parent-child), care site relationships (hierarchical organizational structure of facilities within a health system), indication relationship (between drug exposures and associated conditions), usage relationships (of devices during the course of an associated procedure), or facts derived from one another (measurements derived from an associated specimen).",NA,"All relationships are directional, and each relationship is represented twice symmetrically within the FACT_RELATIONSHIP table. For example, two persons if person_id = 1 is the mother of person_id = 2 two records are in the FACT_RELATIONSHIP table (all strings in fact concept_id records in the Concept table:
- Person, 1, Person, 2, parent of
fact_relationship,CDM,No,NA,No,NA,NA,"The FACT_RELATIONSHIP table contains records about the relationships between facts stored as records in any table of the CDM. Relationships can be defined between facts from the same domain, or different domains. Examples of Fact Relationships include: [Person relationships](https://athena.ohdsi.org/search-terms/terms?domain=Relationship&standardConcept=Standard&page=2&pageSize=15&query=) (parent-child), care site relationships (hierarchical organizational structure of facilities within a health system), indication relationship (between drug exposures and associated conditions), usage relationships (of devices during the course of an associated procedure), or facts derived from one another (measurements derived from an associated specimen).",NA,"All relationships are directional, and each relationship is represented twice symmetrically within the FACT_RELATIONSHIP table. For example, two persons if person_id = 1 is the mother of person_id = 2 two records are in the FACT_RELATIONSHIP table (all strings in fact concept_id records in the Concept table:
- Person, 1, Person, 2, parent of
- Person, 2, Person, 1, child of"
location,CDM,No,NA,No,NA,NA,The LOCATION table represents a generic way to capture physical location or address information of Persons and Care Sites.,NA,"Each address or Location is unique and is present only once in the table. Locations do not contain names, such as the name of a hospital. In order to construct a full address that can be used in the postal service, the address information from the Location needs to be combined with information from the Care Site."
care_site,CDM,No,NA,No,NA,NA,"The CARE_SITE table contains a list of uniquely identified institutional (physical or organizational) units where healthcare delivery is practiced (offices, wards, hospitals, clinics, etc.).",NA,"Care site is a unique combination of location_id and nature of the site - the latter could be the place of service, name, or another characteristic in your source data. Care site does not take into account the provider (human) information such a specialty. Many source data do not make a distinction between individual and institutional providers. The CARE_SITE table contains the institutional providers. If the source, instead of uniquely identifying individual Care Sites, only provides limited information such as Place of Service, generic or ""pooled"" Care Site records are listed in the CARE_SITE table. There can be hierarchical and business relationships between Care Sites. For example, wards can belong to clinics or departments, which can in turn belong to hospitals, which in turn can belong to hospital systems, which in turn can belong to HMOs.The relationships between Care Sites are defined in the FACT_RELATIONSHIP table.<br><br>For additional detailed conventions on how to populate this table, please refer to [THEMIS repository](https://ohdsi.github.io/Themis/care_site.html)."
provider,CDM,No,NA,No,NA,NA,"The PROVIDER table contains a list of uniquely identified healthcare providers; duplication is not allowed. These are individuals providing hands-on healthcare to patients, such as physicians, nurses, midwives, physical therapists etc.","Many sources do not make a distinction between individual and institutional providers. The PROVIDER table contains the individual providers. If the source only provides limited information such as specialty instead of uniquely identifying individual providers, generic or 'pooled' Provider records are listed in the PROVIDER table.",NA
payer_plan_period,CDM,No,NA,Yes,0,NA,"The PAYER_PLAN_PERIOD table captures details of the period of time that a Person is continuously enrolled under a specific health Plan benefit structure from a given Payer. Each Person receiving healthcare is typically covered by a health benefit plan, which pays for (fully or partially), or directly provides, the care. These benefit plans are provided by payers, such as health insurances or state or government agencies. In each plan the details of the health benefits are defined for the Person or her family, and the health benefit Plan might change over time typically with increasing utilization (reaching certain cost thresholds such as deductibles), plan availability and purchasing choices of the Person. The unique combinations of Payer organizations, health benefit Plans and time periods in which they are valid for a Person are recorded in this table.","A Person can have multiple, overlapping, Payer_Plan_Periods in this table. For example, medical and drug coverage in the US can be represented by two Payer_Plan_Periods. The details of the benefit structure of the Plan is rarely known, the idea is just to identify that the Plans are different.",NA
cost,CDM,No,NA,No,NA,NA,"The COST table captures records containing the cost of any medical event recorded in one of the OMOP clinical event tables such as DRUG_EXPOSURE, PROCEDURE_OCCURRENCE, VISIT_OCCURRENCE, VISIT_DETAIL, DEVICE_OCCURRENCE, OBSERVATION or MEASUREMENT.
cost,CDM,No,NA,No,NA,NA,"The COST table captures records containing the cost of any medical event recorded in one of the OMOP clinical event tables such as DRUG_EXPOSURE, PROCEDURE_OCCURRENCE, VISIT_OCCURRENCE, VISIT_DETAIL, DEVICE_OCCURRENCE, OBSERVATION or MEASUREMENT.
Each record in the cost table account for the amount of money transacted for the clinical event. So, the COST table may be used to represent both receivables (charges) and payments (paid), each transaction type represented by its COST_CONCEPT_ID. The COST_TYPE_CONCEPT_ID field will use concepts in the Standardized Vocabularies to designate the source (provenance) of the cost data. A reference to the health plan information in the PAYER_PLAN_PERIOD table is stored in the record for information used for the adjudication system to determine the persons benefit for the clinical event.","When dealing with summary costs, the cost of the goods or services the provider provides is often not known directly, but derived from the hospital charges multiplied by an average cost-to-charge ratio.","One cost record is generated for each response by a payer. In a claims databases, the payment and payment terms reported by the payer for the goods or services billed will generate one cost record. If the source data has payment information for more than one payer (i.e. primary insurance and secondary insurance payment for one entity), then a cost record is created for each reporting payer. Therefore, it is possible for one procedure to have multiple cost records for each payer, but typically it contains one or no record per entity. Payer reimbursement cost records will be identified by using the PAYER_PLAN_ID field. Drug costs are composed of ingredient cost (the amount charged by the wholesale distributor or manufacturer), the dispensing fee (the amount charged by the pharmacy and the sales tax)."
drug_era,CDM,No,NA,Yes,0,NA,"A Drug Era is defined as a span of time when the Person is assumed to be exposed to a particular active ingredient. A Drug Era is not the same as a Drug Exposure: Exposures are individual records corresponding to the source when Drug was delivered to the Person, while successive periods of Drug Exposures are combined under certain rules to produce continuous Drug Eras. Every record in the DRUG_EXPOSURE table should be part of a drug era based on the dates of exposure. ",NA,The SQL script for generating DRUG_ERA records can be found [here](https://ohdsi.github.io/CommonDataModel/sqlScripts.html#drug_eras).
dose_era,CDM,No,NA,Yes,0,NA,A Dose Era is defined as a span of time when the Person is assumed to be exposed to a constant dose of a specific active ingredient.,NA,"Dose Eras will be derived from records in the DRUG_EXPOSURE table and the Dose information from the DRUG_STRENGTH table using a standardized algorithm. Dose Form information is not taken into account. So, if the patient changes between different formulations, or different manufacturers with the same formulation, the Dose Era is still spanning the entire time of exposure to the Ingredient."
condition_era,CDM,No,NA,Yes,0,NA,"A Condition Era is defined as a span of time when the Person is assumed to have a given condition. Similar to Drug Eras, Condition Eras are chronological periods of Condition Occurrence and every Condition Occurrence record should be part of a Condition Era. Combining individual Condition Occurrences into a single Condition Era serves two purposes:
- It allows aggregation of chronic conditions that require frequent ongoing care, instead of treating each Condition Occurrence as an independent event.
- It allows aggregation of multiple, closely timed doctor visits for the same Condition to avoid double-counting the Condition Occurrences.
For example, consider a Person who visits her Primary Care Physician (PCP) and who is referred to a specialist. At a later time, the Person visits the specialist, who confirms the PCP's original diagnosis and provides the appropriate treatment to resolve the condition. These two independent doctor visits should be aggregated into one Condition Era.",NA,"Each Condition Era corresponds to one or many Condition Occurrence records that form a continuous interval.
The condition_concept_id field contains Concepts that are identical to those of the CONDITION_OCCURRENCE table records that make up the Condition Era. In contrast to Drug Eras, Condition Eras are not aggregated to contain Conditions of different hierarchical layers. The SQl Script for generating CONDITION_ERA records can be found [here](https://ohdsi.github.io/CommonDataModel/sqlScripts.html#condition_eras)
The Condition Era Start Date is the start date of the first Condition Occurrence.
condition_era,CDM,No,NA,Yes,0,NA,"A Condition Era is defined as a span of time when the Person is assumed to have a given condition. Similar to Drug Eras, Condition Eras are chronological periods of Condition Occurrence and every Condition Occurrence record should be part of a Condition Era. Combining individual Condition Occurrences into a single Condition Era serves two purposes:
- It allows aggregation of chronic conditions that require frequent ongoing care, instead of treating each Condition Occurrence as an independent event.
- It allows aggregation of multiple, closely timed doctor visits for the same Condition to avoid double-counting the Condition Occurrences.
For example, consider a Person who visits her Primary Care Physician (PCP) and who is referred to a specialist. At a later time, the Person visits the specialist, who confirms the PCP's original diagnosis and provides the appropriate treatment to resolve the condition. These two independent doctor visits should be aggregated into one Condition Era.",NA,"Each Condition Era corresponds to one or many Condition Occurrence records that form a continuous interval.
The condition_concept_id field contains Concepts that are identical to those of the CONDITION_OCCURRENCE table records that make up the Condition Era. In contrast to Drug Eras, Condition Eras are not aggregated to contain Conditions of different hierarchical layers. The SQl Script for generating CONDITION_ERA records can be found [here](https://ohdsi.github.io/CommonDataModel/sqlScripts.html#condition_eras)
The Condition Era Start Date is the start date of the first Condition Occurrence.
The Condition Era End Date is the end date of the last Condition Occurrence. Condition Eras are built with a Persistence Window of 30 days, meaning, if no occurrence of the same condition_concept_id happens within 30 days of any one occurrence, it will be considered the condition_era_end_date."
metadata,CDM,No,NA,No,NA,NA,The METADATA table contains metadata information about a dataset that has been transformed to the OMOP Common Data Model.,NA,NA
cdm_source,CDM,No,NA,No,NA,NA,The CDM_SOURCE table contains detail about the source database and the process used to transform the data into the OMOP Common Data Model.,NA,NA
concept,VOCAB,No,NA,No,NA,NA,"The Standardized Vocabularies contains records, or Concepts, that uniquely identify each fundamental unit of meaning used to express clinical information in all domain tables of the CDM. Concepts are derived from vocabularies, which represent clinical information across a domain (e.g. conditions, drugs, procedures) through the use of codes and associated descriptions. Some Concepts are designated Standard Concepts, meaning these Concepts can be used as normative expressions of a clinical entity within the OMOP Common Data Model and standardized analytics. Each Standard Concept belongs to one Domain, which defines the location where the Concept would be expected to occur within the data tables of the CDM. Concepts can represent broad categories ('Cardiovascular disease'), detailed clinical elements ('Myocardial infarction of the anterolateral wall'), or modifying characteristics and attributes that define Concepts at various levels of detail (severity of a disease, associated morphology, etc.). Records in the Standardized Vocabularies tables are derived from national or international vocabularies such as SNOMED-CT, RxNorm, and LOINC, or custom OMOP Concepts defined to cover various aspects of observational data analysis.
","The primary purpose of the CONCEPT table is to provide a standardized representation of medical Concepts, allowing for consistent querying and analysis across the healthcare databases.
concept,VOCAB,No,NA,No,NA,NA,"The Standardized Vocabularies contains records, or Concepts, that uniquely identify each fundamental unit of meaning used to express clinical information in all domain tables of the CDM. Concepts are derived from vocabularies, which represent clinical information across a domain (e.g. conditions, drugs, procedures) through the use of codes and associated descriptions. Some Concepts are designated Standard Concepts, meaning these Concepts can be used as normative expressions of a clinical entity within the OMOP Common Data Model and standardized analytics. Each Standard Concept belongs to one Domain, which defines the location where the Concept would be expected to occur within the data tables of the CDM. Concepts can represent broad categories ('Cardiovascular disease'), detailed clinical elements ('Myocardial infarction of the anterolateral wall'), or modifying characteristics and attributes that define Concepts at various levels of detail (severity of a disease, associated morphology, etc.). Records in the Standardized Vocabularies tables are derived from national or international vocabularies such as SNOMED-CT, RxNorm, and LOINC, or custom OMOP Concepts defined to cover various aspects of observational data analysis.
","The primary purpose of the CONCEPT table is to provide a standardized representation of medical Concepts, allowing for consistent querying and analysis across the healthcare databases.
Users can join the CONCEPT table with other tables in the CDM to enrich clinical data with standardized Concept information or use the CONCEPT table as a reference for mapping clinical data from source terminologies to Standard Concepts.",NA
vocabulary,VOCAB,No,NA,No,NA,NA,The VOCABULARY table includes a list of the Vocabularies integrated from various sources or created de novo in OMOP CDM. This reference table contains a single record for each Vocabulary and includes a descriptive name and other associated attributes for the Vocabulary.,"The primary purpose of the VOCABULARY table is to provide explicit information about specific vocabulary versions and the references to the sources from which they are asserted. Users can identify the version of a particular vocabulary used in the database, enabling consistency and reproducibility in data analysis. Besides, users can check the vocabulary release version in their CDM which refers to the vocabulary_id = 'None'.",NA
domain,VOCAB,No,NA,No,NA,NA,"The DOMAIN table includes a list of OMOP-defined Domains to which the Concepts of the Standardized Vocabularies can belong. A Domain represents a clinical definition whereby we assign matching Concepts for the standardized fields in the CDM tables. For example, the Condition Domain contains Concepts that describe a patient condition, and these Concepts can only be used in the condition_concept_id field of the CONDITION_OCCURRENCE and CONDITION_ERA tables. This reference table is populated with a single record for each Domain, including a Domain ID and a descriptive name for every Domain.","Users can leverage the DOMAIN table to explore the full spectrum of health-related data Domains available in the Standardized Vocabularies. Also, the information in the DOMAIN table may be used as a reference for mapping source data to OMOP domains, facilitating data harmonization and interoperability.",NA
concept_class,VOCAB,No,NA,No,NA,NA,"The CONCEPT_CLASS table includes semantic categories that reference the source structure of each Vocabulary. Concept Classes represent so-called horizontal (e.g. MedDRA, RxNorm) or vertical levels (e.g. SNOMED) of the vocabulary structure. Vocabularies without any Concept Classes, such as HCPCS, use the vocabulary_id as the Concept Class. This reference table is populated with a single record for each Concept Class, which includes a Concept Class ID and a fully specified Concept Class name.
concept_class,VOCAB,No,NA,No,NA,NA,"The CONCEPT_CLASS table includes semantic categories that reference the source structure of each Vocabulary. Concept Classes represent so-called horizontal (e.g. MedDRA, RxNorm) or vertical levels (e.g. SNOMED) of the vocabulary structure. Vocabularies without any Concept Classes, such as HCPCS, use the vocabulary_id as the Concept Class. This reference table is populated with a single record for each Concept Class, which includes a Concept Class ID and a fully specified Concept Class name.
",Users can utilize the CONCEPT_CLASS table to explore the different classes or categories of concepts within the OHDSI vocabularies.,NA
concept_relationship,VOCAB,No,NA,No,NA,NA,"The CONCEPT_RELATIONSHIP table contains records that define relationships between any two Concepts and the nature or type of the relationship. This table captures various types of relationships, including hierarchical, associative, and other semantic connections, enabling comprehensive analysis and interpretation of clinical concepts. Every kind of relationship is defined in the RELATIONSHIP table.","The CONCEPT_RELATIONSHIP table can be used to explore hierarchical or attribute relationships between concepts to understand the hierarchical structure of clinical concepts and uncover implicit connections and associations within healthcare data. For example, users can utilize mapping relationships ('Maps to') to harmonize data from different sources and terminologies, enabling interoperability and data integration across disparate datasets.",NA
relationship,VOCAB,No,NA,No,NA,NA,The RELATIONSHIP table provides a reference list of all types of relationships that can be used to associate any two concepts in the CONCEPT_RELATIONSHP table.,NA,NA
concept_synonym,VOCAB,No,NA,No,NA,NA,The CONCEPT_SYNONYM table is used to store alternate names and descriptions for Concepts.,NA,NA
concept_ancestor,VOCAB,No,NA,No,NA,NA,"The CONCEPT_ANCESTOR table is designed to simplify observational analysis by providing the complete hierarchical relationships between Concepts. Only direct parent-child relationships between Concepts are stored in the CONCEPT_RELATIONSHIP table. To determine higher level ancestry connections, all individual direct relationships would have to be navigated at analysis time. The CONCEPT_ANCESTOR table includes records for all parent-child relationships, as well as grandparent-grandchild relationships and those of any other level of lineage. Using the CONCEPT_ANCESTOR table allows for querying for all descendants of a hierarchical concept. For example, drug ingredients and drug products are all descendants of a drug class ancestor.
concept_ancestor,VOCAB,No,NA,No,NA,NA,"The CONCEPT_ANCESTOR table is designed to simplify observational analysis by providing the complete hierarchical relationships between Concepts. Only direct parent-child relationships between Concepts are stored in the CONCEPT_RELATIONSHIP table. To determine higher level ancestry connections, all individual direct relationships would have to be navigated at analysis time. The CONCEPT_ANCESTOR table includes records for all parent-child relationships, as well as grandparent-grandchild relationships and those of any other level of lineage. Using the CONCEPT_ANCESTOR table allows for querying for all descendants of a hierarchical concept. For example, drug ingredients and drug products are all descendants of a drug class ancestor.
This table is entirely derived from the CONCEPT, CONCEPT_RELATIONSHIP and RELATIONSHIP tables.",NA,NA
source_to_concept_map,VOCAB,No,NA,No,NA,NA,"The source to concept map table is a legacy data structure within the OMOP Common Data Model, recommended for use in ETL processes to maintain local source codes which are not available as Concepts in the Standardized Vocabularies, and to establish mappings for each source code into a Standard Concept as target_concept_ids that can be used to populate the Common Data Model tables. The SOURCE_TO_CONCEPT_MAP table is no longer populated with content within the Standardized Vocabularies published to the OMOP community.",NA,NA
drug_strength,VOCAB,No,NA,No,NA,NA,The DRUG_STRENGTH table contains structured content about the amount or concentration and associated units of a specific ingredient contained within a particular drug product. This table is supplemental information to support standardized analysis of drug utilization.,NA,NA
cohort_definition,VOCAB,No,NA,No,NA,NA,"The COHORT_DEFINITION table contains records defining a Cohort derived from the data through the associated description and syntax and upon instantiation (execution of the algorithm) placed into the COHORT table. Cohorts are a set of subjects that satisfy a given combination of inclusion criteria for a duration of time. The COHORT_DEFINITION table provides a standardized structure for maintaining the rules governing the inclusion of a subject into a cohort, and can store operational programming code to instantiate the cohort within the OMOP Common Data Model.",NA,NA
attribute_definition,VOCAB,No,NA,No,NA,NA,"The ATTRIBUTE_DEFINITION table contains records to define each attribute
through an associated description and syntax. Attributes are derived elements
that can be selected or calculated for a subject within a cohort. The
ATTRIBUTE_DEFINITION table provides a standardized structure for
maintaining the rules governing the calculation of covariates for a subject in a
cohort, and can store operational programming code to instantiate the
attribute_definition,VOCAB,No,NA,No,NA,NA,"The ATTRIBUTE_DEFINITION table contains records to define each attribute
through an associated description and syntax. Attributes are derived elements
that can be selected or calculated for a subject within a cohort. The
ATTRIBUTE_DEFINITION table provides a standardized structure for
maintaining the rules governing the calculation of covariates for a subject in a
cohort, and can store operational programming code to instantiate the
attributes for a given cohort within the OMOP Common Data Model.",NA,NA
1 cdmTableName schema isRequired conceptPrefix measurePersonCompleteness measurePersonCompletenessThreshold validation tableDescription userGuidance etlConventions
2 person CDM Yes NA No NA NA This table serves as the central identity management for all Persons in the database. It contains records that uniquely identify each person or patient, and some demographic information. All records in this table are independent Persons. All Persons in a database needs one record in this table, unless they fail data quality requirements specified in the ETL. Persons with no Events should have a record nonetheless. If more than one data source contributes Events to the database, Persons must be reconciled, if possible, across the sources to create one single record per Person. The content of the BIRTH_DATETIME must be equivalent to the content of BIRTH_DAY, BIRTH_MONTH and BIRTH_YEAR.<br><br>For detailed conventions for how to populate this table, please refer to the [THEMIS repository](https://ohdsi.github.io/Themis/person.html).
3 observation_period CDM Yes NA Yes 0 NA This table contains records which define spans of time during which two conditions are expected to hold: (i) Clinical Events that happened to the Person are recorded in the Event tables, and (ii) absence of records indicate such Events did not occur during this span of time. For each Person, one or more OBSERVATION_PERIOD records may be present, but they will not overlap or be back to back to each other. Events may exist outside all of the time spans of the OBSERVATION_PERIOD records for a patient, however, absence of an Event outside these time spans cannot be construed as evidence of absence of an Event. Incidence or prevalence rates should only be calculated for the time of active OBSERVATION_PERIOD records. When constructing cohorts, outside Events can be used for inclusion criteria definition, but without any guarantee for the performance of these criteria. Also, OBSERVATION_PERIOD records can be as short as a single day, greatly disturbing the denominator of any rate calculation as part of cohort characterizations. To avoid that, apply minimal observation time as a requirement for any cohort definition. Each Person needs to have at least one OBSERVATION_PERIOD record, which should represent time intervals with a high capture rate of Clinical Events. Some source data have very similar concepts, such as enrollment periods in insurance claims data. In other source data such as most EHR systems these time spans need to be inferred under a set of assumptions. It is the discretion of the ETL developer to define these assumptions. In many ETL solutions the start date of the first occurrence or the first high quality occurrence of a Clinical Event (Condition, Drug, Procedure, Device, Measurement, Visit) is defined as the start of the OBSERVATION_PERIOD record, and the end date of the last occurrence of last high quality occurrence of a Clinical Event, or the end of the database period becomes the end of the OBSERVATOIN_PERIOD for each Person. If a Person only has a single Clinical Event the OBSERVATION_PERIOD record can be as short as one day. Depending on these definitions it is possible that Clinical Events fall outside the time spans defined by OBSERVATION_PERIOD records. Family history or history of Clinical Events generally are not used to generate OBSERVATION_PERIOD records around the time they are referring to. Any two overlapping or adjacent OBSERVATION_PERIOD records have to be merged into one.
4 visit_occurrence CDM No VISIT_ Yes 0 NA This table contains Events where Persons engage with the healthcare system for a duration of time. They are often also called "Encounters". Visits are defined by a configuration of circumstances under which they occur, such as (i) whether the patient comes to a healthcare institution, the other way around, or the interaction is remote, (ii) whether and what kind of trained medical staff is delivering the service during the Visit, and (iii) whether the Visit is transient or for a longer period involving a stay in bed. The configuration defining the Visit are described by Concepts in the Visit Domain, which form a hierarchical structure, but rolling up to generally familiar Visits adopted in most healthcare systems worldwide: - [Inpatient Visit](https://athena.ohdsi.org/search-terms/terms/9201): Person visiting hospital, at a Care Site, in bed, for duration of more than one day, with physicians and other Providers permanently available to deliver service around the clock - [Emergency Room Visit](https://athena.ohdsi.org/search-terms/terms/9203): Person visiting dedicated healthcare institution for treating emergencies, at a Care Site, within one day, with physicians and Providers permanently available to deliver service around the clock - [Emergency Room and Inpatient Visit](https://athena.ohdsi.org/search-terms/terms/262): Person visiting ER followed by a subsequent Inpatient Visit, where Emergency department is part of hospital, and transition from the ER to other hospital departments is undefined - [Non-hospital institution Visit](https://athena.ohdsi.org/search-terms/terms/42898160): Person visiting dedicated institution for reasons of poor health, at a Care Site, long-term or permanently, with no physician but possibly other Providers permanently available to deliver service around the clock - [Outpatient Visit](https://athena.ohdsi.org/search-terms/terms/9202): Person visiting dedicated ambulatory healthcare institution, at a Care Site, within one day, without bed, with physicians or medical Providers delivering service during Visit - [Home Visit](https://athena.ohdsi.org/search-terms/terms/581476): Provider visiting Person, without a Care Site, within one day, delivering service - [Telehealth Visit](https://athena.ohdsi.org/search-terms/terms/5083): Patient engages with Provider through communication media - [Pharmacy Visit](https://athena.ohdsi.org/search-terms/terms/581458): Person visiting pharmacy for dispensing of Drug, at a Care Site, within one day - [Laboratory Visit](https://athena.ohdsi.org/search-terms/terms/32036): Patient visiting dedicated institution, at a Care Site, within one day, for the purpose of a Measurement. - [Ambulance Visit](https://athena.ohdsi.org/search-terms/terms/581478): Person using transportation service for the purpose of initiating one of the other Visits, without a Care Site, within one day, potentially with Providers accompanying the Visit and delivering service - [Case Management Visit](https://athena.ohdsi.org/search-terms/terms/38004193): Person interacting with healthcare system, without a Care Site, within a day, with no Providers involved, for administrative purposes The Visit duration, or 'length of stay', is defined as VISIT_END_DATE - VISIT_START_DATE. For all Visits this is <1 day, except Inpatient Visits and Non-hospital institution Visits. The CDM also contains the VISIT_DETAIL table where additional information about the Visit is stored, for example, transfers between units during an inpatient Visit. Visits can be derived easily if the source data contain coding systems for Place of Service or Procedures, like CPT codes for well visits. In those cases, the codes can be looked up and mapped to a Standard Visit Concept. Otherwise, Visit Concepts have to be identified in the ETL process. This table will contain concepts in the Visit domain. These concepts are arranged in a hierarchical structure to facilitate cohort definitions by rolling up to generally familiar Visits adopted in most healthcare systems worldwide. Visits can be adjacent to each other, i.e. the end date of one can be identical with the start date of the other. As a consequence, more than one-day Visits or their descendants can be recorded for the same day. Multi-day visits must not overlap, i.e. share days other than start and end days. It is often the case that some logic should be written for how to define visits and how to assign Visit_Concept_Id. For example, in US claims outpatient visits that appear to occur within the time period of an inpatient visit can be rolled into one with the same Visit_Occurrence_Id. In EHR data inpatient visits that are within one day of each other may be strung together to create one visit. It will all depend on the source data and how encounter records should be translated to visit occurrences. Providers can be associated with a Visit through the PROVIDER_ID field, or indirectly through PROCEDURE_OCCURRENCE records linked both to the VISIT and PROVIDER tables.
5 visit_detail CDM No VISIT_DETAIL_ Yes 0 NA The VISIT_DETAIL table is an optional table used to represents details of each record in the parent VISIT_OCCURRENCE table. A good example of this would be the movement between units in a hospital during an inpatient stay or claim lines associated with a one insurance claim. For every record in the VISIT_OCCURRENCE table there may be 0 or more records in the VISIT_DETAIL table with a 1:n relationship where n may be 0. The VISIT_DETAIL table is structurally very similar to VISIT_OCCURRENCE table and belongs to the visit domain. The configuration defining the Visit Detail is described by Concepts in the Visit Domain, which form a hierarchical structure. The Visit Detail record will have an associated to the Visit Occurrence record in two ways: <br> 1. The Visit Detail record will have the VISIT_OCCURRENCE_ID it is associated to 2. The VISIT_DETAIL_CONCEPT_ID will be a descendant of the VISIT_CONCEPT_ID for the Visit. It is not mandatory that the VISIT_DETAIL table be filled in, but if you find that the logic to create VISIT_OCCURRENCE records includes the roll-up of multiple smaller records to create one picture of a Visit then it is a good idea to use VISIT_DETAIL. In EHR data, for example, a Person may be in the hospital but instead of one over-arching Visit their encounters are recorded as times they interacted with a health care provider. A Person in the hospital interacts with multiple providers multiple times a day so the encounters must be strung together using some heuristic (defined by the ETL) to identify the entire Visit. In this case the encounters would be considered Visit Details and the entire Visit would be the Visit Occurrence. In this example it is also possible to use the Vocabulary to distinguish Visit Details from a Visit Occurrence by setting the VISIT_CONCEPT_ID to [9201](https://athena.ohdsi.org/search-terms/terms/9201) and the VISIT_DETAIL_CONCEPT_IDs either to 9201 or its children to indicate where the patient was in the hospital at the time of care.
6 condition_occurrence CDM No CONDITION_ Yes 0 NA This table contains records of Events of a Person suggesting the presence of a disease or medical condition stated as a diagnosis, a sign, or a symptom, which is either observed by a Provider or reported by the patient. Conditions are defined by Concepts from the Condition domain, which form a complex hierarchy. As a result, the same Person with the same disease may have multiple Condition records, which belong to the same hierarchical family. Most Condition records are mapped from diagnostic codes, but recorded signs, symptoms and summary descriptions also contribute to this table. Rule out diagnoses should not be recorded in this table, but in reality their negating nature is not always captured in the source data, and other precautions must be taken when when identifying Persons who should suffer from the recorded Condition. Record all conditions as they exist in the source data. Any decisions about diagnosis/phenotype definitions would be done through cohort specifications. These cohorts can be housed in the [COHORT](https://ohdsi.github.io/CommonDataModel/cdm531.html#payer_plan_period) table. Conditions span a time interval from start to end, but are typically recorded as single snapshot records with no end date. The reason is twofold: (i) At the time of the recording the duration is not known and later not recorded, and (ii) the Persons typically cease interacting with the healthcare system when they feel better, which leads to incomplete capture of resolved Conditions. The [CONDITION_ERA](https://ohdsi.github.io/CommonDataModel/cdm531.html#condition_era) table addresses this issue. Family history and past diagnoses ('history of') are not recorded in this table. Instead, they are listed in the [OBSERVATION](https://ohdsi.github.io/CommonDataModel/cdm531.html#observation) table. Codes written in the process of establishing the diagnosis, such as 'question of' of and 'rule out', should not represented here. Instead, they should be recorded in the [OBSERVATION](https://ohdsi.github.io/CommonDataModel/cdm531.html#observation) table, if they are used for analyses. However, this information is not always available. Source codes and source text fields mapped to Standard Concepts of the Condition Domain have to be recorded here.
7 drug_exposure CDM No DRUG_ Yes 0 NA This table captures records about the exposure to a Drug ingested or otherwise introduced into the body. A Drug is a biochemical substance formulated in such a way that when administered to a Person it will exert a certain biochemical effect on the metabolism. Drugs include prescription and over-the-counter medicines, vaccines, and large-molecule biologic therapies. Radiological devices ingested or applied locally do not count as Drugs. The purpose of records in this table is to indicate an exposure to a certain drug as best as possible. In this context a drug is defined as an active ingredient. Drug Exposures are defined by Concepts from the Drug domain, which form a complex hierarchy. As a result, one DRUG_SOURCE_CONCEPT_ID may map to multiple standard concept ids if it is a combination product. Records in this table represent prescriptions written, prescriptions dispensed, and drugs administered by a provider to name a few. The DRUG_TYPE_CONCEPT_ID can be used to find and filter on these types. This table includes additional information about the drug products, the quantity given, and route of administration. Information about quantity and dose is provided in a variety of different ways and it is important for the ETL to provide as much information as possible from the data. Depending on the provenance of the data fields may be captured differently i.e. quantity for drugs administered may have a separate meaning from quantity for prescriptions dispensed. If a patient has multiple records on the same day for the same drug or procedures the ETL should not de-dupe them unless there is probable reason to believe the item is a true data duplicate. Take note on how to handle refills for prescriptions written.<br><br>For detailed conventions on how to populate this table, please refer to the [THEMIS repository](https://ohdsi.github.io/Themis/drug_exposure.html).
8 procedure_occurrence CDM No PROCEDURE_ Yes 0 NA This table contains records of activities or processes ordered by, or carried out by, a healthcare provider on the patient with a diagnostic or therapeutic purpose. Lab tests are not a procedure, if something is observed with an expected resulting amount and unit then it should be a measurement. Phlebotomy is a procedure but so trivial that it tends to be rarely captured. It can be assumed that there is a phlebotomy procedure associated with many lab tests, therefore it is unnecessary to add them as separate procedures. If the user finds the same procedure over concurrent days, it is assumed those records are part of a procedure lasting more than a day. This logic is in lieu of the procedure_end_date, which will be added in a future version of the CDM. If a procedure lasts more than 24 hours, then it should be recorded as a separate record for each day the procedure occurred, this logic is in lieu of the PROCEDURE_END_DATE, which will be added in a future version of the CDM. When dealing with duplicate records, the ETL must determine whether to sum them up into one record or keep them separate. Things to consider are: - Same Procedure - Same PROCEDURE_DATETIME - Same Visit Occurrence or Visit Detail - Same Provider - Same Modifier for Procedures. Source codes and source text fields mapped to Standard Concepts of the Procedure Domain have to be recorded here.
9 device_exposure CDM No DEVICE_ Yes 0 NA The Device domain captures information about a person's exposure to a foreign physical object or instrument which is used for diagnostic or therapeutic purposes through a mechanism beyond chemical action. Devices include implantable objects (e.g. pacemakers, stents, artificial joints), medical equipment and supplies (e.g. bandages, crutches, syringes), other instruments used in medical procedures (e.g. sutures, defibrillators) and material used in clinical care (e.g. adhesives, body material, dental material, surgical material). The distinction between Devices or supplies and Procedures are sometimes blurry, but the former are physical objects while the latter are actions, often to apply a Device or supply. Source codes and source text fields mapped to Standard Concepts of the Device Domain have to be recorded here.
10 measurement CDM No MEASUREMENT_ Yes 0 NA The MEASUREMENT table contains records of Measurements, i.e. structured values (numerical or categorical) obtained through systematic and standardized examination or testing of a Person or Person's sample. The MEASUREMENT table contains both orders and results of such Measurements as laboratory tests, vital signs, quantitative findings from pathology reports, etc. Measurements are stored as attribute value pairs, with the attribute as the Measurement Concept and the value representing the result. The value can be a Concept (stored in VALUE_AS_CONCEPT), or a numerical value (VALUE_AS_NUMBER) with a Unit (UNIT_CONCEPT_ID). The Procedure for obtaining the sample is housed in the PROCEDURE_OCCURRENCE table, though it is unnecessary to create a PROCEDURE_OCCURRENCE record for each measurement if one does not exist in the source data. Measurements differ from Observations in that they require a standardized test or some other activity to generate a quantitative or qualitative result. If there is no result, it is assumed that the lab test was conducted but the result was not captured. Measurements are predominately lab tests with a few exceptions, like blood pressure or function tests. Results are given in the form of a value and unit combination. When investigating measurements, look for operator_concept_ids (<, >, etc.). Only records where the source value maps to a Concept in the measurement domain should be included in this table. Even though each Measurement always has a result, the fields VALUE_AS_NUMBER and VALUE_AS_CONCEPT_ID are not mandatory as often the result is not given in the source data. When the result is not known, the Measurement record represents just the fact that the corresponding Measurement was carried out, which in itself is already useful information for some use cases. For some Measurement Concepts, the result is included in the test. For example, ICD10 CONCEPT_ID [45548980](https://athena.ohdsi.org/search-terms/terms/45548980) 'Abnormal level of unspecified serum enzyme' indicates a Measurement and the result (abnormal). In those situations, the CONCEPT_RELATIONSHIP table in addition to the 'Maps to' record contains a second record with the relationship_id set to 'Maps to value'. In this example, the 'Maps to' relationship directs to [4046263](https://athena.ohdsi.org/search-terms/terms/4046263) 'Enzyme measurement' as well as a 'Maps to value' record to [4135493](https://athena.ohdsi.org/search-terms/terms/4135493) 'Abnormal'.
11 observation CDM No OBSERVATION_ Yes 0 NA The OBSERVATION table captures clinical facts about a Person obtained in the context of examination, questioning or a procedure. Any data that cannot be represented by any other domains, such as social and lifestyle facts, medical history, family history, etc. are recorded here. Observations differ from Measurements in that they do not require a standardized test or some other activity to generate clinical fact. Typical observations are medical history, family history, the stated need for certain treatment, social circumstances, lifestyle choices, healthcare utilization patterns, etc. If the generation clinical facts requires a standardized testing such as lab testing or imaging and leads to a standardized result, the data item is recorded in the MEASUREMENT table. If the clinical fact observed determines a sign, symptom, diagnosis of a disease or other medical condition, it is recorded in the CONDITION_OCCURRENCE table. Valid Observation Concepts are not enforced to be from any domain but they must not belong to the Condition, Procedure, Drug, Device, Specimen, or Measurement domains and they must be Standard Concepts. <br><br>The observation table usually records the date or datetime of when the observation was obtained, not the date of the observation starting. For example, if the patient reports that they had a heart attack when they were 50, the observation date or datetime is the date of the report, the heart attack observation can have a value_as_concept which captures how long ago the observation applied to the patient. Records whose Source Values map to any domain besides Condition, Procedure, Drug, Specimen, Measurement or Device should be stored in the Observation table. Observations can be stored as attribute value pairs, with the attribute as the Observation Concept and the value representing the clinical fact. This fact can be a Concept (stored in VALUE_AS_CONCEPT), a numerical value (VALUE_AS_NUMBER), a verbatim string (VALUE_AS_STRING), or a datetime (VALUE_AS_DATETIME). Even though Observations do not have an explicit result, the clinical fact can be stated separately from the type of Observation in the VALUE_AS_* fields. It is recommended for Observations that are suggestive statements of positive assertion should have a value of 'Yes' (concept_id=4188539), recorded, even though the null value is the equivalent. Records whose Source Values map to any domain besides Condition, Procedure, Drug, Specimen, Measurement or Device should be stored in the Observation table. Observations can be stored as attribute value pairs, with the attribute as the Observation Concept and the value representing the clinical fact. This fact can be a Concept (stored in VALUE_AS_CONCEPT), a numerical value (VALUE_AS_NUMBER) or a verbatim string (VALUE_AS_STRING). Even though Observations do not have an explicit result, the clinical fact can be stated separately from the type of Observation in the VALUE_AS_* fields. It is recommended for Observations that are suggestive statements of positive assertion should have a value of 'Yes' (concept_id=4188539), recorded, even though the null value is the equivalent.
12 death CDM No NA No NA NA The death domain contains the clinical event for how and when a Person dies. A person can have up to one record if the source system contains evidence about the Death, such as: Condition in an administrative claim, status of enrollment into a health plan, or explicit record in EHR data. NA For specific conventions on how to populate this table, please refer to the [THEMIS repository](https://ohdsi.github.io/Themis/death.html).
13 note CDM No NA Yes 0 NA The NOTE table captures unstructured information that was recorded by a provider about a patient in free text (in ASCII, or preferably in UTF8 format) notes on a given date. The type of note_text is CLOB or varchar(MAX) depending on RDBMS. NA HL7/LOINC CDO is a standard for consistent naming of documents to support a range of use cases: retrieval, organization, display, and exchange. It guides the creation of LOINC codes for clinical notes. CDO annotates each document with 5 dimensions: - **Kind of Document**: Characterizes the general structure of the document at a macro level (e.g. Anesthesia Consent) - **Type of Service**: Characterizes the kind of service or activity (e.g. evaluations, consultations, and summaries). The notion of time sequence, e.g., at the beginning (admission) at the end (discharge) is subsumed in this axis. Example: Discharge Teaching. - **Setting**: Setting is an extension of CMS's definitions (e.g. Inpatient, Outpatient) - **Subject Matter Domain (SMD)**: Characterizes the subject matter domain of a note (e.g. Anesthesiology) - **Role**: Characterizes the training or professional level of the author of the document, but does not break down to specialty or subspecialty (e.g. Physician) Each combination of these 5 dimensions rolls up to a unique LOINC code. According to CDO requirements, only 2 of the 5 dimensions are required to properly annotate a document; Kind of Document and any one of the other 4 dimensions. However, not all the permutations of the CDO dimensions will necessarily yield an existing LOINC code. Each of these dimensions are contained in the OMOP Vocabulary under the domain of 'Meas Value' with each dimension represented as a Concept Class.
14 note_nlp CDM No NA No NA NA The NOTE_NLP table encodes all output of NLP on clinical notes. Each row represents a single extracted term from a note. NA NA
15 specimen CDM No SPECIMEN_ Yes 0 NA The specimen domain contains the records identifying biological samples from a person. NA Anatomic site is coded at the most specific level of granularity possible, such that higher level classifications can be derived using the Standardized Vocabularies.
16 fact_relationship CDM No NA No NA NA The FACT_RELATIONSHIP table contains records about the relationships between facts stored as records in any table of the CDM. Relationships can be defined between facts from the same domain, or different domains. Examples of Fact Relationships include: [Person relationships](https://athena.ohdsi.org/search-terms/terms?domain=Relationship&standardConcept=Standard&page=2&pageSize=15&query=) (parent-child), care site relationships (hierarchical organizational structure of facilities within a health system), indication relationship (between drug exposures and associated conditions), usage relationships (of devices during the course of an associated procedure), or facts derived from one another (measurements derived from an associated specimen). NA All relationships are directional, and each relationship is represented twice symmetrically within the FACT_RELATIONSHIP table. For example, two persons if person_id = 1 is the mother of person_id = 2 two records are in the FACT_RELATIONSHIP table (all strings in fact concept_id records in the Concept table: - Person, 1, Person, 2, parent of - Person, 2, Person, 1, child of
17 location CDM No NA No NA NA The LOCATION table represents a generic way to capture physical location or address information of Persons and Care Sites. NA Each address or Location is unique and is present only once in the table. Locations do not contain names, such as the name of a hospital. In order to construct a full address that can be used in the postal service, the address information from the Location needs to be combined with information from the Care Site.
18 care_site CDM No NA No NA NA The CARE_SITE table contains a list of uniquely identified institutional (physical or organizational) units where healthcare delivery is practiced (offices, wards, hospitals, clinics, etc.). NA Care site is a unique combination of location_id and nature of the site - the latter could be the place of service, name, or another characteristic in your source data. Care site does not take into account the provider (human) information such a specialty. Many source data do not make a distinction between individual and institutional providers. The CARE_SITE table contains the institutional providers. If the source, instead of uniquely identifying individual Care Sites, only provides limited information such as Place of Service, generic or "pooled" Care Site records are listed in the CARE_SITE table. There can be hierarchical and business relationships between Care Sites. For example, wards can belong to clinics or departments, which can in turn belong to hospitals, which in turn can belong to hospital systems, which in turn can belong to HMOs.The relationships between Care Sites are defined in the FACT_RELATIONSHIP table.<br><br>For additional detailed conventions on how to populate this table, please refer to [THEMIS repository](https://ohdsi.github.io/Themis/care_site.html).
19 provider CDM No NA No NA NA The PROVIDER table contains a list of uniquely identified healthcare providers; duplication is not allowed. These are individuals providing hands-on healthcare to patients, such as physicians, nurses, midwives, physical therapists etc. Many sources do not make a distinction between individual and institutional providers. The PROVIDER table contains the individual providers. If the source only provides limited information such as specialty instead of uniquely identifying individual providers, generic or 'pooled' Provider records are listed in the PROVIDER table. NA
20 payer_plan_period CDM No NA Yes 0 NA The PAYER_PLAN_PERIOD table captures details of the period of time that a Person is continuously enrolled under a specific health Plan benefit structure from a given Payer. Each Person receiving healthcare is typically covered by a health benefit plan, which pays for (fully or partially), or directly provides, the care. These benefit plans are provided by payers, such as health insurances or state or government agencies. In each plan the details of the health benefits are defined for the Person or her family, and the health benefit Plan might change over time typically with increasing utilization (reaching certain cost thresholds such as deductibles), plan availability and purchasing choices of the Person. The unique combinations of Payer organizations, health benefit Plans and time periods in which they are valid for a Person are recorded in this table. A Person can have multiple, overlapping, Payer_Plan_Periods in this table. For example, medical and drug coverage in the US can be represented by two Payer_Plan_Periods. The details of the benefit structure of the Plan is rarely known, the idea is just to identify that the Plans are different. NA
22 drug_era CDM No NA Yes 0 NA A Drug Era is defined as a span of time when the Person is assumed to be exposed to a particular active ingredient. A Drug Era is not the same as a Drug Exposure: Exposures are individual records corresponding to the source when Drug was delivered to the Person, while successive periods of Drug Exposures are combined under certain rules to produce continuous Drug Eras. Every record in the DRUG_EXPOSURE table should be part of a drug era based on the dates of exposure. NA The SQL script for generating DRUG_ERA records can be found [here](https://ohdsi.github.io/CommonDataModel/sqlScripts.html#drug_eras).
23 dose_era CDM No NA Yes 0 NA A Dose Era is defined as a span of time when the Person is assumed to be exposed to a constant dose of a specific active ingredient. NA Dose Eras will be derived from records in the DRUG_EXPOSURE table and the Dose information from the DRUG_STRENGTH table using a standardized algorithm. Dose Form information is not taken into account. So, if the patient changes between different formulations, or different manufacturers with the same formulation, the Dose Era is still spanning the entire time of exposure to the Ingredient.
24 condition_era CDM No NA Yes 0 NA A Condition Era is defined as a span of time when the Person is assumed to have a given condition. Similar to Drug Eras, Condition Eras are chronological periods of Condition Occurrence and every Condition Occurrence record should be part of a Condition Era. Combining individual Condition Occurrences into a single Condition Era serves two purposes: - It allows aggregation of chronic conditions that require frequent ongoing care, instead of treating each Condition Occurrence as an independent event. - It allows aggregation of multiple, closely timed doctor visits for the same Condition to avoid double-counting the Condition Occurrences. For example, consider a Person who visits her Primary Care Physician (PCP) and who is referred to a specialist. At a later time, the Person visits the specialist, who confirms the PCP's original diagnosis and provides the appropriate treatment to resolve the condition. These two independent doctor visits should be aggregated into one Condition Era. NA Each Condition Era corresponds to one or many Condition Occurrence records that form a continuous interval. The condition_concept_id field contains Concepts that are identical to those of the CONDITION_OCCURRENCE table records that make up the Condition Era. In contrast to Drug Eras, Condition Eras are not aggregated to contain Conditions of different hierarchical layers. The SQl Script for generating CONDITION_ERA records can be found [here](https://ohdsi.github.io/CommonDataModel/sqlScripts.html#condition_eras) The Condition Era Start Date is the start date of the first Condition Occurrence. The Condition Era End Date is the end date of the last Condition Occurrence. Condition Eras are built with a Persistence Window of 30 days, meaning, if no occurrence of the same condition_concept_id happens within 30 days of any one occurrence, it will be considered the condition_era_end_date.
25 metadata CDM No NA No NA NA The METADATA table contains metadata information about a dataset that has been transformed to the OMOP Common Data Model. NA NA
26 cdm_source CDM No NA No NA NA The CDM_SOURCE table contains detail about the source database and the process used to transform the data into the OMOP Common Data Model. NA NA
27 concept VOCAB No NA No NA NA The Standardized Vocabularies contains records, or Concepts, that uniquely identify each fundamental unit of meaning used to express clinical information in all domain tables of the CDM. Concepts are derived from vocabularies, which represent clinical information across a domain (e.g. conditions, drugs, procedures) through the use of codes and associated descriptions. Some Concepts are designated Standard Concepts, meaning these Concepts can be used as normative expressions of a clinical entity within the OMOP Common Data Model and standardized analytics. Each Standard Concept belongs to one Domain, which defines the location where the Concept would be expected to occur within the data tables of the CDM. Concepts can represent broad categories ('Cardiovascular disease'), detailed clinical elements ('Myocardial infarction of the anterolateral wall'), or modifying characteristics and attributes that define Concepts at various levels of detail (severity of a disease, associated morphology, etc.). Records in the Standardized Vocabularies tables are derived from national or international vocabularies such as SNOMED-CT, RxNorm, and LOINC, or custom OMOP Concepts defined to cover various aspects of observational data analysis. The primary purpose of the CONCEPT table is to provide a standardized representation of medical Concepts, allowing for consistent querying and analysis across the healthcare databases. Users can join the CONCEPT table with other tables in the CDM to enrich clinical data with standardized Concept information or use the CONCEPT table as a reference for mapping clinical data from source terminologies to Standard Concepts. NA
28 vocabulary VOCAB No NA No NA NA The VOCABULARY table includes a list of the Vocabularies integrated from various sources or created de novo in OMOP CDM. This reference table contains a single record for each Vocabulary and includes a descriptive name and other associated attributes for the Vocabulary. The primary purpose of the VOCABULARY table is to provide explicit information about specific vocabulary versions and the references to the sources from which they are asserted. Users can identify the version of a particular vocabulary used in the database, enabling consistency and reproducibility in data analysis. Besides, users can check the vocabulary release version in their CDM which refers to the vocabulary_id = 'None'. NA
29 domain VOCAB No NA No NA NA The DOMAIN table includes a list of OMOP-defined Domains to which the Concepts of the Standardized Vocabularies can belong. A Domain represents a clinical definition whereby we assign matching Concepts for the standardized fields in the CDM tables. For example, the Condition Domain contains Concepts that describe a patient condition, and these Concepts can only be used in the condition_concept_id field of the CONDITION_OCCURRENCE and CONDITION_ERA tables. This reference table is populated with a single record for each Domain, including a Domain ID and a descriptive name for every Domain. Users can leverage the DOMAIN table to explore the full spectrum of health-related data Domains available in the Standardized Vocabularies. Also, the information in the DOMAIN table may be used as a reference for mapping source data to OMOP domains, facilitating data harmonization and interoperability. NA
30 concept_class VOCAB No NA No NA NA The CONCEPT_CLASS table includes semantic categories that reference the source structure of each Vocabulary. Concept Classes represent so-called horizontal (e.g. MedDRA, RxNorm) or vertical levels (e.g. SNOMED) of the vocabulary structure. Vocabularies without any Concept Classes, such as HCPCS, use the vocabulary_id as the Concept Class. This reference table is populated with a single record for each Concept Class, which includes a Concept Class ID and a fully specified Concept Class name. Users can utilize the CONCEPT_CLASS table to explore the different classes or categories of concepts within the OHDSI vocabularies. NA
31 concept_relationship VOCAB No NA No NA NA The CONCEPT_RELATIONSHIP table contains records that define relationships between any two Concepts and the nature or type of the relationship. This table captures various types of relationships, including hierarchical, associative, and other semantic connections, enabling comprehensive analysis and interpretation of clinical concepts. Every kind of relationship is defined in the RELATIONSHIP table. The CONCEPT_RELATIONSHIP table can be used to explore hierarchical or attribute relationships between concepts to understand the hierarchical structure of clinical concepts and uncover implicit connections and associations within healthcare data. For example, users can utilize mapping relationships ('Maps to') to harmonize data from different sources and terminologies, enabling interoperability and data integration across disparate datasets. NA
32 relationship VOCAB No NA No NA NA The RELATIONSHIP table provides a reference list of all types of relationships that can be used to associate any two concepts in the CONCEPT_RELATIONSHP table. NA NA
33 concept_synonym VOCAB No NA No NA NA The CONCEPT_SYNONYM table is used to store alternate names and descriptions for Concepts. NA NA
34 concept_ancestor VOCAB No NA No NA NA The CONCEPT_ANCESTOR table is designed to simplify observational analysis by providing the complete hierarchical relationships between Concepts. Only direct parent-child relationships between Concepts are stored in the CONCEPT_RELATIONSHIP table. To determine higher level ancestry connections, all individual direct relationships would have to be navigated at analysis time. The CONCEPT_ANCESTOR table includes records for all parent-child relationships, as well as grandparent-grandchild relationships and those of any other level of lineage. Using the CONCEPT_ANCESTOR table allows for querying for all descendants of a hierarchical concept. For example, drug ingredients and drug products are all descendants of a drug class ancestor. This table is entirely derived from the CONCEPT, CONCEPT_RELATIONSHIP and RELATIONSHIP tables. NA NA
35 source_to_concept_map VOCAB No NA No NA NA The source to concept map table is a legacy data structure within the OMOP Common Data Model, recommended for use in ETL processes to maintain local source codes which are not available as Concepts in the Standardized Vocabularies, and to establish mappings for each source code into a Standard Concept as target_concept_ids that can be used to populate the Common Data Model tables. The SOURCE_TO_CONCEPT_MAP table is no longer populated with content within the Standardized Vocabularies published to the OMOP community. NA NA
36 drug_strength VOCAB No NA No NA NA The DRUG_STRENGTH table contains structured content about the amount or concentration and associated units of a specific ingredient contained within a particular drug product. This table is supplemental information to support standardized analysis of drug utilization. NA NA
37 cohort_definition VOCAB No NA No NA NA The COHORT_DEFINITION table contains records defining a Cohort derived from the data through the associated description and syntax and upon instantiation (execution of the algorithm) placed into the COHORT table. Cohorts are a set of subjects that satisfy a given combination of inclusion criteria for a duration of time. The COHORT_DEFINITION table provides a standardized structure for maintaining the rules governing the inclusion of a subject into a cohort, and can store operational programming code to instantiate the cohort within the OMOP Common Data Model. NA NA
38 attribute_definition VOCAB No NA No NA NA The ATTRIBUTE_DEFINITION table contains records to define each attribute through an associated description and syntax. Attributes are derived elements that can be selected or calculated for a subject within a cohort. The ATTRIBUTE_DEFINITION table provides a standardized structure for maintaining the rules governing the calculation of covariates for a subject in a cohort, and can store operational programming code to instantiate the attributes for a given cohort within the OMOP Common Data Model. NA NA
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cdmTableName,cdmFieldName,isRequired,cdmDatatype,userGuidance,etlConventions,isPrimaryKey,isForeignKey,fkTableName,fkFieldName,fkDomain,fkClass,unique DQ identifiers
person,person_id,Yes,integer,It is assumed that every person with a different unique identifier is in fact a different person and should be treated independently.,"Any person linkage that needs to occur to uniquely identify Persons ought to be done prior to writing this table. This identifier can be the original id from the source data provided if it is an integer, otherwise it can be an autogenerated number.",Yes,No,NA,NA,NA,NA,NA
person,gender_concept_id,Yes,integer,This field is meant to capture the biological sex at birth of the Person. This field should not be used to study gender identity issues.,Use the gender or sex value present in the data under the assumption that it is the biological sex at birth. If the source data captures gender identity it should be stored in the [OBSERVATION](https://ohdsi.github.io/CommonDataModel/cdm531.html#observation) table. [Accepted gender concepts](http://athena.ohdsi.org/search-terms/terms?domain=Gender&standardConcept=Standard&page=1&pageSize=15&query=). Please refer to the [THEMIS repository](https://ohdsi.github.io/Themis/tag_gender_concept_id.html) for detailed conventions on how to populate this field.,No,Yes,CONCEPT,CONCEPT_ID,Gender,NA,NA
person,gender_concept_id,Yes,integer,This field is meant to capture the biological sex at birth of the Person. This field should not be used to study gender identity issues.,Use the gender or sex value present in the data under the assumption that it is the biological sex at birth. If the source data captures gender identity it should be stored in the [OBSERVATION](https://ohdsi.github.io/CommonDataModel/cdm54.html#observation) table. [Accepted gender concepts](http://athena.ohdsi.org/search-terms/terms?domain=Gender&standardConcept=Standard&page=1&pageSize=15&query=). Please refer to the [THEMIS repository](https://ohdsi.github.io/Themis/tag_gender_concept_id.html) for detailed conventions on how to populate this field.,No,Yes,CONCEPT,CONCEPT_ID,Gender,NA,NA
person,year_of_birth,Yes,integer,Compute age using year_of_birth.,"For data sources with date of birth, the year should be extracted. If no year of birth is available all the person's data should be dropped from the CDM instance. For additional information on how to populate this field, please refer to the [THEMIS repository](https://ohdsi.github.io/Themis/tag_year_of_birth.html).",No,No,NA,NA,NA,NA,NA
person,month_of_birth,No,integer,NA,"For data sources that provide the precise date of birth, the month should be extracted and stored in this field.",No,No,NA,NA,NA,NA,NA
person,day_of_birth,No,integer,NA,"For data sources that provide the precise date of birth, the day should be extracted and stored in this field.",No,No,NA,NA,NA,NA,NA
person,birth_datetime,No,datetime,NA,"This field is not required but highly encouraged. For data sources that provide the precise datetime of birth, that value should be stored in this field. For more information on how to populate this field, please refer to the [THEMIS repository](https://ohdsi.github.io/Themis/person.html).",No,No,NA,NA,NA,NA,NA
person,race_concept_id,Yes,integer,This field captures race or ethnic background of the person.,"Only use this field if you have information about race or ethnic background. The Vocabulary contains Concepts about the main races and ethnic backgrounds in a hierarchical system. Due to the imprecise nature of human races and ethnic backgrounds, this is not a perfect system. Mixed races are not supported. If a clear race or ethnic background cannot be established, use Concept_Id 0. [Accepted Race Concepts](http://athena.ohdsi.org/search-terms/terms?domain=Race&standardConcept=Standard&page=1&pageSize=15&query=).",No,Yes,CONCEPT,CONCEPT_ID,Race,NA,NA
person,ethnicity_concept_id,Yes,integer,"This field captures Ethnicity as defined by the Office of Management and Budget (OMB) of the US Government: it distinguishes only between ""Hispanic"" and ""Not Hispanic"". Races and ethnic backgrounds are not stored here.",Only use this field if you have US-based data and a source of this information. Do not attempt to infer Ethnicity from the race or ethnic background of the Person. [Accepted ethnicity concepts](http://athena.ohdsi.org/search-terms/terms?domain=Ethnicity&standardConcept=Standard&page=1&pageSize=15&query=),No,Yes,CONCEPT,CONCEPT_ID,Ethnicity,NA,NA
person,location_id,No,integer,The location refers to the physical address of the person. This field should capture the last known location of the person.,"Put the location_id from the [LOCATION](https://ohdsi.github.io/CommonDataModel/cdm531.html#location) table here that represents the most granular location information for the person. For additional information on how to populate this field, please refer to the [THEMIS repository](https://ohdsi.github.io/Themis/populate_person_location_id.html).",No,Yes,LOCATION,LOCATION_ID,NA,NA,NA
person,provider_id,No,integer,The Provider refers to the last known primary care provider (General Practitioner).,"Put the provider_id from the [PROVIDER](https://ohdsi.github.io/CommonDataModel/cdm531.html#provider) table of the last known general practitioner of the person. If there are multiple providers, it is up to the ETL to decide which to put here.",No,Yes,PROVIDER,PROVIDER_ID,NA,NA,NA
person,location_id,No,integer,The location refers to the physical address of the person. This field should capture the last known location of the person.,"Put the location_id from the [LOCATION](https://ohdsi.github.io/CommonDataModel/cdm54.html#location) table here that represents the most granular location information for the person. For additional information on how to populate this field, please refer to the [THEMIS repository](https://ohdsi.github.io/Themis/populate_person_location_id.html).",No,Yes,LOCATION,LOCATION_ID,NA,NA,NA
person,provider_id,No,integer,The Provider refers to the last known primary care provider (General Practitioner).,"Put the provider_id from the [PROVIDER](https://ohdsi.github.io/CommonDataModel/cdm54.html#provider) table of the last known general practitioner of the person. If there are multiple providers, it is up to the ETL to decide which to put here.",No,Yes,PROVIDER,PROVIDER_ID,NA,NA,NA
person,care_site_id,No,integer,The Care Site refers to where the Provider typically provides the primary care.,NA,No,Yes,CARE_SITE,CARE_SITE_ID,NA,NA,NA
person,person_source_value,No,varchar(50),Use this field to link back to persons in the source data. This is typically used for error checking of ETL logic.,Some use cases require the ability to link back to persons in the source data. This field allows for the storing of the person value as it appears in the source. This field is not required but strongly recommended.,No,No,NA,NA,NA,NA,NA
person,gender_source_value,No,varchar(50),This field is used to store the biological sex of the person from the source data. It is not intended for use in standard analytics but for reference only.,Put the assigned sex at birth of the person as it appears in the source data.,No,No,NA,NA,NA,NA,NA
person,gender_source_concept_id,No,integer,"Due to the small number of options, this tends to be zero.","If the source data codes asigned sex at birth in a non-standard vocabulary, store the concept_id here.",No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
person,gender_source_concept_id,No,integer,"Due to the small number of options, this tends to be zero.","If the source data codes assigned sex at birth in a non-standard vocabulary, store the concept_id here.",No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
person,race_source_value,No,varchar(50),This field is used to store the race of the person from the source data. It is not intended for use in standard analytics but for reference only.,Put the race of the person as it appears in the source data.,No,No,NA,NA,NA,NA,NA
person,race_source_concept_id,No,integer,"Due to the small number of options, this tends to be zero.",If the source data codes race in an OMOP supported vocabulary store the concept_id here.,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
person,ethnicity_source_value,No,varchar(50),This field is used to store the ethnicity of the person from the source data. It is not intended for use in standard analytics but for reference only.,"If the person has an ethnicity other than the OMB standard of ""Hispanic"" or ""Not Hispanic"" store that value from the source data here.",No,No,NA,NA,NA,NA,NA
person,ethnicity_source_concept_id,No,integer,"Due to the small number of options, this tends to be zero.","If the source data codes ethnicity in an OMOP supported vocabulary, store the concept_id here.",No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
observation_period,observation_period_id,Yes,integer,A Person can have multiple discrete Observation Periods which are identified by the Observation_Period_Id.,Assign a unique observation_period_id to each discrete Observation Period for a Person.,Yes,No,NA,NA,NA,NA,NA
observation_period,person_id,Yes,integer,The Person ID of the PERSON record for which the Observation Period is recorded.,NA,No,Yes,PERSON,PERSON_ID,NA,NA,NA
observation_period,observation_period_start_date,Yes,date,Use this date to determine the start date of the Observation Period.,"It is often the case that the idea of Observation Periods does not exist in source data. In those cases, the observation_period_start_date can be inferred as the earliest Event date available for the Person. In insurance claim data, the Observation Period can be considered as the time period the Person is enrolled with a payer. If a Person switches plans but stays with the same payer, and therefore capturing of data continues, that change would be captured in [PAYER_PLAN_PERIOD](https://ohdsi.github.io/CommonDataModel/cdm531.html#payer_plan_period).",No,No,NA,NA,NA,NA,NA
observation_period,observation_period_start_date,Yes,date,Use this date to determine the start date of the Observation Period.,"It is often the case that the idea of Observation Periods does not exist in source data. In those cases, the observation_period_start_date can be inferred as the earliest Event date available for the Person. In insurance claim data, the Observation Period can be considered as the time period the Person is enrolled with a payer. If a Person switches plans but stays with the same payer, and therefore capturing of data continues, that change would be captured in [PAYER_PLAN_PERIOD](https://ohdsi.github.io/CommonDataModel/cdm54.html#payer_plan_period).",No,No,NA,NA,NA,NA,NA
observation_period,observation_period_end_date,Yes,date,Use this date to determine the end date of the period for which we can assume that all events for a Person are recorded.,"It is often the case that the idea of Observation Periods does not exist in source data. In those cases, the observation_period_end_date can be inferred as the last Event date available for the Person. In insurance claim data, the Observation Period can be considered as the time period the Person is enrolled with a payer.",No,No,NA,NA,NA,NA,NA
observation_period,period_type_concept_id,Yes,integer,"This field can be used to determine the provenance of the Observation Period as in whether the period was determined from an insurance enrollment file, EHR healthcare encounters, or other sources.",Choose the observation_period_type_concept_id that best represents how the period was determined. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Type+Concept&standardConcept=Standard&page=1&pageSize=15&query=). A more detailed explanation of each Type Concept can be found on the [vocabulary wiki](https://github.com/OHDSI/Vocabulary-v5.0/wiki/Vocab.-TYPE_CONCEPT).,No,Yes,CONCEPT,CONCEPT_ID,Type Concept,NA,NA
visit_occurrence,visit_occurrence_id,Yes,integer,Use this to identify unique interactions between a person and the health care system. This identifier links across the other CDM event tables to associate events with a visit.,This should be populated by creating a unique identifier for each unique interaction between a person and the healthcare system where the person receives a medical good or service over a span of time.,Yes,No,NA,NA,NA,NA,NA
@ -36,7 +36,7 @@ For Inpatient Visits ongoing at the date of ETL, put date of processing the data
- All other Visits: visit_end_datetime = visit_start_datetime. If this is a one-day visit the end date should match the start date.",No,No,NA,NA,NA,NA,NA
visit_occurrence,visit_end_datetime,No,datetime,"If a Person is still an inpatient in the hospital at the time of the data extract and does not have a visit_end_datetime, then set the visit_end_datetime to the datetime of the data pull.","If no time is given for the end date of a visit, set it to midnight (00:00:0000).",No,No,NA,NA,NA,NA,NA
visit_occurrence,visit_type_concept_id,Yes,Integer,"Use this field to understand the provenance of the visit record, or where the record comes from.","Populate this field based on the provenance of the visit record, as in whether it came from an EHR record or billing claim. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Type+Concept&standardConcept=Standard&page=1&pageSize=15&query=). A more detailed explanation of each Type Concept can be found on the [vocabulary wiki](https://github.com/OHDSI/Vocabulary-v5.0/wiki/Vocab.-TYPE_CONCEPT).",No,Yes,CONCEPT,CONCEPT_ID,Type Concept,NA,NA
visit_occurrence,provider_id,No,integer,"There will only be one provider per visit record and the ETL document should clearly state how they were chosen (attending, admitting, etc.). If there are multiple providers associated with a visit in the source, this can be reflected in the event tables (CONDITION_OCCURRENCE, PROCEDURE_OCCURRENCE, etc.) or in the VISIT_DETAIL table.","If there are multiple providers associated with a visit, you will need to choose which one to put here. The additional providers can be stored in the [VISIT_DETAIL](https://ohdsi.github.io/CommonDataModel/cdm531.html#visit_detail) table.",No,Yes,PROVIDER,PROVIDER_ID,NA,NA,NA
visit_occurrence,provider_id,No,integer,"There will only be one provider per visit record and the ETL document should clearly state how they were chosen (attending, admitting, etc.). If there are multiple providers associated with a visit in the source, this can be reflected in the event tables (CONDITION_OCCURRENCE, PROCEDURE_OCCURRENCE, etc.) or in the VISIT_DETAIL table.","If there are multiple providers associated with a visit, you will need to choose which one to put here. The additional providers can be stored in the [VISIT_DETAIL](https://ohdsi.github.io/CommonDataModel/cdm54.html#visit_detail) table.",No,Yes,PROVIDER,PROVIDER_ID,NA,NA,NA
visit_occurrence,care_site_id,No,integer,This field provides information about the Care Site where the Visit took place.,There should only be one Care Site associated with a Visit.,No,Yes,CARE_SITE,CARE_SITE_ID,NA,NA,NA
visit_occurrence,visit_source_value,No,varchar(50),"This field houses the verbatim value from the source data representing the kind of visit that took place (inpatient, outpatient, emergency, etc.)","If there is information about the kind of visit in the source data that value should be stored here. If a visit is an amalgamation of visits from the source then use a hierarchy to choose the visit source value, such as IP -> ER-> OP. This should line up with the logic chosen to determine how visits are created.",No,No,NA,NA,NA,NA,NA
visit_occurrence,visit_source_concept_id,No,integer,NA,If the visit source value is coded in the source data using an OMOP supported vocabulary put the concept id representing the source value here.,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
@ -62,8 +62,8 @@ visit_detail,visit_detail_type_concept_id,Yes,integer,"Use this field to underst
visit_detail,provider_id,No,integer,"There will only be one provider per **visit** record and the ETL document should clearly state how they were chosen (attending, admitting, etc.). This is a typical reason for leveraging the VISIT_DETAIL table as even though each VISIT_DETAIL record can only have one provider, there is no limit to the number of VISIT_DETAIL records that can be associated to a VISIT_OCCURRENCE record.",The additional providers associated to a Visit can be stored in this table where each VISIT_DETAIL record represents a different provider.,No,Yes,PROVIDER,PROVIDER_ID,NA,NA,NA
visit_detail,care_site_id,No,integer,This field provides information about the Care Site where the Visit Detail took place.,There should only be one Care Site associated with a Visit Detail.,No,Yes,CARE_SITE,CARE_SITE_ID,NA,NA,NA
visit_detail,visit_detail_source_value,No,varchar(50),"This field houses the verbatim value from the source data representing the kind of visit detail that took place (inpatient, outpatient, emergency, etc.)","If there is information about the kind of visit detail in the source data that value should be stored here. If a visit is an amalgamation of visits from the source then use a hierarchy to choose the VISIT_DETAIL_SOURCE_VALUE, such as IP -> ER-> OP. This should line up with the logic chosen to determine how visits are created.",No,No,NA,NA,NA,NA,NA
visit_detail,visit_detail_source_concept_id,No,Integer,NA,If the VISIT_DETAIL_SOURCE_VALUE is coded in the source data using an OMOP supported vocabulary put the concept id representing the source value here.,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
visit_detail,admitted_from_concept_id,No,Integer,"Use this field to determine where the patient was admitted from. This concept is part of the visit domain and can indicate if a patient was admitted to the hospital from a long-term care facility, for example.","If available, map the admitted_from_source_value to a standard concept in the visit domain. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Visit&standardConcept=Standard&page=1&pageSize=15&query=). If a person was admitted from home or was self-referred, set this to 0.",No,Yes,CONCEPT,CONCEPT_ID,Visit,NA,NA
visit_detail,visit_detail_source_concept_id,No,integer,NA,If the VISIT_DETAIL_SOURCE_VALUE is coded in the source data using an OMOP supported vocabulary put the concept id representing the source value here.,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
visit_detail,admitted_from_concept_id,No,integer,"Use this field to determine where the patient was admitted from. This concept is part of the visit domain and can indicate if a patient was admitted to the hospital from a long-term care facility, for example.","If available, map the admitted_from_source_value to a standard concept in the visit domain. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Visit&standardConcept=Standard&page=1&pageSize=15&query=). If a person was admitted from home or was self-referred, set this to 0.",No,Yes,CONCEPT,CONCEPT_ID,Visit,NA,NA
visit_detail,admitted_from_source_value,No,varchar(50),NA,"This information may be called something different in the source data but the field is meant to contain a value indicating where a person was admitted from. Typically this applies only to visits that have a length of stay, like inpatient visits or long-term care visits.",No,No,NA,NA,NA,NA,NA
visit_detail,discharged_to_source_value,No,varchar(50),NA,"This information may be called something different in the source data but the field is meant to contain a value indicating where a person was discharged to after a visit, as in they went home or were moved to long-term care. Typically this applies only to visits that have a length of stay of a day or more.",No,No,NA,NA,NA,NA,NA
visit_detail,discharged_to_concept_id,No,integer,"Use this field to determine where the patient was discharged to after a visit. This concept is part of the visit domain and can indicate if a patient was transferred to another hospital or sent to a long-term care facility, for example. It is assumed that a person is discharged to home therefore there is not a standard concept id for ""home"". Use concept id = 0 when a person is discharged to home.","If available, map the DISCHARGE_TO_SOURCE_VALUE to a Standard Concept in the Visit domain. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Visit&standardConcept=Standard&page=1&pageSize=15&query=).",No,Yes,CONCEPT,CONCEPT_ID,Visit,NA,NA
@ -88,10 +88,10 @@ condition_occurrence,condition_source_concept_id,No,integer,"This is the concept
condition_occurrence,condition_status_source_value,No,varchar(50),This field houses the verbatim value from the source data representing the condition status.,This information may be called something different in the source data but the field is meant to contain a value indicating when and how a diagnosis was given to a patient. This source value is mapped to a standard concept which is stored in the CONDITION_STATUS_CONCEPT_ID field.,No,No,NA,NA,NA,NA,NA
drug_exposure,drug_exposure_id,Yes,integer,The unique key given to records of drug dispensings or administrations for a person. Refer to the ETL for how duplicate drugs during the same visit were handled.,"Each instance of a drug dispensing or administration present in the source data should be assigned this unique key. In some cases, a person can have multiple records of the same drug within the same visit. It is valid to keep these duplicates and assign them individual, unique, DRUG_EXPOSURE_IDs, though it is up to the ETL how they should be handled.",Yes,No,NA,NA,NA,NA,NA
drug_exposure,person_id,Yes,integer,The PERSON_ID of the PERSON for whom the drug dispensing or administration is recorded. This may be a system generated code.,NA,No,Yes,PERSON,PERSON_ID,NA,NA,NA
drug_exposure,drug_concept_id,Yes,integer,"The DRUG_CONCEPT_ID field is recommended for primary use in analyses, and must be used for network studies. This is the standard concept mapped from the source concept id which represents a drug product or molecule otherwise introduced to the body. The drug concepts can have a varying degree of information about drug strength and dose. This information is relevant in the context of quantity and administration information in the subsequent fields plus strength information from the DRUG_STRENGTH table, provided as part of the standard vocabulary download.","The CONCEPT_ID that the DRUG_SOURCE_VALUE maps to. The concept id should be derived either from mapping from the source concept id or by picking the drug concept representing the most amount of detail you have. Records whose source values map to standard concepts with a domain of Drug should go in this table. When the Drug Source Value of the code cannot be translated into Standard Drug Concept IDs, a Drug exposure entry is stored with only the corresponding SOURCE_CONCEPT_ID and DRUG_SOURCE_VALUE and a DRUG_CONCEPT_ID of 0. The Drug Concept with the most detailed content of information is preferred during the mapping process. These are indicated in the CONCEPT_CLASS_ID field of the Concept and are recorded in the following order of precedence: ÒMarketed ProductÓ, ÒBranded PackÓ, ÒClinical PackÓ, ÒBranded DrugÓ, ÒClinical DrugÓ, ÒBranded Drug ComponentÓ, ÒClinical Drug ComponentÓ, ÒBranded Drug FormÓ, ÒClinical Drug FormÓ, and only if no other information is available ÒIngredientÓ. Note: If only the drug class is known, the DRUG_CONCEPT_ID field should contain 0. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Drug&standardConcept=Standard&page=1&pageSize=15&query=).",No,Yes,CONCEPT,CONCEPT_ID,Drug,NA,NA
drug_exposure,drug_concept_id,Yes,integer,"The DRUG_CONCEPT_ID field is recommended for primary use in analyses, and must be used for network studies. This is the standard concept mapped from the source concept id which represents a drug product or molecule otherwise introduced to the body. The drug concepts can have a varying degree of information about drug strength and dose. This information is relevant in the context of quantity and administration information in the subsequent fields plus strength information from the DRUG_STRENGTH table, provided as part of the standard vocabulary download.","The CONCEPT_ID that the DRUG_SOURCE_VALUE maps to. The concept id should be derived either from mapping from the source concept id or by picking the drug concept representing the most amount of detail you have. Records whose source values map to standard concepts with a domain of Drug should go in this table. When the Drug Source Value of the code cannot be translated into Standard Drug Concept IDs, a Drug exposure entry is stored with only the corresponding SOURCE_CONCEPT_ID and DRUG_SOURCE_VALUE and a DRUG_CONCEPT_ID of 0. The Drug Concept with the most detailed content of information is preferred during the mapping process. These are indicated in the CONCEPT_CLASS_ID field of the Concept and are recorded in the following order of precedence: Marketed Product, Branded Pack, Clinical Pack, Branded Drug, Clinical Drug, Branded Drug Component, Clinical Drug Component, Branded Drug Form, Clinical Drug Form, and only if no other information is available Ingredient. Note: If only the drug class is known, the DRUG_CONCEPT_ID field should contain 0. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Drug&standardConcept=Standard&page=1&pageSize=15&query=).",No,Yes,CONCEPT,CONCEPT_ID,Drug,NA,NA
drug_exposure,drug_exposure_start_date,Yes,date,Use this date to determine the start date of the drug record.,"Valid entries include a start date of a prescription, the date a prescription was filled, or the date on which a Drug administration was recorded. It is a valid ETL choice to use the date the drug was ordered as the DRUG_EXPOSURE_START_DATE.",No,No,NA,NA,NA,NA,NA
drug_exposure,drug_exposure_start_datetime,No,datetime,NA,"This is not required, though it is in v6. If a source does not specify datetime the convention is to set the time to midnight (00:00:0000)",No,No,NA,NA,NA,NA,NA
drug_exposure,drug_exposure_end_date,Yes,date,The DRUG_EXPOSURE_END_DATE denotes the day the drug exposure ended for the patient.,"If this information is not explicitly available in the data, infer the end date using the following methods:<br><br> 1. Start first with duration or days supply using the calculation drug start date + days supply -1 day. 2. Use quantity divided by daily dose that you may obtain from the sig or a source field (or assumed daily dose of 1) for solid, indivisibile, drug products. If quantity represents ingredient amount, quantity divided by daily dose * concentration (from drug_strength) drug concept id tells you the dose form. 3. If it is an administration record, set drug end date equal to drug start date. If the record is a written prescription then set end date to start date + 29. If the record is a mail-order prescription set end date to start date + 89. The end date must be equal to or greater than the start date. Ibuprofen 20mg/mL oral solution concept tells us this is oral solution. Calculate duration as quantity (200 example) * daily dose (5mL) /concentration (20mg/mL) 200*5/20 = 50 days. [Examples by dose form](https://ohdsi.github.io/CommonDataModel/drug_dose.html)<br><br>For detailed conventions for how to populate this field, please see the [THEMIS repository](https://ohdsi.github.io/Themis/tag_drug_exposure.html).",No,No,NA,NA,NA,NA,NA
drug_exposure,drug_exposure_end_date,Yes,date,The DRUG_EXPOSURE_END_DATE denotes the day the drug exposure ended for the patient.,"If this information is not explicitly available in the data, infer the end date from start date and duration.<br>For detailed conventions for how to populate this field, please see the [THEMIS repository](https://ohdsi.github.io/Themis/tag_drug_exposure.html).",No,No,NA,NA,NA,NA,NA
drug_exposure,drug_exposure_end_datetime,No,datetime,NA,"This is not required, though it is in v6. If a source does not specify datetime the convention is to set the time to midnight (00:00:0000)",No,No,NA,NA,NA,NA,NA
drug_exposure,verbatim_end_date,No,date,"This is the end date of the drug exposure as it appears in the source data, if it is given",Put the end date or discontinuation date as it appears from the source data or leave blank if unavailable.,No,No,NA,NA,NA,NA,NA
drug_exposure,drug_type_concept_id,Yes,integer,"You can use the TYPE_CONCEPT_ID to delineate between prescriptions written vs. prescriptions dispensed vs. medication history vs. patient-reported exposure, etc.","Choose the drug_type_concept_id that best represents the provenance of the record, for example whether it came from a record of a prescription written or physician administered drug. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Type+Concept&standardConcept=Standard&page=1&pageSize=15&query=). A more detailed explanation of each Type Concept can be found on the [vocabulary wiki](https://github.com/OHDSI/Vocabulary-v5.0/wiki/Vocab.-TYPE_CONCEPT).",No,Yes,CONCEPT,CONCEPT_ID,Type Concept,NA,NA
@ -102,7 +102,7 @@ Quantified clinical drugs with divisible dose forms (prefilled syringes), the qu
",No,No,NA,NA,NA,NA,NA
drug_exposure,days_supply,No,integer,NA,"The number of days of supply of the medication as recorded in the original prescription or dispensing record. Days supply can differ from actual drug duration (i.e. prescribed days supply vs actual exposure)."",""The field should be left empty if the source data does not contain a verbatim days_supply, and should not be calculated from other fields.<br><br>Negative values are not allowed. If the source has negative days supply the record should be dropped as it is unknown if the patient actually took the drug. Several actions are possible: 1) record is not trustworthy and we remove the record entirely. 2) we trust the record and leave days_supply empty or 3) record needs to be combined with other record (e.g. reversal of prescription). High values (>365 days) should be investigated. If considered an error in the source data (e.g. typo), the value needs to be excluded to prevent creation of unrealistic long eras.",No,No,NA,NA,NA,NA,NA
drug_exposure,sig,No,varchar(MAX),This is the verbatim instruction for the drug as written by the provider.,"Put the written out instructions for the drug as it is verbatim in the source, if available.",No,No,NA,NA,NA,NA,NA
drug_exposure,route_concept_id,No,integer,NA,The standard CONCEPT_ID that the ROUTE_SOURCE_VALUE maps to in the route domain.,No,Yes,CONCEPT,CONCEPT_ID,Route,NA,NA
drug_exposure,route_concept_id,No,integer,NA,The standard CONCEPT_ID that the ROUTE_SOURCE_VALUE maps to in the route domain. This is meant to represent the route of administration of the drug. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Route&standardConcept=Standard&page=1&pageSize=15&query=),No,Yes,CONCEPT,CONCEPT_ID,Route,NA,NA
drug_exposure,lot_number,No,varchar(50),NA,NA,No,No,NA,NA,NA,NA,NA
drug_exposure,provider_id,No,integer,"The Provider associated with drug record, e.g. the provider who wrote the prescription or the provider who administered the drug.","The ETL may need to make a choice as to which PROVIDER_ID to put here. Based on what is available this may or may not be different than the provider associated with the overall VISIT_OCCURRENCE record, for example the ordering vs administering physician on an EHR record.",No,Yes,PROVIDER,PROVIDER_ID,NA,NA,NA
drug_exposure,visit_occurrence_id,No,integer,"The Visit during which the drug was prescribed, administered or dispensed.",To populate this field drug exposures must be explicitly initiated in the visit.,No,Yes,VISIT_OCCURRENCE,VISIT_OCCURRENCE_ID,NA,NA,NA
@ -134,7 +134,7 @@ device_exposure,device_exposure_start_date,Yes,date,Use this date to determine t
device_exposure,device_exposure_start_datetime,No,datetime,NA,"This is not required, though it is in v6. If a source does not specify datetime the convention is to set the time to midnight (00:00:0000)",No,No,NA,NA,NA,NA,NA
device_exposure,device_exposure_end_date,No,date,"The DEVICE_EXPOSURE_END_DATE denotes the day the device exposure ended for the patient, if given.",Put the end date or discontinuation date as it appears from the source data or leave blank if unavailable.,No,No,NA,NA,NA,NA,NA
device_exposure,device_exposure_end_datetime,No,datetime,NA,If a source does not specify datetime the convention is to set the time to midnight (00:00:0000),No,No,NA,NA,NA,NA,NA
device_exposure,device_type_concept_id,Yes,integer,"You can use the TYPE_CONCEPT_ID to denote the provenance of the record, as in whether the record is from administrative claims or EHR.","Choose the drug_type_concept_id that best represents the provenance of the record, for example whether it came from a record of a prescription written or physician administered drug. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Type+Concept&standardConcept=Standard&page=1&pageSize=15&query=). A more detailed explanation of each Type Concept can be found on the [vocabulary wiki](https://github.com/OHDSI/Vocabulary-v5.0/wiki/Vocab.-TYPE_CONCEPT).",No,Yes,CONCEPT,CONCEPT_ID,Type Concept,NA,NA
device_exposure,device_type_concept_id,Yes,integer,"You can use the TYPE_CONCEPT_ID to denote the provenance of the record, as in whether the record is from administrative claims or EHR.","Choose the device_type_concept_id that best represents the provenance of the record. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Type+Concept&standardConcept=Standard&page=1&pageSize=15&query=). A more detailed explanation of each Type Concept can be found on the [vocabulary wiki](https://github.com/OHDSI/Vocabulary-v5.0/wiki/Vocab.-TYPE_CONCEPT).",No,Yes,CONCEPT,CONCEPT_ID,Type Concept,NA,NA
device_exposure,unique_device_id,No,varchar(255),"This is the Unique Device Identification (UDI-DI) number for devices regulated by the FDA, if given.","For medical devices that are regulated by the FDA, a Unique Device Identification (UDI) is provided if available in the data source and is recorded in the UNIQUE_DEVICE_ID field.",No,No,NA,NA,NA,NA,NA
device_exposure,production_id,No,varchar(255),This is the Production Identifier (UDI-PI) portion of the Unique Device Identification.,NA,No,No,NA,NA,NA,NA,NA
device_exposure,quantity,No,integer,NA,"If there is a record of device exposure in the source but no quantity value, then set to 1.",No,No,NA,NA,NA,NA,NA
@ -148,12 +148,12 @@ device_exposure,unit_source_value,No,varchar(50),"This field houses the verbatim
device_exposure,unit_source_concept_id,No,integer,"This is the concept representing the UNIT_SOURCE_VALUE and may not necessarily be standard. This field is discouraged from use in analysis because it is not required to contain Standard Concepts that are used across the OHDSI community, and should only be used when Standard Concepts do not adequately represent the source detail for the Unit necessary for a given analytic use case. Consider using UNIT_CONCEPT_ID instead to enable standardized analytics that can be consistent across the network.",If the UNIT_SOURCE_VALUE is coded in the source data using an OMOP supported vocabulary put the concept id representing the source value here.,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
measurement,measurement_id,Yes,integer,The unique key given to a Measurement record for a Person. Refer to the ETL for how duplicate Measurements during the same Visit were handled.,"Each instance of a measurement present in the source data should be assigned this unique key. In some cases, a person can have multiple records of the same measurement within the same visit. It is valid to keep these duplicates and assign them individual, unique, MEASUREMENT_IDs, though it is up to the ETL how they should be handled.",Yes,No,NA,NA,NA,NA,NA
measurement,person_id,Yes,integer,The PERSON_ID of the Person for whom the Measurement is recorded. This may be a system generated code.,NA,No,Yes,PERSON,PERSON_ID,NA,NA,NA
measurement,measurement_concept_id,Yes,integer,"The MEASUREMENT_CONCEPT_ID field is recommended for primary use in analyses, and must be used for network studies. This is the standard concept mapped from the source value which represents a measurement.",The CONCEPT_ID that the MEASUREMENT_SOURCE_VALUE maps to. Only records whose source values map to concepts with a domain of ÒMeasurementÓ should go in this table.,No,Yes,CONCEPT,CONCEPT_ID,Measurement,NA,NA
measurement,measurement_concept_id,Yes,integer,"The MEASUREMENT_CONCEPT_ID field is recommended for primary use in analyses, and must be used for network studies. This is the standard concept mapped from the source value which represents a measurement.",The CONCEPT_ID that the MEASUREMENT_SOURCE_VALUE maps to. Only records whose source values map to concepts with a domain of <EFBFBD>Measurement<EFBFBD> should go in this table.,No,Yes,CONCEPT,CONCEPT_ID,Measurement,NA,NA
measurement,measurement_date,Yes,date,Use this date to determine the date of the measurement.,"If there are multiple dates in the source data associated with a record such as order_date, draw_date, and result_date, choose the one that is closest to the date the sample was drawn from the patient.",No,No,NA,NA,NA,NA,NA
measurement,measurement_datetime,No,datetime,NA,"This is not required, though it is in v6. If a source does not specify datetime the convention is to set the time to midnight (00:00:0000)",No,No,NA,NA,NA,NA,NA
measurement,measurement_time,No,varchar(10),NA,This is present for backwards compatibility and will be deprecated in an upcoming version.,No,No,NA,NA,NA,NA,NA
measurement,measurement_type_concept_id,Yes,integer,"This field can be used to determine the provenance of the Measurement record, as in whether the measurement was from an EHR system, insurance claim, registry, or other sources.","Choose the MEASUREMENT_TYPE_CONCEPT_ID that best represents the provenance of the record, for example whether it came from an EHR record or billing claim. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Type+Concept&standardConcept=Standard&page=1&pageSize=15&query=). A more detailed explanation of each Type Concept can be found on the [vocabulary wiki](https://github.com/OHDSI/Vocabulary-v5.0/wiki/Vocab.-TYPE_CONCEPT).",No,Yes,CONCEPT,CONCEPT_ID,Type Concept,NA,NA
measurement,operator_concept_id,No,integer,"The meaning of Concept [4172703](https://athena.ohdsi.org/search-terms/terms/4172703) for '=' is identical to omission of a OPERATOR_CONCEPT_ID value. Since the use of this field is rare, it's important when devising analyses to not to forget testing for the content of this field for values different from =.","Operators are <, <=, =, >=, > and these concepts belong to the 'Meas Value Operator' domain. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Meas+Value+Operator&standardConcept=Standard&page=1&pageSize=15&query=). Leave it NULL if there's an exact numeric value given (instead of putting '=') or there's no numeric value at all.",No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
measurement,operator_concept_id,No,integer,"The meaning of Concept [4172703](https://athena.ohdsi.org/search-terms/terms/4172703) for '=' is identical to omission of a OPERATOR_CONCEPT_ID value. Since the use of this field is rare, it's important when devising analyses to not to forget testing for the content of this field for values different from =.","Operators are <, <=, =, >=, > and these concepts belong to the 'Meas Value Operator' domain. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Meas+Value+Operator&standardConcept=Standard&page=1&pageSize=15&query=). The operator_concept_id explictly refers to the value of the measurement. Leave it NULL if there's an exact numeric value given (instead of putting '=') or there's no numeric value at all.",No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
measurement,value_as_number,No,float,"This is the numerical value of the Result of the Measurement, if available. Note that measurements such as blood pressures will be split into their component parts i.e. one record for systolic, one record for diastolic.",[Convention for negative values](https://ohdsi.github.io/Themis/negative_value_as_number.html),No,No,NA,NA,NA,NA,NA
measurement,value_as_concept_id,No,integer,If the raw data gives a categorial result for measurements those values are captured and mapped to standard concepts in the 'Meas Value' domain.,"If there is no categorial result in the source data, set VALUE_AS_CONCEPT_ID to NULL, if there is a categorial result in a source data but without mapping, set VALUE_AS_CONCEPT_ID to 0, else map to a CONCEPT_ID.",No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
measurement,unit_concept_id,No,integer,"At present, there isn't a prescribed unit for individual measurements, such as Hemoglobin A1C, meaning it's not obligatory to express these measurements as a percentage. UNIT_SOURCE_VALUES should be linked to a Standard Concept within the Unit domain that most accurately reflects the unit provided in the source data.","If the source data does not include units, set UNIT_CONCEPT_ID to NULL. If units are provided but not mapped, set UNIT_CONCEPT_ID to 0. Otherwise, map the units to a CONCEPT_ID. Remember that units are case-sensitive in vocabulary.",No,Yes,CONCEPT,CONCEPT_ID,Unit,NA,NA
@ -177,7 +177,7 @@ observation,observation_datetime,No,datetime,NA,If no time is given set to midni
observation,observation_type_concept_id,Yes,integer,"This field can be used to determine the provenance of the Observation record, as in whether the measurement was from an EHR system, insurance claim, registry, or other sources.","Choose the OBSERVATION_TYPE_CONCEPT_ID that best represents the provenance of the record, for example whether it came from an EHR record or billing claim. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Type+Concept&standardConcept=Standard&page=1&pageSize=15&query=). A more detailed explanation of each Type Concept can be found on the [vocabulary wiki](https://github.com/OHDSI/Vocabulary-v5.0/wiki/Vocab.-TYPE_CONCEPT).",No,Yes,CONCEPT,CONCEPT_ID,Type Concept,NA,NA
observation,value_as_number,No,float,"This is the numerical value of the Result of the Observation, if applicable and available. It is not expected that all Observations will have numeric results, rather, this field is here to house values should they exist.",NA,No,No,NA,NA,NA,NA,NA
observation,value_as_string,No,varchar(60),"This is the categorical value of the Result of the Observation, if applicable and available.",NA,No,No,NA,NA,NA,NA,NA
observation,value_as_concept_id,No,Integer,"It is possible that some records destined for the Observation table have two clinical ideas represented in one source code. This is common with ICD10 codes that describe a family history of some Condition, for example. In OMOP the Vocabulary breaks these two clinical ideas into two codes; one becomes the OBSERVATION_CONCEPT_ID and the other becomes the VALUE_AS_CONCEPT_ID. It is important when using the Observation table to keep this possibility in mind and to examine the VALUE_AS_CONCEPT_ID field for relevant information.","Note that the value of VALUE_AS_CONCEPT_ID may be provided through mapping from a source Concept which contains the content of the Observation. In those situations, the CONCEPT_RELATIONSHIP table in addition to the 'Maps to' record contains a second record with the relationship_id set to 'Maps to value'. For example, ICD10 [Z82.4](https://athena.ohdsi.org/search-terms/terms/45581076) 'Family history of ischaemic heart disease and other diseases of the circulatory system' has a 'Maps to' relationship to [4167217](https://athena.ohdsi.org/search-terms/terms/4167217) 'Family history of clinical finding' as well as a 'Maps to value' record to [134057](https://athena.ohdsi.org/search-terms/terms/134057) 'Disorder of cardiovascular system'. If there's no categorial result in a source_data, set value_as_concept_id to NULL, if there is a categorial result in a source_data but without mapping, set value_as_concept_id to 0.",No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
observation,value_as_concept_id,No,integer,"It is possible that some records destined for the Observation table have two clinical ideas represented in one source code. This is common with ICD10 codes that describe a family history of some Condition, for example. In OMOP the Vocabulary breaks these two clinical ideas into two codes; one becomes the OBSERVATION_CONCEPT_ID and the other becomes the VALUE_AS_CONCEPT_ID. It is important when using the Observation table to keep this possibility in mind and to examine the VALUE_AS_CONCEPT_ID field for relevant information.","Note that the value of VALUE_AS_CONCEPT_ID may be provided through mapping from a source Concept which contains the content of the Observation. In those situations, the CONCEPT_RELATIONSHIP table in addition to the 'Maps to' record contains a second record with the relationship_id set to 'Maps to value'. For example, ICD10 [Z82.4](https://athena.ohdsi.org/search-terms/terms/45581076) 'Family history of ischaemic heart disease and other diseases of the circulatory system' has a 'Maps to' relationship to [4167217](https://athena.ohdsi.org/search-terms/terms/4167217) 'Family history of clinical finding' as well as a 'Maps to value' record to [134057](https://athena.ohdsi.org/search-terms/terms/134057) 'Disorder of cardiovascular system'. If there's no categorial result in a source_data, set value_as_concept_id to NULL, if there is a categorial result in a source_data but without mapping, set value_as_concept_id to 0.",No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
observation,qualifier_concept_id,No,integer,"This field contains all attributes specifying the clinical fact further, such as as degrees, severities, drug-drug interaction alerts etc.","Use your best judgement as to what Concepts to use here and if they are necessary to accurately represent the clinical record. There is no restriction on the domain of these Concepts, they just need to be Standard.",No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
observation,unit_concept_id,No,integer,There is currently no recommended unit for individual observation concepts. UNIT_SOURCE_VALUES should be mapped to a Standard Concept in the Unit domain that best represents the unit as given in the source data.,"There is no standardization requirement for units associated with OBSERVATION_CONCEPT_IDs, however, it is the responsibility of the ETL to choose the most plausible unit. If the source unit is NULL (applicable to cases when there's no numerical value or when it doesn't require a unit), keep unit_concept_id NULL as well. If there's no mapping of a source unit, populate unit_concept_id with 0.",No,Yes,CONCEPT,CONCEPT_ID,Unit,NA,NA
observation,provider_id,No,integer,"The provider associated with the observation record, e.g. the provider who ordered the test or the provider who recorded the result.",The ETL may need to make a choice as to which PROVIDER_ID to put here. Based on what is available this may or may not be different than the provider associated with the overall VISIT_OCCURRENCE record. For example the admitting vs attending physician on an EHR record.,No,Yes,PROVIDER,PROVIDER_ID,NA,NA,NA
@ -188,7 +188,7 @@ observation,observation_source_concept_id,No,integer,"This is the concept repres
observation,unit_source_value,No,varchar(50),This field houses the verbatim value from the source data representing the unit of the Observation that occurred.,This code is mapped to a Standard Condition Concept in the Standardized Vocabularies and the original code is stored here for reference.,No,No,NA,NA,NA,NA,NA
observation,qualifier_source_value,No,varchar(50),This field houses the verbatim value from the source data representing the qualifier of the Observation that occurred.,This code is mapped to a Standard Condition Concept in the Standardized Vocabularies and the original code is stored here for reference.,No,No,NA,NA,NA,NA,NA
observation,value_source_value,No,varchar(50),This field houses the verbatim result value of the Observation from the source data. Do not get confused with the Observation_source_value which captures source value of the observation mapped to observation_concept_id. This field is the observation result value from the source.,"If the observation_source_value was a question, for example, or an observation that requires a result then this field is the answer/ result from the source data. Store the verbatim value that represents the result of the observation_source_value.",No,No,NA,NA,NA,NA,NA
observation,observation_event_id,No,integer,"If the Observation record is related to another record in the database, this field is the primary key of the linked record.","Put the primary key of the linked record, if applicable, here. See the [ETL Conventions for the OBSERVATION](https://ohdsi.github.io/CommonDataModel/cdm60.html#observation) table for more details.",No,No,NA,NA,NA,NA,NA
observation,observation_event_id,No,integer,"If the Observation record is related to another record in the database, this field is the primary key of the linked record.","Put the primary key of the linked record, if applicable, here. See the [ETL Conventions for the OBSERVATION](https://ohdsi.github.io/CommonDataModel/cdm54.html#observation) table for more details.",No,No,NA,NA,NA,NA,NA
observation,obs_event_field_concept_id,No,integer,"If the Observation record is related to another record in the database, this field is the CONCEPT_ID that identifies which table the primary key of the linked record came from.",Put the CONCEPT_ID that identifies which table and field the OBSERVATION_EVENT_ID came from.,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
death,person_id,Yes,integer,NA,NA,No,Yes,PERSON,PERSON_ID,NA,NA,NA
death,death_date,Yes,date,The date the person was deceased.,"If the precise date include day or month is not known or not allowed, December is used as the default month, and the last day of the month the default day. For additional conventions related to this field, please refer to the [THEMIS repository](https://ohdsi.github.io/Themis/tag_death_date.html). ",No,No,NA,NA,NA,NA,NA
@ -396,7 +396,7 @@ cdm_source,cdm_source_name,Yes,varchar(255),The name of the CDM instance.,NA,No,
cdm_source,cdm_source_abbreviation,Yes,varchar(25),The abbreviation of the CDM instance.,NA,No,No,NA,NA,NA,NA,NA
cdm_source,cdm_holder,Yes,varchar(255),The holder of the CDM instance.,NA,No,No,NA,NA,NA,NA,NA
cdm_source,source_description,No,varchar(MAX),The description of the CDM instance.,NA,No,No,NA,NA,NA,NA,NA
cdm_source,source_documentation_reference,No,varchar(255),NA,NA,No,No,NA,NA,NA,NA,NA
cdm_source,source_documentation_reference,No,varchar(255),Refers to a publication or web resource describing the source data, e.g. a data dictionary.,NA,No,No,NA,NA,NA,NA,NA
cdm_source,cdm_etl_reference,No,varchar(255),NA,Version of the ETL script used. e.g. link to the Git release,No,No,NA,NA,NA,NA,NA
cdm_source,source_release_date,Yes,date,The date the data was extracted from the source system. In some systems that is the same as the date the ETL was run. Typically the latest even date in the source is on the source_release_date.,NA,No,No,NA,NA,NA,NA,NA
cdm_source,cdm_release_date,Yes,date,The date the ETL script was completed. Typically this is after the source_release_date.,NA,No,No,NA,NA,NA,NA,NA
@ -405,8 +405,8 @@ cdm_source,cdm_version_concept_id,Yes,integer,The Concept Id representing the ve
cdm_source,vocabulary_version,Yes,varchar(20),Version of the OMOP standardised vocabularies loaded,You can find the version of your Vocabulary using the query: `SELECT vocabulary_version from vocabulary where vocabulary_id = 'None'`,No,No,NA,NA,NA,NA,NA
concept,concept_id,Yes,integer,A unique identifier for each Concept across all domains.,NA,Yes,No,NA,NA,NA,NA,NA
concept,concept_name,Yes,varchar(255),"An unambiguous, meaningful and descriptive name for the Concept.",NA,No,No,NA,NA,NA,NA,NA
concept,domain_id,Yes,varchar(20),A foreign key to the [DOMAIN](https://ohdsi.github.io/CommonDataModel/cdm531.html#domain) table the Concept belongs to.,NA,No,Yes,DOMAIN,DOMAIN_ID,NA,NA,NA
concept,vocabulary_id,Yes,varchar(20),"A foreign key to the [VOCABULARY](https://ohdsi.github.io/CommonDataModel/cdm531.html#vocabulary)
concept,domain_id,Yes,varchar(20),A foreign key to the [DOMAIN](https://ohdsi.github.io/CommonDataModel/cdm54.html#domain) table the Concept belongs to.,NA,No,Yes,DOMAIN,DOMAIN_ID,NA,NA,NA
concept,vocabulary_id,Yes,varchar(20),"A foreign key to the [VOCABULARY](https://ohdsi.github.io/CommonDataModel/cdm54.html#vocabulary)
table indicating from which source the
Concept has been adapted.",NA,No,Yes,VOCABULARY,VOCABULARY_ID,NA,NA,NA
concept,concept_class_id,Yes,varchar(20),"The attribute or concept class of the
@ -479,7 +479,7 @@ relationship,reverse_relationship_id,Yes,varchar(20),"The identifier for the rel
define the reverse relationship between two
concepts.",NA,No,No,NA,NA,NA,NA,NA
relationship,relationship_concept_id,Yes,integer,"A foreign key that refers to an identifier in
the [CONCEPT](https://ohdsi.github.io/CommonDataModel/cdm531.html#concept) table for the unique
the [CONCEPT](https://ohdsi.github.io/CommonDataModel/cdm54.html#concept) table for the unique
relationship concept.",NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
concept_synonym,concept_id,Yes,integer,NA,NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
concept_synonym,concept_synonym_name,Yes,varchar(1000),NA,NA,No,No,NA,NA,NA,NA,NA
@ -548,4 +548,4 @@ cohort_definition,cohort_definition_description,No,varchar(MAX),A complete descr
cohort_definition,definition_type_concept_id,Yes,integer,Type defining what kind of Cohort Definition the record represents and how the syntax may be executed.,NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
cohort_definition,cohort_definition_syntax,No,varchar(MAX),Syntax or code to operationalize the Cohort Definition.,NA,No,No,NA,NA,NA,NA,NA
cohort_definition,subject_concept_id,Yes,integer,"This field contains a Concept that represents the domain of the subjects that are members of the cohort (e.g., Person, Provider, Visit).",NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
cohort_definition,cohort_initiation_date,No,date,A date to indicate when the Cohort was initiated in the COHORT table.,NA,No,No,NA,NA,NA,NA,NA
cohort_definition,cohort_initiation_date,No,date,A date to indicate when the Cohort was initiated in the COHORT table.,NA,No,No,NA,NA,NA,NA,NA

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@ -1,6 +1,6 @@
cdmTableName,schema,isRequired,conceptPrefix,measurePersonCompleteness,measurePersonCompletenessThreshold,validation,tableDescription,userGuidance,etlConventions
person,CDM,Yes,NA,No,NA,NA,"This table serves as the central identity management for all Persons in the database. It contains records that uniquely identify each person or patient, and some demographic information.",All records in this table are independent Persons.,"All Persons in a database needs one record in this table, unless they fail data quality requirements specified in the ETL. Persons with no Events should have a record nonetheless. If more than one data source contributes Events to the database, Persons must be reconciled, if possible, across the sources to create one single record per Person. The content of the BIRTH_DATETIME must be equivalent to the content of BIRTH_DAY, BIRTH_MONTH and BIRTH_YEAR.<br><br>For detailed conventions for how to populate this table, please refer to the [THEMIS repository](https://ohdsi.github.io/Themis/person.html)."
observation_period,CDM,Yes,NA,Yes,0,NA,"This table contains records which define spans of time during which two conditions are expected to hold: (i) Clinical Events that happened to the Person are recorded in the Event tables, and (ii) absence of records indicate such Events did not occur during this span of time.","For each Person, one or more OBSERVATION_PERIOD records may be present, but they will not overlap or be back to back to each other. Events may exist outside all of the time spans of the OBSERVATION_PERIOD records for a patient, however, absence of an Event outside these time spans cannot be construed as evidence of absence of an Event. Incidence or prevalence rates should only be calculated for the time of active OBSERVATION_PERIOD records. When constructing cohorts, outside Events can be used for inclusion criteria definition, but without any guarantee for the performance of these criteria. Also, OBSERVATION_PERIOD records can be as short as a single day, greatly disturbing the denominator of any rate calculation as part of cohort characterizations. To avoid that, apply minimal observation time as a requirement for any cohort definition.","Each Person needs to have at least one OBSERVATION_PERIOD record, which should represent time intervals with a high capture rate of Clinical Events. Some source data have very similar concepts, such as enrollment periods in insurance claims data. In other source data such as most EHR systems these time spans need to be inferred under a set of assumptions. It is the discretion of the ETL developer to define these assumptions. In many ETL solutions the start date of the first occurrence or the first high quality occurrence of a Clinical Event (Condition, Drug, Procedure, Device, Measurement, Visit) is defined as the start of the OBSERVATION_PERIOD record, and the end date of the last occurrence of last high quality occurrence of a Clinical Event, or the end of the database period becomes the end of the OBSERVATOIN_PERIOD for each Person. If a Person only has a single Clinical Event the OBSERVATION_PERIOD record can be as short as one day. Depending on these definitions it is possible that Clinical Events fall outside the time spans defined by OBSERVATION_PERIOD records. Family history or history of Clinical Events generally are not used to generate OBSERVATION_PERIOD records around the time they are referring to. Any two overlapping or adjacent OBSERVATION_PERIOD records have to be merged into one."
cdmTableName,schema,isRequired,conceptPrefix,measurePersonCompleteness,measurePersonCompletenessThreshold,validation,tableDescription,userGuidance,etlConventions
person,CDM,Yes,NA,No,NA,NA,"This table serves as the central identity management for all Persons in the database. It contains records that uniquely identify each person or patient, and some demographic information.",All records in this table are independent Persons.,"All Persons in a database needs one record in this table, unless they fail data quality requirements specified in the ETL. Persons with no Events should have a record nonetheless. If more than one data source contributes Events to the database, Persons must be reconciled, if possible, across the sources to create one single record per Person. The content of the BIRTH_DATETIME must be equivalent to the content of BIRTH_DAY, BIRTH_MONTH and BIRTH_YEAR.<br><br>For detailed conventions for how to populate this table, please refer to the [THEMIS repository](https://ohdsi.github.io/Themis/person.html)."
observation_period,CDM,Yes,NA,Yes,0,NA,"This table contains records which define spans of time during which two conditions are expected to hold: (i) Clinical Events that happened to the Person are recorded in the Event tables, and (ii) absence of records indicate such Events did not occur during this span of time.","For each Person, one or more OBSERVATION_PERIOD records may be present, but they will not overlap or be back to back to each other. Events may exist outside all of the time spans of the OBSERVATION_PERIOD records for a patient, however, absence of an Event outside these time spans cannot be construed as evidence of absence of an Event. Incidence or prevalence rates should only be calculated for the time of active OBSERVATION_PERIOD records. When constructing cohorts, outside Events can be used for inclusion criteria definition, but without any guarantee for the performance of these criteria. Also, OBSERVATION_PERIOD records can be as short as a single day, greatly disturbing the denominator of any rate calculation as part of cohort characterizations. To avoid that, apply minimal observation time as a requirement for any cohort definition.","Each Person needs to have at least one OBSERVATION_PERIOD record, which should represent time intervals with a high capture rate of Clinical Events. Some source data have very similar concepts, such as enrollment periods in insurance claims data. In other source data such as most EHR systems these time spans need to be inferred under a set of assumptions. It is the discretion of the ETL developer to define these assumptions. In many ETL solutions the start date of the first occurrence or the first high quality occurrence of a Clinical Event (Condition, Drug, Procedure, Device, Measurement, Visit) is defined as the start of the OBSERVATION_PERIOD record, and the end date of the last occurrence of last high quality occurrence of a Clinical Event, or the end of the database period becomes the end of the OBSERVATION_PERIOD for each Person. If a Person only has a single Clinical Event the OBSERVATION_PERIOD record can be as short as one day. Depending on these definitions it is possible that Clinical Events fall outside the time spans defined by OBSERVATION_PERIOD records. Family history or history of Clinical Events generally are not used to generate OBSERVATION_PERIOD records around the time they are referring to. Any two overlapping or adjacent OBSERVATION_PERIOD records have to be merged into one."
visit_occurrence,CDM,No,VISIT_,Yes,0,NA,"This table contains Events where Persons engage with the healthcare system for a duration of time. They are often also called ""Encounters"". Visits are defined by a configuration of circumstances under which they occur, such as (i) whether the patient comes to a healthcare institution, the other way around, or the interaction is remote, (ii) whether and what kind of trained medical staff is delivering the service during the Visit, and (iii) whether the Visit is transient or for a longer period involving a stay in bed.","The configuration defining the Visit are described by Concepts in the Visit Domain, which form a hierarchical structure, but rolling up to generally familiar Visits adopted in most healthcare systems worldwide:
- [Inpatient Visit](https://athena.ohdsi.org/search-terms/terms/9201): Person visiting hospital, at a Care Site, in bed, for duration of more than one day, with physicians and other Providers permanently available to deliver service around the clock
@ -15,15 +15,23 @@ visit_occurrence,CDM,No,VISIT_,Yes,0,NA,"This table contains Events where Person
- [Ambulance Visit](https://athena.ohdsi.org/search-terms/terms/581478): Person using transportation service for the purpose of initiating one of the other Visits, without a Care Site, within one day, potentially with Providers accompanying the Visit and delivering service
- [Case Management Visit](https://athena.ohdsi.org/search-terms/terms/38004193): Person interacting with healthcare system, without a Care Site, within a day, with no Providers involved, for administrative purposes
The Visit duration, or 'length of stay', is defined as VISIT_END_DATE - VISIT_START_DATE. For all Visits this is <1 day, except Inpatient Visits and Non-hospital institution Visits. The CDM also contains the VISIT_DETAIL table where additional information about the Visit is stored, for example, transfers between units during an inpatient Visit.","Visits can be derived easily if the source data contain coding systems for Place of Service or Procedures, like CPT codes for well visits. In those cases, the codes can be looked up and mapped to a Standard Visit Concept. Otherwise, Visit Concepts have to be identified in the ETL process. This table will contain concepts in the Visit domain. These concepts are arranged in a hierarchical structure to facilitate cohort definitions by rolling up to generally familiar Visits adopted in most healthcare systems worldwide. Visits can be adjacent to each other, i.e. the end date of one can be identical with the start date of the other. As a consequence, more than one-day Visits or their descendants can be recorded for the same day. Multi-day visits must not overlap, i.e. share days other than start and end days. It is often the case that some logic should be written for how to define visits and how to assign Visit_Concept_Id. For example, in US claims outpatient visits that appear to occur within the time period of an inpatient visit can be rolled into one with the same Visit_Occurrence_Id. In EHR data inpatient visits that are within one day of each other may be strung together to create one visit. It will all depend on the source data and how encounter records should be translated to visit occurrences. Providers can be associated with a Visit through the PROVIDER_ID field, or indirectly through PROCEDURE_OCCURRENCE records linked both to the VISIT and PROVIDER tables."
visit_detail,CDM,No,VISIT_DETAIL_,Yes,0,NA,The VISIT_DETAIL table is an optional table used to represents details of each record in the parent VISIT_OCCURRENCE table. A good example of this would be the movement between units in a hospital during an inpatient stay or claim lines associated with a one insurance claim. For every record in the VISIT_OCCURRENCE table there may be 0 or more records in the VISIT_DETAIL table with a 1:n relationship where n may be 0. The VISIT_DETAIL table is structurally very similar to VISIT_OCCURRENCE table and belongs to the visit domain.,"The configuration defining the Visit Detail is described by Concepts in the Visit Domain, which form a hierarchical structure. The Visit Detail record will have an associated to the Visit Occurrence record in two ways: <br> 1. The Visit Detail record will have the VISIT_OCCURRENCE_ID it is associated to 2. The VISIT_DETAIL_CONCEPT_ID will be a descendant of the VISIT_CONCEPT_ID for the Visit.","It is not mandatory that the VISIT_DETAIL table be filled in, but if you find that the logic to create VISIT_OCCURRENCE records includes the roll-up of multiple smaller records to create one picture of a Visit then it is a good idea to use VISIT_DETAIL. In EHR data, for example, a Person may be in the hospital but instead of one over-arching Visit their encounters are recorded as times they interacted with a health care provider. A Person in the hospital interacts with multiple providers multiple times a day so the encounters must be strung together using some heuristic (defined by the ETL) to identify the entire Visit. In this case the encounters would be considered Visit Details and the entire Visit would be the Visit Occurrence. In this example it is also possible to use the Vocabulary to distinguish Visit Details from a Visit Occurrence by setting the VISIT_CONCEPT_ID to [9201](https://athena.ohdsi.org/search-terms/terms/9201) and the VISIT_DETAIL_CONCEPT_IDs either to 9201 or its children to indicate where the patient was in the hospital at the time of care."
condition_occurrence,CDM,No,CONDITION_,Yes,0,NA,"This table contains records of Events of a Person suggesting the presence of a disease or medical condition stated as a diagnosis, a sign, or a symptom, which is either observed by a Provider or reported by the patient.","Conditions are defined by Concepts from the Condition domain, which form a complex hierarchy. As a result, the same Person with the same disease may have multiple Condition records, which belong to the same hierarchical family. Most Condition records are mapped from diagnostic codes, but recorded signs, symptoms and summary descriptions also contribute to this table. Rule out diagnoses should not be recorded in this table, but in reality their negating nature is not always captured in the source data, and other precautions must be taken when when identifying Persons who should suffer from the recorded Condition. Record all conditions as they exist in the source data. Any decisions about diagnosis/phenotype definitions would be done through cohort specifications. These cohorts can be housed in the [COHORT](https://ohdsi.github.io/CommonDataModel/cdm531.html#payer_plan_period) table. Conditions span a time interval from start to end, but are typically recorded as single snapshot records with no end date. The reason is twofold: (i) At the time of the recording the duration is not known and later not recorded, and (ii) the Persons typically cease interacting with the healthcare system when they feel better, which leads to incomplete capture of resolved Conditions. The [CONDITION_ERA](https://ohdsi.github.io/CommonDataModel/cdm531.html#condition_era) table addresses this issue. Family history and past diagnoses ('history of') are not recorded in this table. Instead, they are listed in the [OBSERVATION](https://ohdsi.github.io/CommonDataModel/cdm531.html#observation) table. Codes written in the process of establishing the diagnosis, such as 'question of' of and 'rule out', should not represented here. Instead, they should be recorded in the [OBSERVATION](https://ohdsi.github.io/CommonDataModel/cdm531.html#observation) table, if they are used for analyses. However, this information is not always available.",Source codes and source text fields mapped to Standard Concepts of the Condition Domain have to be recorded here.
drug_exposure,CDM,No,DRUG_,Yes,0,NA,"This table captures records about the exposure to a Drug ingested or otherwise introduced into the body. A Drug is a biochemical substance formulated in such a way that when administered to a Person it will exert a certain biochemical effect on the metabolism. Drugs include prescription and over-the-counter medicines, vaccines, and large-molecule biologic therapies. Radiological devices ingested or applied locally do not count as Drugs.","The purpose of records in this table is to indicate an exposure to a certain drug as best as possible. In this context a drug is defined as an active ingredient. Drug Exposures are defined by Concepts from the Drug domain, which form a complex hierarchy. As a result, one DRUG_SOURCE_CONCEPT_ID may map to multiple standard concept ids if it is a combination product. Records in this table represent prescriptions written, prescriptions dispensed, and drugs administered by a provider to name a few. The DRUG_TYPE_CONCEPT_ID can be used to find and filter on these types. This table includes additional information about the drug products, the quantity given, and route of administration.","Information about quantity and dose is provided in a variety of different ways and it is important for the ETL to provide as much information as possible from the data. Depending on the provenance of the data fields may be captured differently i.e. quantity for drugs administered may have a separate meaning from quantity for prescriptions dispensed. If a patient has multiple records on the same day for the same drug or procedures the ETL should not de-dupe them unless there is probable reason to believe the item is a true data duplicate. Take note on how to handle refills for prescriptions written.<br><br>For detailed conventions on how to populate this table, please refer to the [THEMIS repository](https://ohdsi.github.io/Themis/drug_exposure.html)."
procedure_occurrence,CDM,No,PROCEDURE_,Yes,0,NA,"This table contains records of activities or processes ordered by, or carried out by, a healthcare provider on the patient with a diagnostic or therapeutic purpose.","Lab tests are not a procedure, if something is observed with an expected resulting amount and unit then it should be a measurement. Phlebotomy is a procedure but so trivial that it tends to be rarely captured. It can be assumed that there is a phlebotomy procedure associated with many lab tests, therefore it is unnecessary to add them as separate procedures. If the user finds the same procedure over concurrent days, it is assumed those records are part of a procedure lasting more than a day. This logic is in lieu of the procedure_end_date, which will be added in a future version of the CDM.","When dealing with duplicate records, the ETL must determine whether to sum them up into one record or keep them separate. Things to consider are: - Same Procedure - Same PROCEDURE_DATETIME - Same Visit Occurrence or Visit Detail - Same Provider - Same Modifier for Procedures. Source codes and source text fields mapped to Standard Concepts of the Procedure Domain have to be recorded here."
device_exposure,CDM,No,DEVICE_,Yes,0,NA,"The Device domain captures information about a person's exposure to a foreign physical object or instrument which is used for diagnostic or therapeutic purposes through a mechanism beyond chemical action. Devices include implantable objects (e.g. pacemakers, stents, artificial joints), medical equipment and supplies (e.g. bandages, crutches, syringes), other instruments used in medical procedures (e.g. sutures, defibrillators) and material used in clinical care (e.g. adhesives, body material, dental material, surgical material).","The distinction between Devices or supplies and Procedures are sometimes blurry, but the former are physical objects while the latter are actions, often to apply a Device or supply.",Source codes and source text fields mapped to Standard Concepts of the Device Domain have to be recorded here.
measurement,CDM,No,MEASUREMENT_,Yes,0,NA,"The MEASUREMENT table contains records of Measurements, i.e. structured values (numerical or categorical) obtained through systematic and standardized examination or testing of a Person or Person's sample. The MEASUREMENT table contains both orders and results of such Measurements as laboratory tests, vital signs, quantitative findings from pathology reports, etc. Measurements are stored as attribute value pairs, with the attribute as the Measurement Concept and the value representing the result. The value can be a Concept (stored in VALUE_AS_CONCEPT), or a numerical value (VALUE_AS_NUMBER) with a Unit (UNIT_CONCEPT_ID). The Procedure for obtaining the sample is housed in the PROCEDURE_OCCURRENCE table, though it is unnecessary to create a PROCEDURE_OCCURRENCE record for each measurement if one does not exist in the source data. Measurements differ from Observations in that they require a standardized test or some other activity to generate a quantitative or qualitative result. If there is no result, it is assumed that the lab test was conducted but the result was not captured.","Measurements are predominately lab tests with a few exceptions, like blood pressure or function tests. Results are given in the form of a value and unit combination. When investigating measurements, look for operator_concept_ids (<, >, etc.).","Only records where the source value maps to a Concept in the measurement domain should be included in this table. Even though each Measurement always has a result, the fields VALUE_AS_NUMBER and VALUE_AS_CONCEPT_ID are not mandatory as often the result is not given in the source data. When the result is not known, the Measurement record represents just the fact that the corresponding Measurement was carried out, which in itself is already useful information for some use cases. For some Measurement Concepts, the result is included in the test. For example, ICD10 CONCEPT_ID [45548980](https://athena.ohdsi.org/search-terms/terms/45548980) 'Abnormal level of unspecified serum enzyme' indicates a Measurement and the result (abnormal). In those situations, the CONCEPT_RELATIONSHIP table in addition to the 'Maps to' record contains a second record with the relationship_id set to 'Maps to value'. In this example, the 'Maps to' relationship directs to [4046263](https://athena.ohdsi.org/search-terms/terms/4046263) 'Enzyme measurement' as well as a 'Maps to value' record to [4135493](https://athena.ohdsi.org/search-terms/terms/4135493) 'Abnormal'."
observation,CDM,No,OBSERVATION_,Yes,0,NA,"The OBSERVATION table captures clinical facts about a Person obtained in the context of examination, questioning or a procedure. Any data that cannot be represented by any other domains, such as social and lifestyle facts, medical history, family history, etc. are recorded here.","Observations differ from Measurements in that they do not require a standardized test or some other activity to generate clinical fact. Typical observations are medical history, family history, the stated need for certain treatment, social circumstances, lifestyle choices, healthcare utilization patterns, etc. If the generation clinical facts requires a standardized testing such as lab testing or imaging and leads to a standardized result, the data item is recorded in the MEASUREMENT table. If the clinical fact observed determines a sign, symptom, diagnosis of a disease or other medical condition, it is recorded in the CONDITION_OCCURRENCE table. Valid Observation Concepts are not enforced to be from any domain but they must not belong to the Condition, Procedure, Drug, Device, Specimen, or Measurement domains and they must be Standard Concepts. <br><br>The observation table usually records the date or datetime of when the observation was obtained, not the date of the observation starting. For example, if the patient reports that they had a heart attack when they were 50, the observation date or datetime is the date of the report, the heart attack observation can have a value_as_concept which captures how long ago the observation applied to the patient.","Records whose Source Values map to any domain besides Condition, Procedure, Drug, Specimen, Measurement or Device should be stored in the Observation table. Observations can be stored as attribute value pairs, with the attribute as the Observation Concept and the value representing the clinical fact. This fact can be a Concept (stored in VALUE_AS_CONCEPT), a numerical value (VALUE_AS_NUMBER), a verbatim string (VALUE_AS_STRING), or a datetime (VALUE_AS_DATETIME). Even though Observations do not have an explicit result, the clinical fact can be stated separately from the type of Observation in the VALUE_AS_* fields. It is recommended for Observations that are suggestive statements of positive assertion should have a value of 'Yes' (concept_id=4188539), recorded, even though the null value is the equivalent."
death,CDM,No,NA,No,NA,NA,"The death domain contains the clinical event for how and when a Person dies. A person can have up to one record if the source system contains evidence about the Death, such as: Condition in an administrative claim, status of enrollment into a health plan, or explicit record in EHR data.",NA,"For specific conventions on how to populate this table, please refer to the [THEMIS repository](https://ohdsi.github.io/Themis/death.html)."
The Visit duration, or 'length of stay', is defined as VISIT_END_DATE - VISIT_START_DATE. For all Visits this is <1 day, except Inpatient Visits and Non-hospital institution Visits. The CDM also contains the VISIT_DETAIL table where additional information about the Visit is stored, for example, transfers between units during an inpatient Visit.","Visits can be derived easily if the source data contain coding systems for Place of Service or Procedures, like CPT codes for well visits. In those cases, the codes can be looked up and mapped to a Standard Visit Concept. Otherwise, Visit Concepts have to be identified in the ETL process. This table will contain concepts in the Visit domain. These concepts are arranged in a hierarchical structure to facilitate cohort definitions by rolling up to generally familiar Visits adopted in most healthcare systems worldwide. Visits can be adjacent to each other, i.e. the end date of one can be identical with the start date of the other. As a consequence, more than one-day Visits or their descendants can be recorded for the same day. Multi-day visits must not overlap, i.e. share days other than start and end days. It is often the case that some logic should be written for how to define visits and how to assign Visit_Concept_Id. For example, in US claims outpatient visits that appear to occur within the time period of an inpatient visit can be rolled into one with the same Visit_Occurrence_Id. In EHR data inpatient visits that are within one day of each other may be strung together to create one visit. It will all depend on the source data and how encounter records should be translated to visit occurrences. Providers can be associated with a Visit through the PROVIDER_ID field, or indirectly through PROCEDURE_OCCURRENCE records linked both to the VISIT and PROVIDER tables."
visit_detail,CDM,No,VISIT_DETAIL_,Yes,0,NA,The VISIT_DETAIL table is an optional table used to represents details of each record in the parent VISIT_OCCURRENCE table. A good example of this would be the movement between units in a hospital during an inpatient stay or claim lines associated with a one insurance claim. For every record in the VISIT_OCCURRENCE table there may be 0 or more records in the VISIT_DETAIL table with a 1:n relationship where n may be 0. The VISIT_DETAIL table is structurally very similar to VISIT_OCCURRENCE table and belongs to the visit domain.,"The configuration defining the Visit Detail is described by Concepts in the Visit Domain, which form a hierarchical structure. The Visit Detail record will have an associated to the Visit Occurrence record in two ways: <br> 1. The Visit Detail record will have the VISIT_OCCURRENCE_ID it is associated to 2. The VISIT_DETAIL_CONCEPT_ID will be a descendant of the VISIT_CONCEPT_ID for the Visit.","It is not mandatory that the VISIT_DETAIL table be filled in, but if you find that the logic to create VISIT_OCCURRENCE records includes the roll-up of multiple smaller records to create one picture of a Visit then it is a good idea to use VISIT_DETAIL. In EHR data, for example, a Person may be in the hospital but instead of one over-arching Visit their encounters are recorded as times they interacted with a health care provider. A Person in the hospital interacts with multiple providers multiple times a day so the encounters must be strung together using some heuristic (defined by the ETL) to identify the entire Visit. In this case the encounters would be considered Visit Details and the entire Visit would be the Visit Occurrence. In this example it is also possible to use the Vocabulary to distinguish Visit Details from a Visit Occurrence by setting the VISIT_CONCEPT_ID to [9201](https://athena.ohdsi.org/search-terms/terms/9201) and the VISIT_DETAIL_CONCEPT_IDs either to 9201 or its children to indicate where the patient was in the hospital at the time of care."
condition_occurrence,CDM,No,CONDITION_,Yes,0,NA,"This table contains records of Events of a Person suggesting the presence of a disease or medical condition stated as a diagnosis, a sign, or a symptom, which is either observed by a Provider or reported by the patient.","Conditions are defined by Concepts from the Condition domain, which form a complex hierarchy. As a result, the same Person with the same disease may have multiple Condition records, which belong to the same hierarchical family. Most Condition records are mapped from diagnostic codes, but recorded signs, symptoms and summary descriptions also contribute to this table. Rule out diagnoses should not be recorded in this table, but in reality their negating nature is not always captured in the source data, and other precautions must be taken when when identifying Persons who should suffer from the recorded Condition. Record all conditions as they exist in the source data. Any decisions about diagnosis/phenotype definitions would be done through cohort specifications. These cohorts can be housed in the [COHORT](https://ohdsi.github.io/CommonDataModel/cdm54.html#payer_plan_period) table. Conditions span a time interval from start to end, but are typically recorded as single snapshot records with no end date. The reason is twofold: (i) At the time of the recording the duration is not known and later not recorded, and (ii) the Persons typically cease interacting with the healthcare system when they feel better, which leads to incomplete capture of resolved Conditions. The [CONDITION_ERA](https://ohdsi.github.io/CommonDataModel/cdm54.html#condition_era) table addresses this issue. Family history and past diagnoses ('history of') are not recorded in this table. Instead, they are listed in the [OBSERVATION](https://ohdsi.github.io/CommonDataModel/cdm54.html#observation) table. Codes written in the process of establishing the diagnosis, such as 'question of' of and 'rule out', should not represented here. Instead, they should be recorded in the [OBSERVATION](https://ohdsi.github.io/CommonDataModel/cdm54.html#observation) table, if they are used for analyses. However, this information is not always available.",Source codes and source text fields mapped to Standard Concepts of the Condition Domain have to be recorded here.
drug_exposure,CDM,No,DRUG_,Yes,0,NA,"This table captures records about the exposure to a Drug ingested or otherwise introduced into the body. A Drug is a biochemical substance formulated in such a way that when administered to a Person it will exert a certain biochemical effect on the metabolism. Drugs include prescription and over-the-counter medicines, vaccines, and large-molecule biologic therapies. Radiological devices ingested or applied locally do not count as Drugs.","The purpose of records in this table is to indicate an exposure to a certain drug as best as possible. In this context a drug is defined as an active ingredient. Drug Exposures are defined by Concepts from the Drug domain, which form a complex hierarchy. As a result, one DRUG_SOURCE_CONCEPT_ID may map to multiple standard concept ids if it is a combination product. Records in this table represent prescriptions written, prescriptions dispensed, and drugs administered by a provider to name a few. The DRUG_TYPE_CONCEPT_ID can be used to find and filter on these types. This table includes additional information about the drug products, the quantity given, and route of administration.","Information about quantity and dose is provided in a variety of different ways and it is important for the ETL to provide as much information as possible from the data. Depending on the provenance of the data fields may be captured differently i.e. quantity for drugs administered may have a separate meaning from quantity for prescriptions dispensed. If a patient has multiple records on the same day for the same drug or procedures the ETL should not de-dupe them unless there is probable reason to believe the item is a true data duplicate. Take note on how to handle refills for prescriptions written.<br><br>For detailed conventions on how to populate this table, please refer to the [THEMIS repository](https://ohdsi.github.io/Themis/drug_exposure.html)."
procedure_occurrence,CDM,No,PROCEDURE_,Yes,0,NA,"This table contains records of activities or processes ordered by, or carried out by, a healthcare provider on the patient with a diagnostic or therapeutic purpose.","Lab tests are not a procedure, if something is observed with an expected resulting amount and unit then it should be a measurement. Phlebotomy is a procedure but so trivial that it tends to be rarely captured. It can be assumed that there is a phlebotomy procedure associated with many lab tests, therefore it is unnecessary to add them as separate procedures.","When dealing with duplicate records, the ETL must determine whether to sum them up into one record or keep them separate. Things to consider are:
- Same Procedure
- Same procedure_datetime
- Same Visit Occurrence or Visit Detail
- Same Provider
- Same Modifier for Procedures.
Source codes and source text fields mapped to Standard Concepts of the Procedure Domain have to be recorded here."
device_exposure,CDM,No,DEVICE_,Yes,0,NA,"The Device domain captures information about a person's exposure to a foreign physical object or instrument which is used for diagnostic or therapeutic purposes through a mechanism beyond chemical action. Devices include implantable objects (e.g. pacemakers, stents, artificial joints), medical equipment and supplies (e.g. bandages, crutches, syringes), other instruments used in medical procedures (e.g. sutures, defibrillators) and material used in clinical care (e.g. adhesives, body material, dental material, surgical material).","The distinction between Devices or supplies and Procedures are sometimes blurry, but the former are physical objects while the latter are actions, often to apply a Device or supply.",Source codes and source text fields mapped to Standard Concepts of the Device Domain have to be recorded here.
measurement,CDM,No,MEASUREMENT_,Yes,0,NA,"The MEASUREMENT table contains records of Measurements, i.e. structured values (numerical or categorical) obtained through systematic and standardized examination or testing of a Person or Person's sample. The MEASUREMENT table contains both orders and results of such Measurements as laboratory tests, vital signs, quantitative findings from pathology reports, etc. Measurements are stored as attribute value pairs, with the attribute as the Measurement Concept and the value representing the result. The value can be a Concept (stored in VALUE_AS_CONCEPT), or a numerical value (VALUE_AS_NUMBER) with a Unit (UNIT_CONCEPT_ID). The Procedure for obtaining the sample is housed in the PROCEDURE_OCCURRENCE table, though it is unnecessary to create a PROCEDURE_OCCURRENCE record for each measurement if one does not exist in the source data. Measurements differ from Observations in that they require a standardized test or some other activity to generate a quantitative or qualitative result. If there is no result, it is assumed that the lab test was conducted but the result was not captured.","Measurements are predominately lab tests with a few exceptions, like blood pressure or function tests. Results are given in the form of a value and unit combination. When investigating measurements, look for operator_concept_ids (<, >, etc.).","Only records where the source value maps to a Concept in the measurement domain should be included in this table. Even though each Measurement always has a result, the fields VALUE_AS_NUMBER and VALUE_AS_CONCEPT_ID are not mandatory as often the result is not given in the source data. When the result is not known, the Measurement record represents just the fact that the corresponding Measurement was carried out, which in itself is already useful information for some use cases. For some Measurement Concepts, the result is included in the test. For example, ICD10 CONCEPT_ID [45548980](https://athena.ohdsi.org/search-terms/terms/45548980) 'Abnormal level of unspecified serum enzyme' indicates a Measurement and the result (abnormal). In those situations, the CONCEPT_RELATIONSHIP table in addition to the 'Maps to' record contains a second record with the relationship_id set to 'Maps to value'. In this example, the 'Maps to' relationship directs to [4046263](https://athena.ohdsi.org/search-terms/terms/4046263) 'Enzyme measurement' as well as a 'Maps to value' record to [4135493](https://athena.ohdsi.org/search-terms/terms/4135493) 'Abnormal'."
observation,CDM,No,OBSERVATION_,Yes,0,NA,"The OBSERVATION table captures clinical facts about a Person obtained in the context of examination, questioning or a procedure. Any data that cannot be represented by any other domains, such as social and lifestyle facts, medical history, family history, etc. are recorded here.","Observations differ from Measurements in that they do not require a standardized test or some other activity to generate clinical fact. Typical observations are medical history, family history, the stated need for certain treatment, social circumstances, lifestyle choices, healthcare utilization patterns, etc. If the generation clinical facts requires a standardized testing such as lab testing or imaging and leads to a standardized result, the data item is recorded in the MEASUREMENT table. If the clinical fact observed determines a sign, symptom, diagnosis of a disease or other medical condition, it is recorded in the CONDITION_OCCURRENCE table. Valid Observation Concepts are not enforced to be from any domain but they must not belong to the Condition, Procedure, Drug, Device, Specimen, or Measurement domains and they must be Standard Concepts. <br><br>The observation table usually records the date or datetime of when the observation was obtained, not the date of the observation starting. For example, if the patient reports that they had a heart attack when they were 50, the observation date or datetime is the date of the report, the heart attack observation can have a value_as_concept which captures how long ago the observation applied to the patient.","Records whose Source Values map to any domain besides Condition, Procedure, Drug, Specimen, Measurement or Device should be stored in the Observation table. Observations can be stored as attribute value pairs, with the attribute as the Observation Concept and the value representing the clinical fact. This fact can be a Concept (stored in VALUE_AS_CONCEPT), a numerical value (VALUE_AS_NUMBER) or a verbatim string (VALUE_AS_STRING). Even though Observations do not have an explicit result, the clinical fact can be stated separately from the type of Observation in the VALUE_AS_* fields. It is recommended for Observations that are suggestive statements of positive assertion should have a value of 'Yes' (concept_id=4188539), recorded, even though the null value is the equivalent."
death,CDM,No,NA,No,NA,NA,"The death domain contains the clinical event for how and when a Person dies. A person can have up to one record if the source system contains evidence about the Death, such as: Condition in an administrative claim, status of enrollment into a health plan, or explicit record in EHR data.",NA,"For specific conventions on how to populate this table, please refer to the [THEMIS repository](https://ohdsi.github.io/Themis/death.html)."
note,CDM,No,NA,Yes,0,NA,"The NOTE table captures unstructured information that was recorded by a provider about a patient in free text (in ASCII, or preferably in UTF8 format) notes on a given date. The type of note_text is CLOB or varchar(MAX) depending on RDBMS.",NA,"HL7/LOINC CDO is a standard for consistent naming of documents to support a range of use cases: retrieval, organization, display, and exchange. It guides the creation of LOINC codes for clinical notes. CDO annotates each document with 5 dimensions:
- **Kind of Document**: Characterizes the general structure of the document at a macro level (e.g. Anesthesia Consent)
@ -34,21 +42,21 @@ note,CDM,No,NA,Yes,0,NA,"The NOTE table captures unstructured information that w
Each combination of these 5 dimensions rolls up to a unique LOINC code.
According to CDO requirements, only 2 of the 5 dimensions are required to properly annotate a document; Kind of Document and any one of the other 4 dimensions.
However, not all the permutations of the CDO dimensions will necessarily yield an existing LOINC code. Each of these dimensions are contained in the OMOP Vocabulary under the domain of 'Meas Value' with each dimension represented as a Concept Class."
note_nlp,CDM,No,NA,No,NA,NA,The NOTE_NLP table encodes all output of NLP on clinical notes. Each row represents a single extracted term from a note.,NA,NA
specimen,CDM,No,SPECIMEN_,Yes,0,NA,The specimen domain contains the records identifying biological samples from a person.,NA,"Anatomic site is coded at the most specific level of granularity possible, such that higher level classifications can be derived using the Standardized Vocabularies."
However, not all the permutations of the CDO dimensions will necessarily yield an existing LOINC code. Each of these dimensions are contained in the OMOP Vocabulary under the domain of 'Meas Value' with each dimension represented as a Concept Class."
note_nlp,CDM,No,NA,No,NA,NA,The NOTE_NLP table encodes all output of NLP on clinical notes. Each row represents a single extracted term from a note.,NA,NA
specimen,CDM,No,SPECIMEN_,Yes,0,NA,The specimen domain contains the records identifying biological samples from a person.,NA,"Anatomic site is coded at the most specific level of granularity possible, such that higher level classifications can be derived using the Standardized Vocabularies."
fact_relationship,CDM,No,NA,No,NA,NA,"The FACT_RELATIONSHIP table contains records about the relationships between facts stored as records in any table of the CDM. Relationships can be defined between facts from the same domain, or different domains. Examples of Fact Relationships include: [Person relationships](https://athena.ohdsi.org/search-terms/terms?domain=Relationship&standardConcept=Standard&page=2&pageSize=15&query=) (parent-child), care site relationships (hierarchical organizational structure of facilities within a health system), indication relationship (between drug exposures and associated conditions), usage relationships (of devices during the course of an associated procedure), or facts derived from one another (measurements derived from an associated specimen).",NA,"All relationships are directional, and each relationship is represented twice symmetrically within the FACT_RELATIONSHIP table. For example, two persons if person_id = 1 is the mother of person_id = 2 two records are in the FACT_RELATIONSHIP table (all strings in fact concept_id records in the Concept table:
- Person, 1, Person, 2, parent of
- Person, 2, Person, 1, child of"
location,CDM,No,NA,No,NA,NA,The LOCATION table represents a generic way to capture physical location or address information of Persons and Care Sites.,"The current iteration of the LOCATION table is US centric. Until a major release to correct this, certain fields can be used to represent different international values. <br><br> - STATE can also be used for province or district<br>- ZIP is also the postal code or postcode <br>- COUNTY can also be used to represent region","Each address or Location is unique and is present only once in the table. Locations do not contain names, such as the name of a hospital. In order to construct a full address that can be used in the postal service, the address information from the Location needs to be combined with information from the Care Site."
care_site,CDM,No,NA,No,NA,NA,"The CARE_SITE table contains a list of uniquely identified institutional (physical or organizational) units where healthcare delivery is practiced (offices, wards, hospitals, clinics, etc.).",NA,"Care site is a unique combination of location_id and nature of the site - the latter could be the place of service, name, or another characteristic in your source data. Care site does not take into account the provider (human) information such a specialty. Many source data do not make a distinction between individual and institutional providers. The CARE_SITE table contains the institutional providers. If the source, instead of uniquely identifying individual Care Sites, only provides limited information such as Place of Service, generic or ""pooled"" Care Site records are listed in the CARE_SITE table. There can be hierarchical and business relationships between Care Sites. For example, wards can belong to clinics or departments, which can in turn belong to hospitals, which in turn can belong to hospital systems, which in turn can belong to HMOs.The relationships between Care Sites are defined in the FACT_RELATIONSHIP table.<br><br>For additional detailed conventions on how to populate this table, please refer to [THEMIS repository](https://ohdsi.github.io/Themis/care_site.html)."
provider,CDM,No,NA,No,NA,NA,"The PROVIDER table contains a list of uniquely identified healthcare providers; duplication is not allowed. These are individuals providing hands-on healthcare to patients, such as physicians, nurses, midwives, physical therapists etc.","Many sources do not make a distinction between individual and institutional providers. The PROVIDER table contains the individual providers. If the source only provides limited information such as specialty instead of uniquely identifying individual providers, generic or 'pooled' Provider records are listed in the PROVIDER table.",NA
payer_plan_period,CDM,No,NA,Yes,0,NA,"The PAYER_PLAN_PERIOD table captures details of the period of time that a Person is continuously enrolled under a specific health Plan benefit structure from a given Payer. Each Person receiving healthcare is typically covered by a health benefit plan, which pays for (fully or partially), or directly provides, the care. These benefit plans are provided by payers, such as health insurances or state or government agencies. In each plan the details of the health benefits are defined for the Person or her family, and the health benefit Plan might change over time typically with increasing utilization (reaching certain cost thresholds such as deductibles), plan availability and purchasing choices of the Person. The unique combinations of Payer organizations, health benefit Plans and time periods in which they are valid for a Person are recorded in this table.","A Person can have multiple, overlapping, Payer_Plan_Periods in this table. For example, medical and drug coverage in the US can be represented by two Payer_Plan_Periods. The details of the benefit structure of the Plan is rarely known, the idea is just to identify that the Plans are different.",NA
- Person, 2, Person, 1, child of"
location,CDM,No,NA,No,NA,NA,The LOCATION table represents a generic way to capture physical location or address information of Persons and Care Sites.,"The current iteration of the LOCATION table is US centric. Until a major release to correct this, certain fields can be used to represent different international values. <br><br> - STATE can also be used for province or district<br>- ZIP is also the postal code or postcode <br>- COUNTY can also be used to represent region","Each address or Location is unique and is present only once in the table. Locations do not contain names, such as the name of a hospital. In order to construct a full address that can be used in the postal service, the address information from the Location needs to be combined with information from the Care Site."
care_site,CDM,No,NA,No,NA,NA,"The CARE_SITE table contains a list of uniquely identified institutional (physical or organizational) units where healthcare delivery is practiced (offices, wards, hospitals, clinics, etc.).",NA,"Care site is a unique combination of location_id and nature of the site - the latter could be the place of service, name, or another characteristic in your source data. Care site does not take into account the provider (human) information such a specialty. Many source data do not make a distinction between individual and institutional providers. The CARE_SITE table contains the institutional providers. If the source, instead of uniquely identifying individual Care Sites, only provides limited information such as Place of Service, generic or ""pooled"" Care Site records are listed in the CARE_SITE table. There can be hierarchical and business relationships between Care Sites. For example, wards can belong to clinics or departments, which can in turn belong to hospitals, which in turn can belong to hospital systems, which in turn can belong to HMOs.The relationships between Care Sites are defined in the FACT_RELATIONSHIP table.<br><br>For additional detailed conventions on how to populate this table, please refer to [THEMIS repository](https://ohdsi.github.io/Themis/care_site.html)."
provider,CDM,No,NA,No,NA,NA,"The PROVIDER table contains a list of uniquely identified healthcare providers; duplication is not allowed. These are individuals providing hands-on healthcare to patients, such as physicians, nurses, midwives, physical therapists etc.","Many sources do not make a distinction between individual and institutional providers. The PROVIDER table contains the individual providers. If the source only provides limited information such as specialty instead of uniquely identifying individual providers, generic or 'pooled' Provider records are listed in the PROVIDER table.",NA
payer_plan_period,CDM,No,NA,Yes,0,NA,"The PAYER_PLAN_PERIOD table captures details of the period of time that a Person is continuously enrolled under a specific health Plan benefit structure from a given Payer. Each Person receiving healthcare is typically covered by a health benefit plan, which pays for (fully or partially), or directly provides, the care. These benefit plans are provided by payers, such as health insurances or state or government agencies. In each plan the details of the health benefits are defined for the Person or her family, and the health benefit Plan might change over time typically with increasing utilization (reaching certain cost thresholds such as deductibles), plan availability and purchasing choices of the Person. The unique combinations of Payer organizations, health benefit Plans and time periods in which they are valid for a Person are recorded in this table.","A Person can have multiple, overlapping, Payer_Plan_Periods in this table. For example, medical and drug coverage in the US can be represented by two Payer_Plan_Periods. The details of the benefit structure of the Plan is rarely known, the idea is just to identify that the Plans are different.",NA
cost,CDM,No,NA,No,NA,NA,"The COST table captures records containing the cost of any medical event recorded in one of the OMOP clinical event tables such as DRUG_EXPOSURE, PROCEDURE_OCCURRENCE, VISIT_OCCURRENCE, VISIT_DETAIL, DEVICE_OCCURRENCE, OBSERVATION or MEASUREMENT.
Each record in the cost table account for the amount of money transacted for the clinical event. So, the COST table may be used to represent both receivables (charges) and payments (paid), each transaction type represented by its COST_CONCEPT_ID. The COST_TYPE_CONCEPT_ID field will use concepts in the Standardized Vocabularies to designate the source (provenance) of the cost data. A reference to the health plan information in the PAYER_PLAN_PERIOD table is stored in the record for information used for the adjudication system to determine the persons benefit for the clinical event.","When dealing with summary costs, the cost of the goods or services the provider provides is often not known directly, but derived from the hospital charges multiplied by an average cost-to-charge ratio.","One cost record is generated for each response by a payer. In a claims databases, the payment and payment terms reported by the payer for the goods or services billed will generate one cost record. If the source data has payment information for more than one payer (i.e. primary insurance and secondary insurance payment for one entity), then a cost record is created for each reporting payer. Therefore, it is possible for one procedure to have multiple cost records for each payer, but typically it contains one or no record per entity. Payer reimbursement cost records will be identified by using the PAYER_PLAN_ID field. Drug costs are composed of ingredient cost (the amount charged by the wholesale distributor or manufacturer), the dispensing fee (the amount charged by the pharmacy and the sales tax)."
drug_era,CDM,No,NA,Yes,0,NA,"A Drug Era is defined as a span of time when the Person is assumed to be exposed to a particular active ingredient. A Drug Era is not the same as a Drug Exposure: Exposures are individual records corresponding to the source when Drug was delivered to the Person, while successive periods of Drug Exposures are combined under certain rules to produce continuous Drug Eras. Every record in the DRUG_EXPOSURE table should be part of a drug era based on the dates of exposure. ",NA,The SQL script for generating DRUG_ERA records can be found [here](https://ohdsi.github.io/CommonDataModel/sqlScripts.html#drug_eras).
dose_era,CDM,No,NA,Yes,0,NA,A Dose Era is defined as a span of time when the Person is assumed to be exposed to a constant dose of a specific active ingredient.,NA,"Dose Eras will be derived from records in the DRUG_EXPOSURE table and the Dose information from the DRUG_STRENGTH table using a standardized algorithm. Dose Form information is not taken into account. So, if the patient changes between different formulations, or different manufacturers with the same formulation, the Dose Era is still spanning the entire time of exposure to the Ingredient."
Each record in the cost table account for the amount of money transacted for the clinical event. So, the COST table may be used to represent both receivables (charges) and payments (paid), each transaction type represented by its COST_CONCEPT_ID. The COST_TYPE_CONCEPT_ID field will use concepts in the Standardized Vocabularies to designate the source (provenance) of the cost data. A reference to the health plan information in the PAYER_PLAN_PERIOD table is stored in the record for information used for the adjudication system to determine the persons benefit for the clinical event.","When dealing with summary costs, the cost of the goods or services the provider provides is often not known directly, but derived from the hospital charges multiplied by an average cost-to-charge ratio.","One cost record is generated for each response by a payer. In a claims databases, the payment and payment terms reported by the payer for the goods or services billed will generate one cost record. If the source data has payment information for more than one payer (i.e. primary insurance and secondary insurance payment for one entity), then a cost record is created for each reporting payer. Therefore, it is possible for one procedure to have multiple cost records for each payer, but typically it contains one or no record per entity. Payer reimbursement cost records will be identified by using the PAYER_PLAN_ID field. Drug costs are composed of ingredient cost (the amount charged by the wholesale distributor or manufacturer), the dispensing fee (the amount charged by the pharmacy and the sales tax)."
drug_era,CDM,No,NA,Yes,0,NA,"A Drug Era is defined as a span of time when the Person is assumed to be exposed to a particular active ingredient. A Drug Era is not the same as a Drug Exposure: Exposures are individual records corresponding to the source when Drug was delivered to the Person, while successive periods of Drug Exposures are combined under certain rules to produce continuous Drug Eras. Every record in the DRUG_EXPOSURE table should be part of a drug era based on the dates of exposure. ",NA,The SQL script for generating DRUG_ERA records can be found [here](https://ohdsi.github.io/CommonDataModel/sqlScripts.html#drug_eras).
dose_era,CDM,No,NA,Yes,0,NA,A Dose Era is defined as a span of time when the Person is assumed to be exposed to a constant dose of a specific active ingredient.,NA,"Dose Eras will be derived from records in the DRUG_EXPOSURE table and the Dose information from the DRUG_STRENGTH table using a standardized algorithm. Dose Form information is not taken into account. So, if the patient changes between different formulations, or different manufacturers with the same formulation, the Dose Era is still spanning the entire time of exposure to the Ingredient."
condition_era,CDM,No,NA,Yes,0,NA,"A Condition Era is defined as a span of time when the Person is assumed to have a given condition. Similar to Drug Eras, Condition Eras are chronological periods of Condition Occurrence and every Condition Occurrence record should be part of a Condition Era. Combining individual Condition Occurrences into a single Condition Era serves two purposes:
- It allows aggregation of chronic conditions that require frequent ongoing care, instead of treating each Condition Occurrence as an independent event.
@ -56,25 +64,21 @@ condition_era,CDM,No,NA,Yes,0,NA,"A Condition Era is defined as a span of time w
For example, consider a Person who visits her Primary Care Physician (PCP) and who is referred to a specialist. At a later time, the Person visits the specialist, who confirms the PCP's original diagnosis and provides the appropriate treatment to resolve the condition. These two independent doctor visits should be aggregated into one Condition Era.",NA,"Each Condition Era corresponds to one or many Condition Occurrence records that form a continuous interval.
The condition_concept_id field contains Concepts that are identical to those of the CONDITION_OCCURRENCE table records that make up the Condition Era. In contrast to Drug Eras, Condition Eras are not aggregated to contain Conditions of different hierarchical layers. The SQl Script for generating CONDITION_ERA records can be found [here](https://ohdsi.github.io/CommonDataModel/sqlScripts.html#condition_eras)
The Condition Era Start Date is the start date of the first Condition Occurrence.
The Condition Era End Date is the end date of the last Condition Occurrence. Condition Eras are built with a Persistence Window of 30 days, meaning, if no occurrence of the same condition_concept_id happens within 30 days of any one occurrence, it will be considered the condition_era_end_date."
episode,CDM,No,NA,No,NA,NA,"The EPISODE table aggregates lower-level clinical events (VISIT_OCCURRENCE, DRUG_EXPOSURE, PROCEDURE_OCCURRENCE, DEVICE_EXPOSURE) into a higher-level abstraction representing clinically and analytically relevant disease phases,outcomes and treatments. The EPISODE_EVENT table connects qualifying clinical events (VISIT_OCCURRENCE, DRUG_EXPOSURE, PROCEDURE_OCCURRENCE, DEVICE_EXPOSURE) to the appropriate EPISODE entry. For example cancers including their development over time, their treatment, and final resolution.","Valid Episode Concepts belong to the 'Episode' domain. For cancer episodes please see [article], for non-cancer episodes please see [article]. If your source data does not have all episodes that are relevant to the therapeutic area, write only those you can easily derive from the data. It is understood that that table is not currently expected to be comprehensive.",NA
episode_event,CDM,No,NA,No,NA,NA,"The EPISODE_EVENT table connects qualifying clinical events (such as CONDITION_OCCURRENCE, DRUG_EXPOSURE, PROCEDURE_OCCURRENCE, MEASUREMENT) to the appropriate EPISODE entry. For example, linking the precise location of the metastasis (cancer modifier in MEASUREMENT) to the disease episode.",This connecting table is used instead of the FACT_RELATIONSHIP table for linking low-level events to abstracted Episodes.,"Some episodes may not have links to any underlying clinical events. For such episodes, the EPISODE_EVENT table is not populated."
metadata,CDM,No,NA,No,NA,NA,The METADATA table contains metadata information about a dataset that has been transformed to the OMOP Common Data Model.,NA,NA
cdm_source,CDM,No,NA,No,NA,NA,The CDM_SOURCE table contains detail about the source database and the process used to transform the data into the OMOP Common Data Model.,NA,NA
concept,VOCAB,No,NA,No,NA,NA,"The Standardized Vocabularies contains records, or Concepts, that uniquely identify each fundamental unit of meaning used to express clinical information in all domain tables of the CDM. Concepts are derived from vocabularies, which represent clinical information across a domain (e.g. conditions, drugs, procedures) through the use of codes and associated descriptions. Some Concepts are designated Standard Concepts, meaning these Concepts can be used as normative expressions of a clinical entity within the OMOP Common Data Model and standardized analytics. Each Standard Concept belongs to one Domain, which defines the location where the Concept would be expected to occur within the data tables of the CDM. Concepts can represent broad categories ('Cardiovascular disease'), detailed clinical elements ('Myocardial infarction of the anterolateral wall'), or modifying characteristics and attributes that define Concepts at various levels of detail (severity of a disease, associated morphology, etc.). Records in the Standardized Vocabularies tables are derived from national or international vocabularies such as SNOMED-CT, RxNorm, and LOINC, or custom OMOP Concepts defined to cover various aspects of observational data analysis.
","The primary purpose of the CONCEPT table is to provide a standardized representation of medical Concepts, allowing for consistent querying and analysis across the healthcare databases.
Users can join the CONCEPT table with other tables in the CDM to enrich clinical data with standardized Concept information or use the CONCEPT table as a reference for mapping clinical data from source terminologies to Standard Concepts.",NA
vocabulary,VOCAB,No,NA,No,NA,NA,The VOCABULARY table includes a list of the Vocabularies integrated from various sources or created de novo in OMOP CDM. This reference table contains a single record for each Vocabulary and includes a descriptive name and other associated attributes for the Vocabulary.,"The primary purpose of the VOCABULARY table is to provide explicit information about specific vocabulary versions and the references to the sources from which they are asserted. Users can identify the version of a particular vocabulary used in the database, enabling consistency and reproducibility in data analysis. Besides, users can check the vocabulary release version in their CDM which refers to the vocabulary_id = 'None'.",NA
domain,VOCAB,No,NA,No,NA,NA,"The DOMAIN table includes a list of OMOP-defined Domains to which the Concepts of the Standardized Vocabularies can belong. A Domain represents a clinical definition whereby we assign matching Concepts for the standardized fields in the CDM tables. For example, the Condition Domain contains Concepts that describe a patient condition, and these Concepts can only be used in the condition_concept_id field of the CONDITION_OCCURRENCE and CONDITION_ERA tables. This reference table is populated with a single record for each Domain, including a Domain ID and a descriptive name for every Domain.","Users can leverage the DOMAIN table to explore the full spectrum of health-related data Domains available in the Standardized Vocabularies. Also, the information in the DOMAIN table may be used as a reference for mapping source data to OMOP domains, facilitating data harmonization and interoperability.",NA
The Condition Era End Date is the end date of the last Condition Occurrence. Condition Eras are built with a Persistence Window of 30 days, meaning, if no occurrence of the same condition_concept_id happens within 30 days of any one occurrence, it will be considered the condition_era_end_date."
episode,CDM,No,NA,No,NA,NA,"The EPISODE table aggregates lower-level clinical events (VISIT_OCCURRENCE, DRUG_EXPOSURE, PROCEDURE_OCCURRENCE, DEVICE_EXPOSURE) into a higher-level abstraction representing clinically and analytically relevant disease phases,outcomes and treatments. The EPISODE_EVENT table connects qualifying clinical events (VISIT_OCCURRENCE, DRUG_EXPOSURE, PROCEDURE_OCCURRENCE, DEVICE_EXPOSURE) to the appropriate EPISODE entry. For example cancers including their development over time, their treatment, and final resolution.","Valid Episode Concepts belong to the 'Episode' domain. For cancer episodes please see [article], for non-cancer episodes please see [article]. If your source data does not have all episodes that are relevant to the therapeutic area, write only those you can easily derive from the data. It is understood that that table is not currently expected to be comprehensive.",NA
episode_event,CDM,No,NA,No,NA,NA,"The EPISODE_EVENT table connects qualifying clinical events (such as CONDITION_OCCURRENCE, DRUG_EXPOSURE, PROCEDURE_OCCURRENCE, MEASUREMENT) to the appropriate EPISODE entry. For example, linking the precise location of the metastasis (cancer modifier in MEASUREMENT) to the disease episode.",This connecting table is used instead of the FACT_RELATIONSHIP table for linking low-level events to abstracted Episodes.,"Some episodes may not have links to any underlying clinical events. For such episodes, the EPISODE_EVENT table is not populated."
metadata,CDM,No,NA,No,NA,NA,The METADATA table contains metadata information about a dataset that has been transformed to the OMOP Common Data Model.,NA,NA
cdm_source,CDM,No,NA,No,NA,NA,The CDM_SOURCE table contains detail about the source database and the process used to transform the data into the OMOP Common Data Model.,NA,NA
concept,VOCAB,No,NA,No,NA,NA,"The Standardized Vocabularies contains records, or Concepts, that uniquely identify each fundamental unit of meaning used to express clinical information in all domain tables of the CDM. Concepts are derived from vocabularies, which represent clinical information across a domain (e.g. conditions, drugs, procedures) through the use of codes and associated descriptions. Some Concepts are designated Standard Concepts, meaning these Concepts can be used as normative expressions of a clinical entity within the OMOP Common Data Model and standardized analytics. Each Standard Concept belongs to one Domain, which defines the location where the Concept would be expected to occur within the data tables of the CDM. Concepts can represent broad categories ('Cardiovascular disease'), detailed clinical elements ('Myocardial infarction of the anterolateral wall'), or modifying characteristics and attributes that define Concepts at various levels of detail (severity of a disease, associated morphology, etc.). Records in the Standardized Vocabularies tables are derived from national or international vocabularies such as SNOMED-CT, RxNorm, and LOINC, or custom OMOP Concepts defined to cover various aspects of observational data analysis.","The primary purpose of the CONCEPT table is to provide a standardized representation of medical Concepts, allowing for consistent querying and analysis across the healthcare databases. Users can join the CONCEPT table with other tables in the CDM to enrich clinical data with standardized Concept information or use the CONCEPT table as a reference for mapping clinical data from source terminologies to Standard Concepts.",NA
vocabulary,VOCAB,No,NA,No,NA,NA,The VOCABULARY table includes a list of the Vocabularies integrated from various sources or created de novo in OMOP CDM. This reference table contains a single record for each Vocabulary and includes a descriptive name and other associated attributes for the Vocabulary.,"The primary purpose of the VOCABULARY table is to provide explicit information about specific vocabulary versions and the references to the sources from which they are asserted. Users can identify the version of a particular vocabulary used in the database, enabling consistency and reproducibility in data analysis. Besides, users can check the vocabulary release version in their CDM which refers to the vocabulary_id = 'None'.",NA
domain,VOCAB,No,NA,No,NA,NA,"The DOMAIN table includes a list of OMOP-defined Domains to which the Concepts of the Standardized Vocabularies can belong. A Domain represents a clinical definition whereby we assign matching Concepts for the standardized fields in the CDM tables. For example, the Condition Domain contains Concepts that describe a patient condition, and these Concepts can only be used in the condition_concept_id field of the CONDITION_OCCURRENCE and CONDITION_ERA tables. This reference table is populated with a single record for each Domain, including a Domain ID and a descriptive name for every Domain.","Users can leverage the DOMAIN table to explore the full spectrum of health-related data Domains available in the Standardized Vocabularies. Also, the information in the DOMAIN table may be used as a reference for mapping source data to OMOP domains, facilitating data harmonization and interoperability.",NA
concept_class,VOCAB,No,NA,No,NA,NA,"The CONCEPT_CLASS table includes semantic categories that reference the source structure of each Vocabulary. Concept Classes represent so-called horizontal (e.g. MedDRA, RxNorm) or vertical levels (e.g. SNOMED) of the vocabulary structure. Vocabularies without any Concept Classes, such as HCPCS, use the vocabulary_id as the Concept Class. This reference table is populated with a single record for each Concept Class, which includes a Concept Class ID and a fully specified Concept Class name.
",Users can utilize the CONCEPT_CLASS table to explore the different classes or categories of concepts within the OHDSI vocabularies.,NA
concept_relationship,VOCAB,No,NA,No,NA,NA,"The CONCEPT_RELATIONSHIP table contains records that define relationships between any two Concepts and the nature or type of the relationship. This table captures various types of relationships, including hierarchical, associative, and other semantic connections, enabling comprehensive analysis and interpretation of clinical concepts. Every kind of relationship is defined in the RELATIONSHIP table.","The CONCEPT_RELATIONSHIP table can be used to explore hierarchical or attribute relationships between concepts to understand the hierarchical structure of clinical concepts and uncover implicit connections and associations within healthcare data. For example, users can utilize mapping relationships ('Maps to') to harmonize data from different sources and terminologies, enabling interoperability and data integration across disparate datasets.",NA
relationship,VOCAB,No,NA,No,NA,NA,The RELATIONSHIP table provides a reference list of all types of relationships that can be used to associate any two concepts in the CONCEPT_RELATIONSHP table.,NA,NA
concept_synonym,VOCAB,No,NA,No,NA,NA,The CONCEPT_SYNONYM table is used to store alternate names and descriptions for Concepts.,NA,NA
concept_ancestor,VOCAB,No,NA,No,NA,NA,"The CONCEPT_ANCESTOR table is designed to simplify observational analysis by providing the complete hierarchical relationships between Concepts. Only direct parent-child relationships between Concepts are stored in the CONCEPT_RELATIONSHIP table. To determine higher level ancestry connections, all individual direct relationships would have to be navigated at analysis time. The CONCEPT_ANCESTOR table includes records for all parent-child relationships, as well as grandparent-grandchild relationships and those of any other level of lineage. Using the CONCEPT_ANCESTOR table allows for querying for all descendants of a hierarchical concept. For example, drug ingredients and drug products are all descendants of a drug class ancestor.
This table is entirely derived from the CONCEPT, CONCEPT_RELATIONSHIP and RELATIONSHIP tables.",NA,NA
source_to_concept_map,VOCAB,No,NA,No,NA,NA,"The source to concept map table is recommended for use in ETL processes to maintain local source codes which are not available as Concepts in the Standardized Vocabularies, and to establish mappings for each source code into a Standard Concept as target_concept_ids that can be used to populate the Common Data Model tables. The SOURCE_TO_CONCEPT_MAP table is no longer populated with content within the Standardized Vocabularies published to the OMOP community. **There are OHDSI tools to help you populate this table; [Usagi](https://github.com/OHDSI/Usagi) and [Perseus](https://github.com/ohdsi/Perseus). You can read more about OMOP vocabulary mapping in [The Book of OHDSI Chapter 6.3](https://ohdsi.github.io/TheBookOfOhdsi/ExtractTransformLoad.html#step-2-create-the-code-mappings).**",NA,NA
drug_strength,VOCAB,No,NA,No,NA,NA,The DRUG_STRENGTH table contains structured content about the amount or concentration and associated units of a specific ingredient contained within a particular drug product. This table is supplemental information to support standardized analysis of drug utilization.,NA,NA
cohort,RESULTS,No,NA,No,NA,NA,"The subject of a cohort can have multiple, discrete records in the cohort table per cohort_definition_id, subject_id, and non-overlapping time periods. The definition of the cohort is contained within the COHORT_DEFINITION table. It is listed as part of the RESULTS schema because it is a table that users of the database as well as tools such as ATLAS need to be able to write to. The CDM and Vocabulary tables are all read-only so it is suggested that the COHORT and COHORT_DEFINTION tables are kept in a separate schema to alleviate confusion.",NA,"Cohorts typically include patients diagnosed with a specific condition, patients exposed to a particular drug, but can also be Providers who have performed a specific Procedure. Cohort records must have a Start Date and an End Date, but the End Date may be set to Start Date or could have an applied censor date using the Observation Period Start Date. Cohort records must contain a Subject Id, which can refer to the Person, Provider, Visit record or Care Site though they are most often Person Ids. The Cohort Definition will define the type of subject through the subject concept id. A subject can belong (or not belong) to a cohort at any moment in time. A subject can only have one record in the cohort table for any moment of time, i.e. it is not possible for a person to contain multiple records indicating cohort membership that are overlapping in time"
",Users can utilize the CONCEPT_CLASS table to explore the different classes or categories of concepts within the OHDSI vocabularies.,NA
concept_relationship,VOCAB,No,NA,No,NA,NA,"The CONCEPT_RELATIONSHIP table contains records that define relationships between any two Concepts and the nature or type of the relationship. This table captures various types of relationships, including hierarchical, associative, and other semantic connections, enabling comprehensive analysis and interpretation of clinical concepts. Every kind of relationship is defined in the RELATIONSHIP table.","The CONCEPT_RELATIONSHIP table can be used to explore hierarchical or attribute relationships between concepts to understand the hierarchical structure of clinical concepts and uncover implicit connections and associations within healthcare data. For example, users can utilize mapping relationships ('Maps to') to harmonize data from different sources and terminologies, enabling interoperability and data integration across disparate datasets.",NA
relationship,VOCAB,No,NA,No,NA,NA,"The RELATIONSHIP table provides a reference list of all types of relationships that can be used to associate any two Concepts in the CONCEPT_RELATIONSHIP table, the respective reverse relationships, and their hierarchical characteristics. Note, that Concepts representing relationships between the clinical facts, used for filling in the FACT_RELATIONSHIP table are stored in the CONCEPT table and belong to the Relationship Domain.","Users can leverage the RELATIONSHIP table to explore the full list of direct and reverse relationships within the OMOP vocabulary system. Also, users can get insight into how these relationships can be used in ETL, cohort creation, and other tasks according to their ancestral characteristics.",NA
concept_synonym,VOCAB,No,NA,No,NA,NA,"The CONCEPT_SYNONYM table captures alternative terms, synonyms, and translations of Concept Name into various languages linked to specific concepts, providing users with a comprehensive view of how Concepts may be expressed or referenced.","Users can leverage the CONCEPT_SYNONYM table to expand search capabilities and improve query accuracy by incorporating synonymous terms into data analysis and retrieval processes. Also, users can enhance their mapping efforts between local terminologies and standardized concepts by identifying synonymous terms associated with concepts in the CONCEPT_SYNONYM table.",NA
concept_ancestor,VOCAB,No,NA,No,NA,NA,"The CONCEPT_ANCESTOR table is designed to simplify observational analysis by providing the complete hierarchical relationships between Concepts. Only direct parent-child relationships between Concepts are stored in the CONCEPT_RELATIONSHIP table. To determine higher-level ancestry connections, all individual direct relationships would have to be navigated at analysis time. The CONCEPT_ANCESTOR table includes records for all parent-child relationships, as well as grandparent-grandchild relationships and those of any other level of lineage for Standard or Classification concepts. Using the CONCEPT_ANCESTOR table allows for querying for all descendants of a hierarchical concept, and the other way around. For example, drug ingredients and drug products, beneath them in the hierarchy, are all descendants of a drug class ancestor. This table is entirely derived from the CONCEPT, CONCEPT_RELATIONSHIP, and RELATIONSHIP tables.","The CONCEPT_ANCESTOR table can be used to explore the hierarchical relationships captured in the table to gain insights into the hierarchical structure of clinical concepts. Understanding the hierarchical relationships of concepts can facilitate accurate interpretation and analysis of healthcare data. Also, by incorporating hierarchical relationships from the CONCEPT_ANCESTOR table, users can create cohorts containing related concepts within a hierarchical structure, enabling more comprehensive cohort definitions.",NA
source_to_concept_map,VOCAB,No,NA,No,NA,NA,"The source to concept map table is recommended for use in ETL processes to maintain local source codes which are not available as Concepts in the Standardized Vocabularies, and to establish mappings for each source code into a Standard Concept as target_concept_ids that can be used to populate the Common Data Model tables. The SOURCE_TO_CONCEPT_MAP table is no longer populated with content within the Standardized Vocabularies published to the OMOP community. **There are OHDSI tools to help you populate this table; [Usagi](https://github.com/OHDSI/Usagi) and [Perseus](https://github.com/ohdsi/Perseus). You can read more about OMOP vocabulary mapping in [The Book of OHDSI Chapter 6.3](https://ohdsi.github.io/TheBookOfOhdsi/ExtractTransformLoad.html#step-2-create-the-code-mappings).**",NA,NA
drug_strength,VOCAB,No,NA,No,NA,NA,The DRUG_STRENGTH table contains structured content about the amount or concentration and associated units of a specific ingredient contained within a particular drug product. This table is supplemental information to support standardized analysis of drug utilization.,NA,NA
cohort,RESULTS,No,NA,No,NA,NA,"The subject of a cohort can have multiple, discrete records in the cohort table per cohort_definition_id, subject_id, and non-overlapping time periods. The definition of the cohort is contained within the COHORT_DEFINITION table. It is listed as part of the RESULTS schema because it is a table that users of the database as well as tools such as ATLAS need to be able to write to. The CDM and Vocabulary tables are all read-only so it is suggested that the COHORT and COHORT_DEFINTION tables are kept in a separate schema to alleviate confusion.",NA,"Cohorts typically include patients diagnosed with a specific condition, patients exposed to a particular drug, but can also be Providers who have performed a specific Procedure. Cohort records must have a Start Date and an End Date, but the End Date may be set to Start Date or could have an applied censor date using the Observation Period Start Date. Cohort records must contain a Subject Id, which can refer to the Person, Provider, Visit record or Care Site though they are most often Person Ids. The Cohort Definition will define the type of subject through the subject concept id. A subject can belong (or not belong) to a cohort at any moment in time. A subject can only have one record in the cohort table for any moment of time, i.e. it is not possible for a person to contain multiple records indicating cohort membership that are overlapping in time"
cohort_definition,RESULTS,No,NA,No,NA,NA,"The COHORT_DEFINITION table contains records defining a Cohort derived from the data through the associated description and syntax and upon instantiation (execution of the algorithm) placed into the COHORT table. Cohorts are a set of subjects that satisfy a given combination of inclusion criteria for a duration of time. The COHORT_DEFINITION table provides a standardized structure for maintaining the rules governing the inclusion of a subject into a cohort, and can store operational programming code to instantiate the cohort within the OMOP Common Data Model.",NA,NA
1 cdmTableName schema isRequired conceptPrefix measurePersonCompleteness measurePersonCompletenessThreshold validation tableDescription userGuidance etlConventions
2 person CDM Yes NA No NA NA This table serves as the central identity management for all Persons in the database. It contains records that uniquely identify each person or patient, and some demographic information. All records in this table are independent Persons. All Persons in a database needs one record in this table, unless they fail data quality requirements specified in the ETL. Persons with no Events should have a record nonetheless. If more than one data source contributes Events to the database, Persons must be reconciled, if possible, across the sources to create one single record per Person. The content of the BIRTH_DATETIME must be equivalent to the content of BIRTH_DAY, BIRTH_MONTH and BIRTH_YEAR.<br><br>For detailed conventions for how to populate this table, please refer to the [THEMIS repository](https://ohdsi.github.io/Themis/person.html).
3 observation_period CDM Yes NA Yes 0 NA This table contains records which define spans of time during which two conditions are expected to hold: (i) Clinical Events that happened to the Person are recorded in the Event tables, and (ii) absence of records indicate such Events did not occur during this span of time. For each Person, one or more OBSERVATION_PERIOD records may be present, but they will not overlap or be back to back to each other. Events may exist outside all of the time spans of the OBSERVATION_PERIOD records for a patient, however, absence of an Event outside these time spans cannot be construed as evidence of absence of an Event. Incidence or prevalence rates should only be calculated for the time of active OBSERVATION_PERIOD records. When constructing cohorts, outside Events can be used for inclusion criteria definition, but without any guarantee for the performance of these criteria. Also, OBSERVATION_PERIOD records can be as short as a single day, greatly disturbing the denominator of any rate calculation as part of cohort characterizations. To avoid that, apply minimal observation time as a requirement for any cohort definition. Each Person needs to have at least one OBSERVATION_PERIOD record, which should represent time intervals with a high capture rate of Clinical Events. Some source data have very similar concepts, such as enrollment periods in insurance claims data. In other source data such as most EHR systems these time spans need to be inferred under a set of assumptions. It is the discretion of the ETL developer to define these assumptions. In many ETL solutions the start date of the first occurrence or the first high quality occurrence of a Clinical Event (Condition, Drug, Procedure, Device, Measurement, Visit) is defined as the start of the OBSERVATION_PERIOD record, and the end date of the last occurrence of last high quality occurrence of a Clinical Event, or the end of the database period becomes the end of the OBSERVATOIN_PERIOD for each Person. If a Person only has a single Clinical Event the OBSERVATION_PERIOD record can be as short as one day. Depending on these definitions it is possible that Clinical Events fall outside the time spans defined by OBSERVATION_PERIOD records. Family history or history of Clinical Events generally are not used to generate OBSERVATION_PERIOD records around the time they are referring to. Any two overlapping or adjacent OBSERVATION_PERIOD records have to be merged into one. Each Person needs to have at least one OBSERVATION_PERIOD record, which should represent time intervals with a high capture rate of Clinical Events. Some source data have very similar concepts, such as enrollment periods in insurance claims data. In other source data such as most EHR systems these time spans need to be inferred under a set of assumptions. It is the discretion of the ETL developer to define these assumptions. In many ETL solutions the start date of the first occurrence or the first high quality occurrence of a Clinical Event (Condition, Drug, Procedure, Device, Measurement, Visit) is defined as the start of the OBSERVATION_PERIOD record, and the end date of the last occurrence of last high quality occurrence of a Clinical Event, or the end of the database period becomes the end of the OBSERVATION_PERIOD for each Person. If a Person only has a single Clinical Event the OBSERVATION_PERIOD record can be as short as one day. Depending on these definitions it is possible that Clinical Events fall outside the time spans defined by OBSERVATION_PERIOD records. Family history or history of Clinical Events generally are not used to generate OBSERVATION_PERIOD records around the time they are referring to. Any two overlapping or adjacent OBSERVATION_PERIOD records have to be merged into one.
4 visit_occurrence CDM No VISIT_ Yes 0 NA This table contains Events where Persons engage with the healthcare system for a duration of time. They are often also called "Encounters". Visits are defined by a configuration of circumstances under which they occur, such as (i) whether the patient comes to a healthcare institution, the other way around, or the interaction is remote, (ii) whether and what kind of trained medical staff is delivering the service during the Visit, and (iii) whether the Visit is transient or for a longer period involving a stay in bed. The configuration defining the Visit are described by Concepts in the Visit Domain, which form a hierarchical structure, but rolling up to generally familiar Visits adopted in most healthcare systems worldwide: - [Inpatient Visit](https://athena.ohdsi.org/search-terms/terms/9201): Person visiting hospital, at a Care Site, in bed, for duration of more than one day, with physicians and other Providers permanently available to deliver service around the clock - [Emergency Room Visit](https://athena.ohdsi.org/search-terms/terms/9203): Person visiting dedicated healthcare institution for treating emergencies, at a Care Site, within one day, with physicians and Providers permanently available to deliver service around the clock - [Emergency Room and Inpatient Visit](https://athena.ohdsi.org/search-terms/terms/262): Person visiting ER followed by a subsequent Inpatient Visit, where Emergency department is part of hospital, and transition from the ER to other hospital departments is undefined - [Non-hospital institution Visit](https://athena.ohdsi.org/search-terms/terms/42898160): Person visiting dedicated institution for reasons of poor health, at a Care Site, long-term or permanently, with no physician but possibly other Providers permanently available to deliver service around the clock - [Outpatient Visit](https://athena.ohdsi.org/search-terms/terms/9202): Person visiting dedicated ambulatory healthcare institution, at a Care Site, within one day, without bed, with physicians or medical Providers delivering service during Visit - [Home Visit](https://athena.ohdsi.org/search-terms/terms/581476): Provider visiting Person, without a Care Site, within one day, delivering service - [Telehealth Visit](https://athena.ohdsi.org/search-terms/terms/5083): Patient engages with Provider through communication media - [Pharmacy Visit](https://athena.ohdsi.org/search-terms/terms/581458): Person visiting pharmacy for dispensing of Drug, at a Care Site, within one day - [Laboratory Visit](https://athena.ohdsi.org/search-terms/terms/32036): Patient visiting dedicated institution, at a Care Site, within one day, for the purpose of a Measurement. - [Ambulance Visit](https://athena.ohdsi.org/search-terms/terms/581478): Person using transportation service for the purpose of initiating one of the other Visits, without a Care Site, within one day, potentially with Providers accompanying the Visit and delivering service - [Case Management Visit](https://athena.ohdsi.org/search-terms/terms/38004193): Person interacting with healthcare system, without a Care Site, within a day, with no Providers involved, for administrative purposes The Visit duration, or 'length of stay', is defined as VISIT_END_DATE - VISIT_START_DATE. For all Visits this is <1 day, except Inpatient Visits and Non-hospital institution Visits. The CDM also contains the VISIT_DETAIL table where additional information about the Visit is stored, for example, transfers between units during an inpatient Visit. Visits can be derived easily if the source data contain coding systems for Place of Service or Procedures, like CPT codes for well visits. In those cases, the codes can be looked up and mapped to a Standard Visit Concept. Otherwise, Visit Concepts have to be identified in the ETL process. This table will contain concepts in the Visit domain. These concepts are arranged in a hierarchical structure to facilitate cohort definitions by rolling up to generally familiar Visits adopted in most healthcare systems worldwide. Visits can be adjacent to each other, i.e. the end date of one can be identical with the start date of the other. As a consequence, more than one-day Visits or their descendants can be recorded for the same day. Multi-day visits must not overlap, i.e. share days other than start and end days. It is often the case that some logic should be written for how to define visits and how to assign Visit_Concept_Id. For example, in US claims outpatient visits that appear to occur within the time period of an inpatient visit can be rolled into one with the same Visit_Occurrence_Id. In EHR data inpatient visits that are within one day of each other may be strung together to create one visit. It will all depend on the source data and how encounter records should be translated to visit occurrences. Providers can be associated with a Visit through the PROVIDER_ID field, or indirectly through PROCEDURE_OCCURRENCE records linked both to the VISIT and PROVIDER tables.
5 visit_detail CDM No VISIT_DETAIL_ Yes 0 NA The VISIT_DETAIL table is an optional table used to represents details of each record in the parent VISIT_OCCURRENCE table. A good example of this would be the movement between units in a hospital during an inpatient stay or claim lines associated with a one insurance claim. For every record in the VISIT_OCCURRENCE table there may be 0 or more records in the VISIT_DETAIL table with a 1:n relationship where n may be 0. The VISIT_DETAIL table is structurally very similar to VISIT_OCCURRENCE table and belongs to the visit domain. The configuration defining the Visit Detail is described by Concepts in the Visit Domain, which form a hierarchical structure. The Visit Detail record will have an associated to the Visit Occurrence record in two ways: <br> 1. The Visit Detail record will have the VISIT_OCCURRENCE_ID it is associated to 2. The VISIT_DETAIL_CONCEPT_ID will be a descendant of the VISIT_CONCEPT_ID for the Visit. It is not mandatory that the VISIT_DETAIL table be filled in, but if you find that the logic to create VISIT_OCCURRENCE records includes the roll-up of multiple smaller records to create one picture of a Visit then it is a good idea to use VISIT_DETAIL. In EHR data, for example, a Person may be in the hospital but instead of one over-arching Visit their encounters are recorded as times they interacted with a health care provider. A Person in the hospital interacts with multiple providers multiple times a day so the encounters must be strung together using some heuristic (defined by the ETL) to identify the entire Visit. In this case the encounters would be considered Visit Details and the entire Visit would be the Visit Occurrence. In this example it is also possible to use the Vocabulary to distinguish Visit Details from a Visit Occurrence by setting the VISIT_CONCEPT_ID to [9201](https://athena.ohdsi.org/search-terms/terms/9201) and the VISIT_DETAIL_CONCEPT_IDs either to 9201 or its children to indicate where the patient was in the hospital at the time of care.
6 condition_occurrence CDM No CONDITION_ Yes 0 NA This table contains records of Events of a Person suggesting the presence of a disease or medical condition stated as a diagnosis, a sign, or a symptom, which is either observed by a Provider or reported by the patient. Conditions are defined by Concepts from the Condition domain, which form a complex hierarchy. As a result, the same Person with the same disease may have multiple Condition records, which belong to the same hierarchical family. Most Condition records are mapped from diagnostic codes, but recorded signs, symptoms and summary descriptions also contribute to this table. Rule out diagnoses should not be recorded in this table, but in reality their negating nature is not always captured in the source data, and other precautions must be taken when when identifying Persons who should suffer from the recorded Condition. Record all conditions as they exist in the source data. Any decisions about diagnosis/phenotype definitions would be done through cohort specifications. These cohorts can be housed in the [COHORT](https://ohdsi.github.io/CommonDataModel/cdm531.html#payer_plan_period) table. Conditions span a time interval from start to end, but are typically recorded as single snapshot records with no end date. The reason is twofold: (i) At the time of the recording the duration is not known and later not recorded, and (ii) the Persons typically cease interacting with the healthcare system when they feel better, which leads to incomplete capture of resolved Conditions. The [CONDITION_ERA](https://ohdsi.github.io/CommonDataModel/cdm531.html#condition_era) table addresses this issue. Family history and past diagnoses ('history of') are not recorded in this table. Instead, they are listed in the [OBSERVATION](https://ohdsi.github.io/CommonDataModel/cdm531.html#observation) table. Codes written in the process of establishing the diagnosis, such as 'question of' of and 'rule out', should not represented here. Instead, they should be recorded in the [OBSERVATION](https://ohdsi.github.io/CommonDataModel/cdm531.html#observation) table, if they are used for analyses. However, this information is not always available. Conditions are defined by Concepts from the Condition domain, which form a complex hierarchy. As a result, the same Person with the same disease may have multiple Condition records, which belong to the same hierarchical family. Most Condition records are mapped from diagnostic codes, but recorded signs, symptoms and summary descriptions also contribute to this table. Rule out diagnoses should not be recorded in this table, but in reality their negating nature is not always captured in the source data, and other precautions must be taken when when identifying Persons who should suffer from the recorded Condition. Record all conditions as they exist in the source data. Any decisions about diagnosis/phenotype definitions would be done through cohort specifications. These cohorts can be housed in the [COHORT](https://ohdsi.github.io/CommonDataModel/cdm54.html#payer_plan_period) table. Conditions span a time interval from start to end, but are typically recorded as single snapshot records with no end date. The reason is twofold: (i) At the time of the recording the duration is not known and later not recorded, and (ii) the Persons typically cease interacting with the healthcare system when they feel better, which leads to incomplete capture of resolved Conditions. The [CONDITION_ERA](https://ohdsi.github.io/CommonDataModel/cdm54.html#condition_era) table addresses this issue. Family history and past diagnoses ('history of') are not recorded in this table. Instead, they are listed in the [OBSERVATION](https://ohdsi.github.io/CommonDataModel/cdm54.html#observation) table. Codes written in the process of establishing the diagnosis, such as 'question of' of and 'rule out', should not represented here. Instead, they should be recorded in the [OBSERVATION](https://ohdsi.github.io/CommonDataModel/cdm54.html#observation) table, if they are used for analyses. However, this information is not always available. Source codes and source text fields mapped to Standard Concepts of the Condition Domain have to be recorded here.
15 specimen CDM No SPECIMEN_ Yes 0 NA The specimen domain contains the records identifying biological samples from a person. NA Anatomic site is coded at the most specific level of granularity possible, such that higher level classifications can be derived using the Standardized Vocabularies.
16 fact_relationship CDM No NA No NA NA The FACT_RELATIONSHIP table contains records about the relationships between facts stored as records in any table of the CDM. Relationships can be defined between facts from the same domain, or different domains. Examples of Fact Relationships include: [Person relationships](https://athena.ohdsi.org/search-terms/terms?domain=Relationship&standardConcept=Standard&page=2&pageSize=15&query=) (parent-child), care site relationships (hierarchical organizational structure of facilities within a health system), indication relationship (between drug exposures and associated conditions), usage relationships (of devices during the course of an associated procedure), or facts derived from one another (measurements derived from an associated specimen). NA All relationships are directional, and each relationship is represented twice symmetrically within the FACT_RELATIONSHIP table. For example, two persons if person_id = 1 is the mother of person_id = 2 two records are in the FACT_RELATIONSHIP table (all strings in fact concept_id records in the Concept table: - Person, 1, Person, 2, parent of - Person, 2, Person, 1, child of
17 location CDM No NA No NA NA The LOCATION table represents a generic way to capture physical location or address information of Persons and Care Sites. The current iteration of the LOCATION table is US centric. Until a major release to correct this, certain fields can be used to represent different international values. <br><br> - STATE can also be used for province or district<br>- ZIP is also the postal code or postcode <br>- COUNTY can also be used to represent region Each address or Location is unique and is present only once in the table. Locations do not contain names, such as the name of a hospital. In order to construct a full address that can be used in the postal service, the address information from the Location needs to be combined with information from the Care Site.
18 care_site CDM No NA No NA NA The CARE_SITE table contains a list of uniquely identified institutional (physical or organizational) units where healthcare delivery is practiced (offices, wards, hospitals, clinics, etc.). NA Care site is a unique combination of location_id and nature of the site - the latter could be the place of service, name, or another characteristic in your source data. Care site does not take into account the provider (human) information such a specialty. Many source data do not make a distinction between individual and institutional providers. The CARE_SITE table contains the institutional providers. If the source, instead of uniquely identifying individual Care Sites, only provides limited information such as Place of Service, generic or "pooled" Care Site records are listed in the CARE_SITE table. There can be hierarchical and business relationships between Care Sites. For example, wards can belong to clinics or departments, which can in turn belong to hospitals, which in turn can belong to hospital systems, which in turn can belong to HMOs.The relationships between Care Sites are defined in the FACT_RELATIONSHIP table.<br><br>For additional detailed conventions on how to populate this table, please refer to [THEMIS repository](https://ohdsi.github.io/Themis/care_site.html).
19 provider CDM No NA No NA NA The PROVIDER table contains a list of uniquely identified healthcare providers; duplication is not allowed. These are individuals providing hands-on healthcare to patients, such as physicians, nurses, midwives, physical therapists etc. Many sources do not make a distinction between individual and institutional providers. The PROVIDER table contains the individual providers. If the source only provides limited information such as specialty instead of uniquely identifying individual providers, generic or 'pooled' Provider records are listed in the PROVIDER table. NA
20 payer_plan_period CDM No NA Yes 0 NA The PAYER_PLAN_PERIOD table captures details of the period of time that a Person is continuously enrolled under a specific health Plan benefit structure from a given Payer. Each Person receiving healthcare is typically covered by a health benefit plan, which pays for (fully or partially), or directly provides, the care. These benefit plans are provided by payers, such as health insurances or state or government agencies. In each plan the details of the health benefits are defined for the Person or her family, and the health benefit Plan might change over time typically with increasing utilization (reaching certain cost thresholds such as deductibles), plan availability and purchasing choices of the Person. The unique combinations of Payer organizations, health benefit Plans and time periods in which they are valid for a Person are recorded in this table. A Person can have multiple, overlapping, Payer_Plan_Periods in this table. For example, medical and drug coverage in the US can be represented by two Payer_Plan_Periods. The details of the benefit structure of the Plan is rarely known, the idea is just to identify that the Plans are different. NA
21 cost CDM No NA No NA NA The COST table captures records containing the cost of any medical event recorded in one of the OMOP clinical event tables such as DRUG_EXPOSURE, PROCEDURE_OCCURRENCE, VISIT_OCCURRENCE, VISIT_DETAIL, DEVICE_OCCURRENCE, OBSERVATION or MEASUREMENT. Each record in the cost table account for the amount of money transacted for the clinical event. So, the COST table may be used to represent both receivables (charges) and payments (paid), each transaction type represented by its COST_CONCEPT_ID. The COST_TYPE_CONCEPT_ID field will use concepts in the Standardized Vocabularies to designate the source (provenance) of the cost data. A reference to the health plan information in the PAYER_PLAN_PERIOD table is stored in the record for information used for the adjudication system to determine the persons benefit for the clinical event. When dealing with summary costs, the cost of the goods or services the provider provides is often not known directly, but derived from the hospital charges multiplied by an average cost-to-charge ratio. One cost record is generated for each response by a payer. In a claims databases, the payment and payment terms reported by the payer for the goods or services billed will generate one cost record. If the source data has payment information for more than one payer (i.e. primary insurance and secondary insurance payment for one entity), then a cost record is created for each reporting payer. Therefore, it is possible for one procedure to have multiple cost records for each payer, but typically it contains one or no record per entity. Payer reimbursement cost records will be identified by using the PAYER_PLAN_ID field. Drug costs are composed of ingredient cost (the amount charged by the wholesale distributor or manufacturer), the dispensing fee (the amount charged by the pharmacy and the sales tax).
22 drug_era CDM No NA Yes 0 NA A Drug Era is defined as a span of time when the Person is assumed to be exposed to a particular active ingredient. A Drug Era is not the same as a Drug Exposure: Exposures are individual records corresponding to the source when Drug was delivered to the Person, while successive periods of Drug Exposures are combined under certain rules to produce continuous Drug Eras. Every record in the DRUG_EXPOSURE table should be part of a drug era based on the dates of exposure. NA The SQL script for generating DRUG_ERA records can be found [here](https://ohdsi.github.io/CommonDataModel/sqlScripts.html#drug_eras).
23 dose_era CDM No NA Yes 0 NA A Dose Era is defined as a span of time when the Person is assumed to be exposed to a constant dose of a specific active ingredient. NA Dose Eras will be derived from records in the DRUG_EXPOSURE table and the Dose information from the DRUG_STRENGTH table using a standardized algorithm. Dose Form information is not taken into account. So, if the patient changes between different formulations, or different manufacturers with the same formulation, the Dose Era is still spanning the entire time of exposure to the Ingredient.
24 condition_era CDM No NA Yes 0 NA A Condition Era is defined as a span of time when the Person is assumed to have a given condition. Similar to Drug Eras, Condition Eras are chronological periods of Condition Occurrence and every Condition Occurrence record should be part of a Condition Era. Combining individual Condition Occurrences into a single Condition Era serves two purposes: - It allows aggregation of chronic conditions that require frequent ongoing care, instead of treating each Condition Occurrence as an independent event. - It allows aggregation of multiple, closely timed doctor visits for the same Condition to avoid double-counting the Condition Occurrences. For example, consider a Person who visits her Primary Care Physician (PCP) and who is referred to a specialist. At a later time, the Person visits the specialist, who confirms the PCP's original diagnosis and provides the appropriate treatment to resolve the condition. These two independent doctor visits should be aggregated into one Condition Era. NA Each Condition Era corresponds to one or many Condition Occurrence records that form a continuous interval. The condition_concept_id field contains Concepts that are identical to those of the CONDITION_OCCURRENCE table records that make up the Condition Era. In contrast to Drug Eras, Condition Eras are not aggregated to contain Conditions of different hierarchical layers. The SQl Script for generating CONDITION_ERA records can be found [here](https://ohdsi.github.io/CommonDataModel/sqlScripts.html#condition_eras) The Condition Era Start Date is the start date of the first Condition Occurrence. The Condition Era End Date is the end date of the last Condition Occurrence. Condition Eras are built with a Persistence Window of 30 days, meaning, if no occurrence of the same condition_concept_id happens within 30 days of any one occurrence, it will be considered the condition_era_end_date.
25 episode CDM No NA No NA NA The EPISODE table aggregates lower-level clinical events (VISIT_OCCURRENCE, DRUG_EXPOSURE, PROCEDURE_OCCURRENCE, DEVICE_EXPOSURE) into a higher-level abstraction representing clinically and analytically relevant disease phases,outcomes and treatments. The EPISODE_EVENT table connects qualifying clinical events (VISIT_OCCURRENCE, DRUG_EXPOSURE, PROCEDURE_OCCURRENCE, DEVICE_EXPOSURE) to the appropriate EPISODE entry. For example cancers including their development over time, their treatment, and final resolution. Valid Episode Concepts belong to the 'Episode' domain. For cancer episodes please see [article], for non-cancer episodes please see [article]. If your source data does not have all episodes that are relevant to the therapeutic area, write only those you can easily derive from the data. It is understood that that table is not currently expected to be comprehensive. NA
26 episode_event CDM No NA No NA NA The EPISODE_EVENT table connects qualifying clinical events (such as CONDITION_OCCURRENCE, DRUG_EXPOSURE, PROCEDURE_OCCURRENCE, MEASUREMENT) to the appropriate EPISODE entry. For example, linking the precise location of the metastasis (cancer modifier in MEASUREMENT) to the disease episode. This connecting table is used instead of the FACT_RELATIONSHIP table for linking low-level events to abstracted Episodes. Some episodes may not have links to any underlying clinical events. For such episodes, the EPISODE_EVENT table is not populated.
27 metadata CDM No NA No NA NA The METADATA table contains metadata information about a dataset that has been transformed to the OMOP Common Data Model. NA NA
28 cdm_source CDM No NA No NA NA The CDM_SOURCE table contains detail about the source database and the process used to transform the data into the OMOP Common Data Model. NA NA
29 concept VOCAB No NA No NA NA The Standardized Vocabularies contains records, or Concepts, that uniquely identify each fundamental unit of meaning used to express clinical information in all domain tables of the CDM. Concepts are derived from vocabularies, which represent clinical information across a domain (e.g. conditions, drugs, procedures) through the use of codes and associated descriptions. Some Concepts are designated Standard Concepts, meaning these Concepts can be used as normative expressions of a clinical entity within the OMOP Common Data Model and standardized analytics. Each Standard Concept belongs to one Domain, which defines the location where the Concept would be expected to occur within the data tables of the CDM. Concepts can represent broad categories ('Cardiovascular disease'), detailed clinical elements ('Myocardial infarction of the anterolateral wall'), or modifying characteristics and attributes that define Concepts at various levels of detail (severity of a disease, associated morphology, etc.). Records in the Standardized Vocabularies tables are derived from national or international vocabularies such as SNOMED-CT, RxNorm, and LOINC, or custom OMOP Concepts defined to cover various aspects of observational data analysis. The primary purpose of the CONCEPT table is to provide a standardized representation of medical Concepts, allowing for consistent querying and analysis across the healthcare databases. Users can join the CONCEPT table with other tables in the CDM to enrich clinical data with standardized Concept information or use the CONCEPT table as a reference for mapping clinical data from source terminologies to Standard Concepts. NA
30 vocabulary VOCAB No NA No NA NA The VOCABULARY table includes a list of the Vocabularies integrated from various sources or created de novo in OMOP CDM. This reference table contains a single record for each Vocabulary and includes a descriptive name and other associated attributes for the Vocabulary. The primary purpose of the VOCABULARY table is to provide explicit information about specific vocabulary versions and the references to the sources from which they are asserted. Users can identify the version of a particular vocabulary used in the database, enabling consistency and reproducibility in data analysis. Besides, users can check the vocabulary release version in their CDM which refers to the vocabulary_id = 'None'. NA
31 domain VOCAB No NA No NA NA The DOMAIN table includes a list of OMOP-defined Domains to which the Concepts of the Standardized Vocabularies can belong. A Domain represents a clinical definition whereby we assign matching Concepts for the standardized fields in the CDM tables. For example, the Condition Domain contains Concepts that describe a patient condition, and these Concepts can only be used in the condition_concept_id field of the CONDITION_OCCURRENCE and CONDITION_ERA tables. This reference table is populated with a single record for each Domain, including a Domain ID and a descriptive name for every Domain. Users can leverage the DOMAIN table to explore the full spectrum of health-related data Domains available in the Standardized Vocabularies. Also, the information in the DOMAIN table may be used as a reference for mapping source data to OMOP domains, facilitating data harmonization and interoperability. NA
32 concept_class VOCAB No NA No NA NA The CONCEPT_CLASS table includes semantic categories that reference the source structure of each Vocabulary. Concept Classes represent so-called horizontal (e.g. MedDRA, RxNorm) or vertical levels (e.g. SNOMED) of the vocabulary structure. Vocabularies without any Concept Classes, such as HCPCS, use the vocabulary_id as the Concept Class. This reference table is populated with a single record for each Concept Class, which includes a Concept Class ID and a fully specified Concept Class name. Users can utilize the CONCEPT_CLASS table to explore the different classes or categories of concepts within the OHDSI vocabularies. NA
33 concept_relationship VOCAB No NA No NA NA The CONCEPT_RELATIONSHIP table contains records that define relationships between any two Concepts and the nature or type of the relationship. This table captures various types of relationships, including hierarchical, associative, and other semantic connections, enabling comprehensive analysis and interpretation of clinical concepts. Every kind of relationship is defined in the RELATIONSHIP table. The CONCEPT_RELATIONSHIP table can be used to explore hierarchical or attribute relationships between concepts to understand the hierarchical structure of clinical concepts and uncover implicit connections and associations within healthcare data. For example, users can utilize mapping relationships ('Maps to') to harmonize data from different sources and terminologies, enabling interoperability and data integration across disparate datasets. NA
34 relationship VOCAB No NA No NA NA The RELATIONSHIP table provides a reference list of all types of relationships that can be used to associate any two Concepts in the CONCEPT_RELATIONSHIP table, the respective reverse relationships, and their hierarchical characteristics. Note, that Concepts representing relationships between the clinical facts, used for filling in the FACT_RELATIONSHIP table are stored in the CONCEPT table and belong to the Relationship Domain. Users can leverage the RELATIONSHIP table to explore the full list of direct and reverse relationships within the OMOP vocabulary system. Also, users can get insight into how these relationships can be used in ETL, cohort creation, and other tasks according to their ancestral characteristics. NA
35 metadata concept_synonym CDM VOCAB No NA No NA NA The METADATA table contains metadata information about a dataset that has been transformed to the OMOP Common Data Model. The CONCEPT_SYNONYM table captures alternative terms, synonyms, and translations of Concept Name into various languages linked to specific concepts, providing users with a comprehensive view of how Concepts may be expressed or referenced. NA Users can leverage the CONCEPT_SYNONYM table to expand search capabilities and improve query accuracy by incorporating synonymous terms into data analysis and retrieval processes. Also, users can enhance their mapping efforts between local terminologies and standardized concepts by identifying synonymous terms associated with concepts in the CONCEPT_SYNONYM table. NA
36 cdm_source concept_ancestor CDM VOCAB No NA No NA NA The CDM_SOURCE table contains detail about the source database and the process used to transform the data into the OMOP Common Data Model. The CONCEPT_ANCESTOR table is designed to simplify observational analysis by providing the complete hierarchical relationships between Concepts. Only direct parent-child relationships between Concepts are stored in the CONCEPT_RELATIONSHIP table. To determine higher-level ancestry connections, all individual direct relationships would have to be navigated at analysis time. The CONCEPT_ANCESTOR table includes records for all parent-child relationships, as well as grandparent-grandchild relationships and those of any other level of lineage for Standard or Classification concepts. Using the CONCEPT_ANCESTOR table allows for querying for all descendants of a hierarchical concept, and the other way around. For example, drug ingredients and drug products, beneath them in the hierarchy, are all descendants of a drug class ancestor. This table is entirely derived from the CONCEPT, CONCEPT_RELATIONSHIP, and RELATIONSHIP tables. NA The CONCEPT_ANCESTOR table can be used to explore the hierarchical relationships captured in the table to gain insights into the hierarchical structure of clinical concepts. Understanding the hierarchical relationships of concepts can facilitate accurate interpretation and analysis of healthcare data. Also, by incorporating hierarchical relationships from the CONCEPT_ANCESTOR table, users can create cohorts containing related concepts within a hierarchical structure, enabling more comprehensive cohort definitions. NA
37 concept source_to_concept_map VOCAB No NA No NA NA The Standardized Vocabularies contains records, or Concepts, that uniquely identify each fundamental unit of meaning used to express clinical information in all domain tables of the CDM. Concepts are derived from vocabularies, which represent clinical information across a domain (e.g. conditions, drugs, procedures) through the use of codes and associated descriptions. Some Concepts are designated Standard Concepts, meaning these Concepts can be used as normative expressions of a clinical entity within the OMOP Common Data Model and standardized analytics. Each Standard Concept belongs to one Domain, which defines the location where the Concept would be expected to occur within the data tables of the CDM. Concepts can represent broad categories ('Cardiovascular disease'), detailed clinical elements ('Myocardial infarction of the anterolateral wall'), or modifying characteristics and attributes that define Concepts at various levels of detail (severity of a disease, associated morphology, etc.). Records in the Standardized Vocabularies tables are derived from national or international vocabularies such as SNOMED-CT, RxNorm, and LOINC, or custom OMOP Concepts defined to cover various aspects of observational data analysis. The source to concept map table is recommended for use in ETL processes to maintain local source codes which are not available as Concepts in the Standardized Vocabularies, and to establish mappings for each source code into a Standard Concept as target_concept_ids that can be used to populate the Common Data Model tables. The SOURCE_TO_CONCEPT_MAP table is no longer populated with content within the Standardized Vocabularies published to the OMOP community. **There are OHDSI tools to help you populate this table; [Usagi](https://github.com/OHDSI/Usagi) and [Perseus](https://github.com/ohdsi/Perseus). You can read more about OMOP vocabulary mapping in [The Book of OHDSI Chapter 6.3](https://ohdsi.github.io/TheBookOfOhdsi/ExtractTransformLoad.html#step-2-create-the-code-mappings).** The primary purpose of the CONCEPT table is to provide a standardized representation of medical Concepts, allowing for consistent querying and analysis across the healthcare databases. Users can join the CONCEPT table with other tables in the CDM to enrich clinical data with standardized Concept information or use the CONCEPT table as a reference for mapping clinical data from source terminologies to Standard Concepts. NA NA
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@ -28,12 +28,12 @@ visit_occurrence,person_id,Yes,bigint,NA,NA,No,Yes,PERSON,PERSON_ID,NA,NA,NA
visit_occurrence,visit_concept_id,Yes,integer,"This field contains a concept id representing the kind of visit, like inpatient or outpatient. All concepts in this field should be standard and belong to the Visit domain.","Populate this field based on the kind of visit that took place for the person. For example this could be ""Inpatient Visit"", ""Outpatient Visit"", ""Ambulatory Visit"", etc. This table will contain standard concepts in the Visit domain. These concepts are arranged in a hierarchical structure to facilitate cohort definitions by rolling up to generally familiar Visits adopted in most healthcare systems worldwide.",No,Yes,CONCEPT,CONCEPT_ID,Visit,NA,NA
visit_occurrence,visit_start_date,No,date,"For inpatient visits, the start date is typically the admission date. For outpatient visits the start date and end date will be the same.","When populating visit_start_date, you should think about the patient experience to make decisions on how to define visits. In the case of an inpatient visit this should be the date the patient was admitted to the hospital or institution. In all other cases this should be the date of the patient-provider interaction.",No,No,NA,NA,NA,NA,NA
visit_occurrence,visit_start_datetime,Yes,datetime,NA,"If no time is given for the start date of a visit, set it to midnight (00:00:0000).",No,No,NA,NA,NA,NA,NA
visit_occurrence,visit_end_date,No,date,For inpatient visits the end date is typically the discharge date.,"Visit end dates are mandatory. If end dates are not provided in the source there are three ways in which to derive them:
Outpatient Visit: visit_end_datetime = visit_start_datetime
Emergency Room Visit: visit_end_datetime = visit_start_datetime
Inpatient Visit: Usually there is information about discharge. If not, you should be able to derive the end date from the sudden decline of activity or from the absence of inpatient procedures/drugs.
Non-hospital institution Visits: Particularly for claims data, if end dates are not provided assume the visit is for the duration of month that it occurs.
For Inpatient Visits ongoing at the date of ETL, put date of processing the data into visit_end_datetime and visit_type_concept_id with 32220 ""Still patient"" to identify the visit as incomplete.
visit_occurrence,visit_end_date,No,date,For inpatient visits the end date is typically the discharge date.,"Visit end dates are mandatory. If end dates are not provided in the source there are three ways in which to derive them:
Outpatient Visit: visit_end_datetime = visit_start_datetime
Emergency Room Visit: visit_end_datetime = visit_start_datetime
Inpatient Visit: Usually there is information about discharge. If not, you should be able to derive the end date from the sudden decline of activity or from the absence of inpatient procedures/drugs.
Non-hospital institution Visits: Particularly for claims data, if end dates are not provided assume the visit is for the duration of month that it occurs.
For Inpatient Visits ongoing at the date of ETL, put date of processing the data into visit_end_datetime and visit_type_concept_id with 32220 ""Still patient"" to identify the visit as incomplete.
All other Visits: visit_end_datetime = visit_start_datetime. If this is a one-day visit the end date should match the start date.",No,No,NA,NA,NA,NA,NA
visit_occurrence,visit_end_datetime,Yes,datetime,NA,"If no time is given for the end date of a visit, set it to midnight (00:00:0000).",No,No,NA,NA,NA,NA,NA
visit_occurrence,visit_type_concept_id,Yes,Integer,"Use this field to understand the provenance of the visit record, or where the record comes from.","Populate this field based on the provenance of the visit record, as in whether it came from an EHR record or billing claim.",No,Yes,CONCEPT,CONCEPT_ID,Type Concept,NA,NA
@ -51,12 +51,12 @@ visit_detail,person_id,Yes,bigint,NA,NA,No,Yes,PERSON,PERSON_ID,NA,NA,NA
visit_detail,visit_detail_concept_id,Yes,integer,"This field contains a concept id representing the kind of visit detail, like inpatient or outpatient. All concepts in this field should be standard and belong to the Visit domain.","Populate this field based on the kind of visit that took place for the person. For example this could be ""Inpatient Visit"", ""Outpatient Visit"", ""Ambulatory Visit"", etc. This table will contain standard concepts in the Visit domain. These concepts are arranged in a hierarchical structure to facilitate cohort definitions by rolling up to generally familiar Visits adopted in most healthcare systems worldwide. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Visit&standardConcept=Standard&page=1&pageSize=15&query=).",No,Yes,CONCEPT,CONCEPT_ID,Visit,NA,NA
visit_detail,visit_detail_start_date,Yes,date,This is the date of the start of the encounter. This may or may not be equal to the date of the Visit the Visit Detail is associated with.,"When populating visit_start_date, you should think about the patient experience to make decisions on how to define visits. Most likely this should be the date of the patient-provider interaction.",No,No,NA,NA,NA,NA,NA
visit_detail,visit_detail_start_datetime,No,datetime,NA,"If no time is given for the start date of a visit, set it to midnight (00:00:0000).",No,No,NA,NA,NA,NA,NA
visit_detail,visit_detail_end_date,Yes,date,This the end date of the patient-provider interaction.,"Visit Detail end dates are mandatory. If end dates are not provided in the source there are three ways in which to derive them:<br>
- Outpatient Visit Detail: visit_detail_end_datetime = visit_detail_start_datetime
- Emergency Room Visit Detail: visit_detail_end_datetime = visit_detail_start_datetime
- Inpatient Visit Detail: Usually there is information about discharge. If not, you should be able to derive the end date from the sudden decline of activity or from the absence of inpatient procedures/drugs.
- Non-hospital institution Visit Details: Particularly for claims data, if end dates are not provided assume the visit is for the duration of month that it occurs.<br>
For Inpatient Visit Details ongoing at the date of ETL, put date of processing the data into visit_detai_end_datetime and visit_detail_type_concept_id with 32220 ""Still patient"" to identify the visit as incomplete.
visit_detail,visit_detail_end_date,Yes,date,This the end date of the patient-provider interaction.,"Visit Detail end dates are mandatory. If end dates are not provided in the source there are three ways in which to derive them:<br>
- Outpatient Visit Detail: visit_detail_end_datetime = visit_detail_start_datetime
- Emergency Room Visit Detail: visit_detail_end_datetime = visit_detail_start_datetime
- Inpatient Visit Detail: Usually there is information about discharge. If not, you should be able to derive the end date from the sudden decline of activity or from the absence of inpatient procedures/drugs.
- Non-hospital institution Visit Details: Particularly for claims data, if end dates are not provided assume the visit is for the duration of month that it occurs.<br>
For Inpatient Visit Details ongoing at the date of ETL, put date of processing the data into visit_detai_end_datetime and visit_detail_type_concept_id with 32220 ""Still patient"" to identify the visit as incomplete.
All other Visits Details: visit_detail_end_datetime = visit_detail_start_datetime.",No,No,NA,NA,NA,NA,NA
visit_detail,visit_detail_end_datetime,No,datetime,NA,"If no time is given for the end date of a visit, set it to midnight (00:00:0000).",No,No,NA,NA,NA,NA,NA
visit_detail,visit_detail_type_concept_id,Yes,Integer,"Use this field to understand the provenance of the visit detail record, or where the record comes from.","Populate this field based on the provenance of the visit detail record, as in whether it came from an EHR record or billing claim. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Type+Concept&standardConcept=Standard&page=1&pageSize=15&query=).",No,Yes,CONCEPT,CONCEPT_ID,Type Concept,NA,NA
@ -64,8 +64,8 @@ visit_detail,provider_id,No,bigint,"There will only be one provider per **visit
visit_detail,care_site_id,No,bigint,This field provides information about the Care Site where the Visit Detail took place.,There should only be one Care Site associated with a Visit Detail.,No,Yes,CARE_SITE,CARE_SITE_ID,NA,NA,NA
visit_detail,visit_detail_source_value,No,varchar(50),"This field houses the verbatim value from the source data representing the kind of visit detail that took place (inpatient, outpatient, emergency, etc.)","If there is information about the kind of visit detail in the source data that value should be stored here. If a visit is an amalgamation of visits from the source then use a hierarchy to choose the VISIT_DETAIL_SOURCE_VALUE, such as IP -> ER-> OP. This should line up with the logic chosen to determine how visits are created.",No,No,NA,NA,NA,NA,NA
visit_detail,visit_detail_source_concept_id,Yes,integer,NA,"If the VISIT_DETAIL_SOURCE_VALUE is coded in the source data using an OMOP supported vocabulary put the concept id representing the source value here. If not available, map to 0.",No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
visit_detail,admitted_from_concept_id,No,varchar(50),NA,"This information may be called something different in the source data but the field is meant to contain a value indicating where a person was admitted from. Typically this applies only to visits that have a length of stay, like inpatient visits or long-term care visits.",No,No,NA,NA,NA,NA,NA
visit_detail,admitted_from_source_value,Yes,integer,"Use this field to determine where the patient was admitted from. This concept is part of the visit domain and can indicate if a patient was admitted to the hospital from a long-term care facility, for example.","If available, map the admitted_from_source_value to a standard concept in the visit domain. If not available, map to 0. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Visit&standardConcept=Standard&page=1&pageSize=15&query=).",No,Yes,CONCEPT,CONCEPT_ID,Visit,NA,NA
visit_detail,admitted_from_source_value,No,varchar(50),NA,"This information may be called something different in the source data but the field is meant to contain a value indicating where a person was admitted from. Typically this applies only to visits that have a length of stay, like inpatient visits or long-term care visits.",No,No,NA,NA,NA,NA,NA
visit_detail,admitted_from_concept_id,Yes,integer,"Use this field to determine where the patient was admitted from. This concept is part of the visit domain and can indicate if a patient was admitted to the hospital from a long-term care facility, for example.","If available, map the admitted_from_source_value to a standard concept in the visit domain. If not available, map to 0. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Visit&standardConcept=Standard&page=1&pageSize=15&query=).",No,Yes,CONCEPT,CONCEPT_ID,Visit,NA,NA
visit_detail,discharge_to_source_value,No,varchar(50),NA,"This information may be called something different in the source data but the field is meant to contain a value indicating where a person was discharged to after a visit, as in they went home or were moved to long-term care. Typically this applies only to visits that have a length of stay of a day or more.",No,No,NA,NA,NA,NA,NA
visit_detail,discharge_to_concept_id,Yes,integer,"Use this field to determine where the patient was discharged to after a visit detail record. This concept is part of the visit domain and can indicate if a patient was discharged to home or sent to a long-term care facility, for example.","If available, map the DISCHARGE_TO_SOURCE_VALUE to a Standard Concept in the Visit domain. If not available, set to 0. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Visit&standardConcept=Standard&page=1&pageSize=15&query=).",No,Yes,CONCEPT,CONCEPT_ID,Visit,NA,NA
visit_detail,preceding_visit_detail_id,No,bigint,Use this field to find the visit detail that occurred for the person prior to the given visit detail record. There could be a few days or a few years in between.,"The PRECEDING_VISIT_DETAIL_ID can be used to link a visit immediately preceding the current Visit Detail. Note this is not symmetrical, and there is no such thing as a ""following_visit_id"".",No,Yes,VISIT_DETAIL,VISIT_DETAIL_ID,NA,NA,NA
@ -89,21 +89,21 @@ condition_occurrence,condition_source_concept_id,Yes,integer,"This is the concep
condition_occurrence,condition_status_source_value,No,varchar(50),This field houses the verbatim value from the source data representing the condition status.,This information may be called something different in the source data but the field is meant to contain a value indicating when and how a diagnosis was given to a patient. This source value is mapped to a standard concept which is stored in the CONDITION_STATUS_CONCEPT_ID field.,No,No,NA,NA,NA,NA,NA
drug_exposure,drug_exposure_id,Yes,bigint,The unique key given to records of drug dispensings or administrations for a person. Refer to the ETL for how duplicate drugs during the same visit were handled.,"Each instance of a drug dispensing or administration present in the source data should be assigned this unique key. In some cases, a person can have multiple records of the same drug within the same visit. It is valid to keep these duplicates and assign them individual, unique, DRUG_EXPOSURE_IDs, though it is up to the ETL how they should be handled.",Yes,No,NA,NA,NA,NA,NA
drug_exposure,person_id,Yes,bigint,The PERSON_ID of the PERSON for whom the drug dispensing or administration is recorded. This may be a system generated code.,NA,No,Yes,PERSON,PERSON_ID,NA,NA,NA
drug_exposure,drug_concept_id,Yes,integer,"The DRUG_CONCEPT_ID field is recommended for primary use in analyses, and must be used for network studies. This is the standard concept mapped from the source concept id which represents a drug product or molecule otherwise introduced to the body. The drug concepts can have a varying degree of information about drug strength and dose. This information is relevant in the context of quantity and administration information in the subsequent fields plus strength information from the DRUG_STRENGTH table, provided as part of the standard vocabulary download.","The CONCEPT_ID that the DRUG_SOURCE_VALUE maps to. The concept id should be derived either from mapping from the source concept id or by picking the drug concept representing the most amount of detail you have. Records whose source values map to standard concepts with a domain of Drug should go in this table. When the Drug Source Value of the code cannot be translated into Standard Drug Concept IDs, a Drug exposure entry is stored with only the corresponding SOURCE_CONCEPT_ID and DRUG_SOURCE_VALUE and a DRUG_CONCEPT_ID of 0. The Drug Concept with the most detailed content of information is preferred during the mapping process. These are indicated in the CONCEPT_CLASS_ID field of the Concept and are recorded in the following order of precedence: 'Branded Pack', 'Clinical Pack', 'Branded Drug', 'Clinical Drug', 'Branded Drug Component', 'Clinical Drug Component', 'Branded Drug Form', 'Clinical Drug Form', and only if no other information is available 'Ingredient'. Note: If only the drug class is known, the DRUG_CONCEPT_ID field should contain 0. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Drug&standardConcept=Standard&page=1&pageSize=15&query=).",No,Yes,CONCEPT,CONCEPT_ID,Drug,NA,NA
drug_exposure,drug_concept_id,Yes,integer,"The DRUG_CONCEPT_ID field is recommended for primary use in analyses, and must be used for network studies. This is the standard concept mapped from the source concept id which represents a drug product or molecule otherwise introduced to the body. The drug concepts can have a varying degree of information about drug strength and dose. This information is relevant in the context of quantity and administration information in the subsequent fields plus strength information from the DRUG_STRENGTH table, provided as part of the standard vocabulary download.","The CONCEPT_ID that the DRUG_SOURCE_VALUE maps to. The concept id should be derived either from mapping from the source concept id or by picking the drug concept representing the most amount of detail you have. Records whose source values map to standard concepts with a domain of Drug should go in this table. When the Drug Source Value of the code cannot be translated into Standard Drug Concept IDs, a Drug exposure entry is stored with only the corresponding SOURCE_CONCEPT_ID and DRUG_SOURCE_VALUE and a DRUG_CONCEPT_ID of 0. The Drug Concept with the most detailed content of information is preferred during the mapping process. These are indicated in the CONCEPT_CLASS_ID field of the Concept and are recorded in the following order of precedence: Branded Pack, Clinical Pack, Branded Drug, Clinical Drug, Branded Drug Component, Clinical Drug Component, Branded Drug Form, Clinical Drug Form, and only if no other information is available 'Ingredient'. Note: If only the drug class is known, the DRUG_CONCEPT_ID field should contain 0. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Drug&standardConcept=Standard&page=1&pageSize=15&query=).",No,Yes,CONCEPT,CONCEPT_ID,Drug,NA,NA
drug_exposure,drug_exposure_start_date,Yes,date,Use this date to determine the start date of the drug record.,"Valid entries include a start date of a prescription, the date a prescription was filled, or the date on which a Drug administration was recorded. It is a valid ETL choice to use the date the drug was ordered as the DRUG_EXPOSURE_START_DATE.",No,No,NA,NA,NA,NA,NA
drug_exposure,drug_exposure_start_datetime,No,datetime,NA,"This is not required, though it is in v6. If a source does not specify datetime the convention is to set the time to midnight (00:00:0000)",No,No,NA,NA,NA,NA,NA
drug_exposure,drug_exposure_end_date,Yes,date,The DRUG_EXPOSURE_END_DATE denotes the day the drug exposure ended for the patient.,"If this information is not explicitly available in the data, infer the end date using the following methods:/n/n 1. Start first with duration or days supply using the calculation drug start date + days supply -1 day. 2. Use quantity divided by daily dose that you may obtain from the sig or a source field (or assumed daily dose of 1) for solid, indivisibile, drug products. If quantity represents ingredient amount, quantity divided by daily dose * concentration (from drug_strength) drug concept id tells you the dose form. 3. If it is an administration record, set drug end date equal to drug start date. If the record is a written prescription then set end date to start date + 29. If the record is a mail-order prescription set end date to start date + 89. The end date must be equal to or greater than the start date. Ibuprofen 20mg/mL oral solution concept tells us this is oral solution. Calculate duration as quantity (200 example) * daily dose (5mL) /concentration (20mg/mL) 200*5/20 = 50 days. [Examples by dose form](https://ohdsi.github.io/CommonDataModel/drug_dose.html)",No,No,NA,NA,NA,NA,NA
drug_exposure,drug_exposure_end_date,Yes,date,The DRUG_EXPOSURE_END_DATE denotes the day the drug exposure ended for the patient.,"If this information is not explicitly available in the data, infer the end date from start date and duration.<br>For detailed conventions for how to populate this field, please see the [THEMIS repository](https://ohdsi.github.io/Themis/tag_drug_exposure.html).",No,No,NA,NA,NA,NA,NA
drug_exposure,drug_exposure_end_datetime,No,datetime,NA,"This is not required, though it is in v6. If a source does not specify datetime the convention is to set the time to midnight (00:00:0000)",No,No,NA,NA,NA,NA,NA
drug_exposure,verbatim_end_date,No,date,"This is the end date of the drug exposure as it appears in the source data, if it is given",Put the end date or discontinuation date as it appears from the source data or leave blank if unavailable.,No,No,NA,NA,NA,NA,NA
drug_exposure,drug_type_concept_id,Yes,integer,"You can use the TYPE_CONCEPT_ID to delineate between prescriptions written vs. prescriptions dispensed vs. medication history vs. patient-reported exposure, etc.","Choose the drug_type_concept_id that best represents the provenance of the record, for example whether it came from a record of a prescription written or physician administered drug. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Type+Concept&standardConcept=Standard&page=1&pageSize=15&query=).",No,Yes,CONCEPT,CONCEPT_ID,Type Concept,NA,NA
drug_exposure,stop_reason,No,varchar(20),"The reason a person stopped a medication as it is represented in the source. Reasons include regimen completed, changed, removed, etc. This field will be retired in v6.0.",This information is often not populated in source data and it is a valid etl choice to leave it blank if the information does not exist.,No,No,NA,NA,NA,NA,NA
drug_exposure,refills,No,integer,This is only filled in when the record is coming from a prescription written this field is meant to represent intended refills at time of the prescription.,NA,No,No,NA,NA,NA,NA,NA
drug_exposure,quantity,No,float,NA,"To find the dose form of a drug the RELATIONSHIP table can be used where the relationship_id is 'Has dose form'. If liquid, quantity stands for the total amount dispensed or ordered of ingredient in the units given by the drug_strength table. If the unit from the source data does not align with the unit in the DRUG_STRENGTH table the quantity should be converted to the correct unit given in DRUG_STRENGTH. For clinical drugs with fixed dose forms (tablets etc.) the quantity is the number of units/tablets/capsules prescribed or dispensed (can be partial, but then only 1/2 or 1/3, not 0.01). Clinical drugs with divisible dose forms (injections) the quantity is the amount of ingredient the patient got. For example, if the injection is 2mg/mL but the patient got 80mL then quantity is reported as 160.
Quantified clinical drugs with divisible dose forms (prefilled syringes), the quantity is the amount of ingredient similar to clinical drugs. Please see [how to calculate drug dose](https://ohdsi.github.io/CommonDataModel/drug_dose.html) for more information.
drug_exposure,quantity,No,float,NA,"To find the dose form of a drug the RELATIONSHIP table can be used where the relationship_id is 'Has dose form'. If liquid, quantity stands for the total amount dispensed or ordered of ingredient in the units given by the drug_strength table. If the unit from the source data does not align with the unit in the DRUG_STRENGTH table the quantity should be converted to the correct unit given in DRUG_STRENGTH. For clinical drugs with fixed dose forms (tablets etc.) the quantity is the number of units/tablets/capsules prescribed or dispensed (can be partial, but then only 1/2 or 1/3, not 0.01). Clinical drugs with divisible dose forms (injections) the quantity is the amount of ingredient the patient got. For example, if the injection is 2mg/mL but the patient got 80mL then quantity is reported as 160.
Quantified clinical drugs with divisible dose forms (prefilled syringes), the quantity is the amount of ingredient similar to clinical drugs. Please see [how to calculate drug dose](https://ohdsi.github.io/CommonDataModel/drug_dose.html) for more information.
",No,No,NA,NA,NA,NA,NA
drug_exposure,days_supply,No,integer,The number of days of supply of the medication as recorded in the original prescription or dispensing record. Days supply can differ from actual drug duration (i.e. prescribed days supply vs actual exposure).,"The field should be left empty if the source data does not contain a verbatim days_supply, and should not be calculated from other fields. Negative values are not allowed. Several actions are possible: 1) record is not trustworthy and we remove the record entirely. 2) we trust the record and leave days_supply empty or 3) record needs to be combined with other record (e.g. reversal of prescription). High values (>365 days) should be investigated. If considered an error in the source data (e.g. typo), the value needs to be excluded to prevent creation of unrealistic long eras.",No,No,NA,NA,NA,NA,NA
drug_exposure,sig,No,varchar(MAX),This is the verbatim instruction for the drug as written by the provider.,"Put the written out instructions for the drug as it is verbatim in the source, if available.",No,No,NA,NA,NA,NA,NA
drug_exposure,route_concept_id,No,integer,NA,The standard CONCEPT_ID that the ROUTE_SOURCE_VALUE maps to in the route domain.,No,Yes,CONCEPT,CONCEPT_ID,Route,NA,NA
drug_exposure,route_concept_id,No,integer,NA,The standard CONCEPT_ID that the ROUTE_SOURCE_VALUE maps to in the route domain. This is meant to represent the route of administration of the drug. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Route&standardConcept=Standard&page=1&pageSize=15&query=),No,Yes,CONCEPT,CONCEPT_ID,Route,NA,NA
drug_exposure,lot_number,No,varchar(50),NA,NA,No,No,NA,NA,NA,NA,NA
drug_exposure,provider_id,No,bigint,"The Provider associated with drug record, e.g. the provider who wrote the prescription or the provider who administered the drug.","The ETL may need to make a choice as to which PROVIDER_ID to put here. Based on what is available this may or may not be different than the provider associated with the overall VISIT_OCCURRENCE record, for example the ordering vs administering physician on an EHR record.",No,Yes,PROVIDER,PROVIDER_ID,NA,NA,NA
drug_exposure,visit_occurrence_id,No,bigint,"The Visit during which the drug was prescribed, administered or dispensed.",To populate this field drug exposures must be explicitly initiated in the visit.,No,Yes,VISIT_OCCURRENCE,VISIT_OCCURRENCE_ID,NA,NA,NA
@ -133,7 +133,7 @@ device_exposure,device_exposure_start_date,Yes,date,Use this date to determine t
device_exposure,device_exposure_start_datetime,No,datetime,NA,"This is not required, though it is in v6. If a source does not specify datetime the convention is to set the time to midnight (00:00:0000)",No,No,NA,NA,NA,NA,NA
device_exposure,device_exposure_end_date,No,date,"The DEVICE_EXPOSURE_END_DATE denotes the day the device exposure ended for the patient, if given.",Put the end date or discontinuation date as it appears from the source data or leave blank if unavailable.,No,No,NA,NA,NA,NA,NA
device_exposure,device_exposure_end_datetime,No,datetime,NA,If a source does not specify datetime the convention is to set the time to midnight (00:00:0000),No,No,NA,NA,NA,NA,NA
device_exposure,device_type_concept_id,Yes,integer,"You can use the TYPE_CONCEPT_ID to denote the provenance of the record, as in whether the record is from administrative claims or EHR. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Type+Concept&standardConcept=Standard&page=1&pageSize=15&query=).","Choose the drug_type_concept_id that best represents the provenance of the record, for example whether it came from a record of a prescription written or physician administered drug.",No,Yes,CONCEPT,CONCEPT_ID,Type Concept,NA,NA
device_exposure,device_type_concept_id,Yes,integer,"You can use the TYPE_CONCEPT_ID to denote the provenance of the record, as in whether the record is from administrative claims or EHR. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Type+Concept&standardConcept=Standard&page=1&pageSize=15&query=).","Choose the device_type_concept_id that best represents the provenance of the record, for example whether it came from a record of a prescription written or physician administered drug.",No,Yes,CONCEPT,CONCEPT_ID,Type Concept,NA,NA
device_exposure,unique_device_id,No,varchar(50),"This is the Unique Device Identification number for devices regulated by the FDA, if given.","For medical devices that are regulated by the FDA, a Unique Device Identification (UDI) is provided if available in the data source and is recorded in the UNIQUE_DEVICE_ID field.",No,No,NA,NA,NA,NA,NA
device_exposure,quantity,No,integer,NA,NA,No,No,NA,NA,NA,NA,NA
device_exposure,provider_id,No,bigint,"The Provider associated with device record, e.g. the provider who wrote the prescription or the provider who implanted the device.",The ETL may need to make a choice as to which PROVIDER_ID to put here. Based on what is available this may or may not be different than the provider associated with the overall VISIT_OCCURRENCE record.,No,Yes,PROVIDER,PROVIDER_ID,NA,NA,NA
@ -148,7 +148,7 @@ measurement,measurement_date,Yes,date,Use this date to determine the date of the
measurement,measurement_datetime,No,datetime,NA,"This is not required, though it is in v6. If a source does not specify datetime the convention is to set the time to midnight (00:00:0000)",No,No,NA,NA,NA,NA,NA
measurement,measurement_time,No,varchar(10),NA,This is present for backwards compatibility and will be deprecated in an upcoming version.,No,No,NA,NA,NA,NA,NA
measurement,measurement_type_concept_id,Yes,integer,"This field can be used to determine the provenance of the Measurement record, as in whether the measurement was from an EHR system, insurance claim, registry, or other sources.","Choose the MEASUREMENT_TYPE_CONCEPT_ID that best represents the provenance of the record, for example whether it came from an EHR record or billing claim. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Type+Concept&standardConcept=Standard&page=1&pageSize=15&query=).",No,Yes,CONCEPT,CONCEPT_ID,Type Concept,NA,NA
measurement,operator_concept_id,No,integer,"The meaning of Concept [4172703](https://athena.ohdsi.org/search-terms/terms/4172703) for '=' is identical to omission of a OPERATOR_CONCEPT_ID value. Since the use of this field is rare, it's important when devising analyses to not to forget testing for the content of this field for values different from =.","Operators are <, <=, =, >=, > and these concepts belong to the 'Meas Value Operator' domain. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Meas+Value+Operator&standardConcept=Standard&page=1&pageSize=15&query=).",No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
measurement,operator_concept_id,No,integer,"The meaning of Concept [4172703](https://athena.ohdsi.org/search-terms/terms/4172703) for '=' is identical to omission of a OPERATOR_CONCEPT_ID value. Since the use of this field is rare, it's important when devising analyses to not to forget testing for the content of this field for values different from =.","The operator_concept_id explictly refers to the value of the measurement. Operators are <, <=, =, >=, > and these concepts belong to the 'Meas Value Operator' domain. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Meas+Value+Operator&standardConcept=Standard&page=1&pageSize=15&query=).",No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
measurement,value_as_number,No,float,"This is the numerical value of the Result of the Measurement, if available. Note that measurements such as blood pressures will be split into their component parts i.e. one record for systolic, one record for diastolic.","If there is a negative value coming from the source, set the VALUE_AS_NUMBER to NULL, with the exception of the following Measurements (listed as LOINC codes):<br>- [1925-7](https://athena.ohdsi.org/search-terms/terms/3003396) Base excess in Arterial blood by calculation - [1927-3](https://athena.ohdsi.org/search-terms/terms/3002032) Base excess in Venous blood by calculation - [8632-2](https://athena.ohdsi.org/search-terms/terms/3006277) QRS-Axis - [11555-0](https://athena.ohdsi.org/search-terms/terms/3012501) Base excess in Blood by calculation - [1926-5](https://athena.ohdsi.org/search-terms/terms/3003129) Base excess in Capillary blood by calculation - [28638-5](https://athena.ohdsi.org/search-terms/terms/3004959) Base excess in Arterial cord blood by calculation [28639-3](https://athena.ohdsi.org/search-terms/terms/3007435) Base excess in Venous cord blood by calculation",No,No,NA,NA,NA,NA,NA
measurement,value_as_concept_id,No,integer,If the raw data gives a categorial result for measurements those values are captured and mapped to standard concepts in the 'Meas Value' domain.,"If the raw data provides categorial results as well as continuous results for measurements, it is a valid ETL choice to preserve both values. The continuous value should go in the VALUE_AS_NUMBER field and the categorical value should be mapped to a standard concept in the 'Meas Value' domain and put in the VALUE_AS_CONCEPT_ID field. This is also the destination for the 'Maps to value' relationship.",No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
measurement,unit_concept_id,No,integer,"There is currently no recommended unit for individual measurements, i.e. it is not mandatory to represent Hemoglobin a1C measurements as a percentage. UNIT_SOURCE_VALUES should be mapped to a Standard Concept in the Unit domain that best represents the unit as given in the source data.","There is no standardization requirement for units associated with MEASUREMENT_CONCEPT_IDs, however, it is the responsibility of the ETL to choose the most plausible unit.",No,Yes,CONCEPT,CONCEPT_ID,Unit,NA,NA
@ -196,7 +196,7 @@ note,note_event_field_concept_id,No,integer,NA,NA,No,Yes,CONCEPT,CONCEPT_ID,NA,N
note,note_date,Yes,date,The date the note was recorded.,NA,No,No,NA,NA,NA,NA,NA
note,note_datetime,No,datetime,NA,If time is not given set the time to midnight.,No,No,NA,NA,NA,NA,NA
note,note_type_concept_id,Yes,integer,The provenance of the note. Most likely this will be EHR.,"Put the source system of the note, as in EHR record. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?standardConcept=Standard&domain=Type+Concept&page=1&pageSize=15&query=).",No,Yes,CONCEPT,CONCEPT_ID,Type Concept,NA,NA
note,note_class_concept_id,Yes,integer,"A Standard Concept Id representing the HL7 LOINC
note,note_class_concept_id,Yes,integer,"A Standard Concept Id representing the HL7 LOINC
Document Type Vocabulary classification of the note.",Map the note classification to a Standard Concept. For more information see the ETL Conventions in the description of the NOTE table. [AcceptedConcepts](https://athena.ohdsi.org/search-terms/terms?standardConcept=Standard&conceptClass=Doc+Kind&conceptClass=Doc+Role&conceptClass=Doc+Setting&conceptClass=Doc+Subject+Matter&conceptClass=Doc+Type+of+Service&domain=Meas+Value&page=1&pageSize=15&query=). This Concept can alternatively be represented by concepts with the relationship 'Kind of (LOINC)' to [706391](https://athena.ohdsi.org/search-terms/terms/706391) (Note).,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
note,note_title,No,varchar(250),The title of the note.,NA,No,No,NA,NA,NA,NA,NA
note,note_text,Yes,varchar(MAX),The content of the note.,NA,No,No,NA,NA,NA,NA,NA
@ -217,22 +217,22 @@ note_nlp,note_nlp_source_concept_id,No,integer,NA,NA,No,Yes,CONCEPT,CONCEPT_ID,N
note_nlp,nlp_system,No,varchar(250),NA,Name and version of the NLP system that extracted the term. Useful for data provenance.,No,No,NA,NA,NA,NA,NA
note_nlp,nlp_date,Yes,date,The date of the note processing.,NA,No,No,NA,NA,NA,NA,NA
note_nlp,nlp_datetime,No,datetime,The date and time of the note processing.,NA,No,No,NA,NA,NA,NA,NA
note_nlp,term_exists,No,varchar(1),NA,"Term_exists is defined as a flag that indicates if the patient actually has or had the condition. Any of the following modifiers would make Term_exists false:
Negation = true
Subject = [anything other than the patient]
Conditional = true/li>
Rule_out = true
Uncertain = very low certainty or any lower certainties
A complete lack of modifiers would make Term_exists true.
note_nlp,term_exists,No,varchar(1),NA,"Term_exists is defined as a flag that indicates if the patient actually has or had the condition. Any of the following modifiers would make Term_exists false:
Negation = true
Subject = [anything other than the patient]
Conditional = true/li>
Rule_out = true
Uncertain = very low certainty or any lower certainties
A complete lack of modifiers would make Term_exists true.
",No,No,NA,NA,NA,NA,NA
note_nlp,term_temporal,No,varchar(50),NA,"Term_temporal is to indicate if a condition is present or just in the past. The following would be past:<br><br>
- History = true
note_nlp,term_temporal,No,varchar(50),NA,"Term_temporal is to indicate if a condition is present or just in the past. The following would be past:<br><br>
- History = true
- Concept_date = anything before the time of the report",No,No,NA,NA,NA,NA,NA
note_nlp,term_modifiers,No,varchar(2000),NA,"For the modifiers that are there, they would have to have these values:<br><br>
- Negation = false
- Subject = patient
- Conditional = false
- Rule_out = false
note_nlp,term_modifiers,No,varchar(2000),NA,"For the modifiers that are there, they would have to have these values:<br><br>
- Negation = false
- Subject = patient
- Conditional = false
- Rule_out = false
- Uncertain = true or high or moderate or even low (could argue about low). Term_modifiers will concatenate all modifiers for different types of entities (conditions, drugs, labs etc) into one string. Lab values will be saved as one of the modifiers.",No,No,NA,NA,NA,NA,NA
specimen,specimen_id,Yes,bigint,Unique identifier for each specimen.,NA,Yes,No,NA,NA,NA,NA,NA
specimen,person_id,Yes,bigint,The person from whom the specimen is collected.,NA,No,Yes,PERSON,PERSON_ID,NA,NA,NA
@ -356,9 +356,9 @@ drug_era,drug_era_id,Yes,bigint,NA,NA,Yes,No,NA,NA,NA,NA,NA
drug_era,person_id,Yes,bigint,NA,NA,No,Yes,PERSON,PERSON_ID,NA,NA,NA
drug_era,drug_concept_id,Yes,integer,The Concept Id representing the specific drug ingredient.,NA,No,Yes,CONCEPT,CONCEPT_ID,Drug,Ingredient,NA
drug_era,drug_era_start_datetime,Yes,datetime,NA,"The Drug Era Start Date is the start date of the first Drug Exposure for a given ingredient, with at least 31 days since the previous exposure.",No,No,NA,NA,NA,NA,NA
drug_era,drug_era_end_datetime,Yes,datetime,NA,"The Drug Era End Date is the end date of the last Drug Exposure. The End Date of each Drug Exposure is either taken from the field drug_exposure_end_date or, as it is typically not available, inferred using the following rules:
For pharmacy prescription data, the date when the drug was dispensed plus the number of days of supply are used to extrapolate the End Date for the Drug Exposure. Depending on the country-specific healthcare system, this supply information is either explicitly provided in the day_supply field or inferred from package size or similar information.
For Procedure Drugs, usually the drug is administered on a single date (i.e., the administration date).
drug_era,drug_era_end_datetime,Yes,datetime,NA,"The Drug Era End Date is the end date of the last Drug Exposure. The End Date of each Drug Exposure is either taken from the field drug_exposure_end_date or, as it is typically not available, inferred using the following rules:
For pharmacy prescription data, the date when the drug was dispensed plus the number of days of supply are used to extrapolate the End Date for the Drug Exposure. Depending on the country-specific healthcare system, this supply information is either explicitly provided in the day_supply field or inferred from package size or similar information.
For Procedure Drugs, usually the drug is administered on a single date (i.e., the administration date).
A standard Persistence Window of 30 days (gap, slack) is permitted between two subsequent such extrapolated DRUG_EXPOSURE records to be considered to be merged into a single Drug Era.",No,No,NA,NA,NA,NA,NA
drug_era,drug_exposure_count,No,integer,The count of grouped DRUG_EXPOSURE records that were included in the DRUG_ERA row.,NA,No,No,NA,NA,NA,NA,NA
drug_era,gap_days,No,integer,NA,"The Gap Days determine how many total drug-free days are observed between all Drug Exposure events that contribute to a DRUG_ERA record. It is assumed that the drugs are ""not stockpiled"" by the patient, i.e. that if a new drug prescription or refill is observed (a new DRUG_EXPOSURE record is written), the remaining supply from the previous events is abandoned. The difference between Persistence Window and Gap Days is that the former is the maximum drug-free time allowed between two subsequent DRUG_EXPOSURE records, while the latter is the sum of actual drug-free days for the given Drug Era under the above assumption of non-stockpiling.",No,No,NA,NA,NA,NA,NA
@ -372,20 +372,20 @@ dose_era,dose_era_end_datetime,Yes,datetime,NA,The date the Person was no longer
condition_era,condition_era_id,Yes,bigint,NA,NA,Yes,No,NA,NA,NA,NA,NA
condition_era,person_id,Yes,bigint,NA,NA,No,No,PERSON,PERSON_ID,NA,NA,NA
condition_era,condition_concept_id,Yes,integer,The Concept Id representing the Condition.,NA,No,Yes,CONCEPT,CONCEPT_ID,Condition,NA,NA
condition_era,condition_era_start_datetime,Yes,datetime,"The start date for the Condition Era
constructed from the individual
instances of Condition Occurrences.
It is the start date of the very first
chronologically recorded instance of
condition_era,condition_era_start_datetime,Yes,datetime,"The start date for the Condition Era
constructed from the individual
instances of Condition Occurrences.
It is the start date of the very first
chronologically recorded instance of
the condition with at least 31 days since any prior record of the same Condition.",NA,No,No,NA,NA,NA,NA,NA
condition_era,condition_era_end_datetime,Yes,datetime,"The end date for the Condition Era
constructed from the individual
instances of Condition Occurrences.
It is the end date of the final
continuously recorded instance of the
condition_era,condition_era_end_datetime,Yes,datetime,"The end date for the Condition Era
constructed from the individual
instances of Condition Occurrences.
It is the end date of the final
continuously recorded instance of the
Condition.",NA,No,No,NA,NA,NA,NA,NA
condition_era,condition_occurrence_count,No,integer,"The number of individual Condition
Occurrences used to construct the
condition_era,condition_occurrence_count,No,integer,"The number of individual Condition
Occurrences used to construct the
condition era.",NA,No,No,NA,NA,NA,NA,NA
metadata,metadata_concept_id,Yes,integer,NA,NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
metadata,metadata_type_concept_id,Yes,integer,NA,NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
@ -406,58 +406,58 @@ cdm_source,cdm_version,No,varchar(10),NA,NA,No,No,NA,NA,NA,NA,NA
cdm_source,vocabulary_version,No,varchar(20),NA,NA,No,No,NA,NA,NA,NA,NA
concept,concept_id,Yes,integer,A unique identifier for each Concept across all domains.,NA,Yes,No,NA,NA,NA,NA,NA
concept,concept_name,Yes,varchar(255),"An unambiguous, meaningful and descriptive name for the Concept.",NA,No,No,NA,NA,NA,NA,NA
concept,domain_id,Yes,varchar(20),A foreign key to the [DOMAIN](https://ohdsi.github.io/CommonDataModel/cdm531.html#domain) table the Concept belongs to.,NA,No,Yes,DOMAIN,DOMAIN_ID,NA,NA,NA
concept,vocabulary_id,Yes,varchar(20),"A foreign key to the [VOCABULARY](https://ohdsi.github.io/CommonDataModel/cdm531.html#vocabulary)
table indicating from which source the
concept,domain_id,Yes,varchar(20),A foreign key to the [DOMAIN](https://ohdsi.github.io/CommonDataModel/cdm60.html#domain) table the Concept belongs to.,NA,No,Yes,DOMAIN,DOMAIN_ID,NA,NA,NA
concept,vocabulary_id,Yes,varchar(20),"A foreign key to the [VOCABULARY](https://ohdsi.github.io/CommonDataModel/cdm60.html#vocabulary)
table indicating from which source the
Concept has been adapted.",NA,No,Yes,VOCABULARY,VOCABULARY_ID,NA,NA,NA
concept,concept_class_id,Yes,varchar(20),"The attribute or concept class of the
Concept. Examples are 'Clinical Drug',
concept,concept_class_id,Yes,varchar(20),"The attribute or concept class of the
Concept. Examples are 'Clinical Drug',
'Ingredient', 'Clinical Finding' etc.",NA,No,Yes,CONCEPT_CLASS,CONCEPT_CLASS_ID,NA,NA,NA
concept,standard_concept,No,varchar(1),"This flag determines where a Concept is
a Standard Concept, i.e. is used in the
data, a Classification Concept, or a
non-standard Source Concept. The
allowable values are 'S' (Standard
Concept) and 'C' (Classification
concept,standard_concept,No,varchar(1),"This flag determines where a Concept is
a Standard Concept, i.e. is used in the
data, a Classification Concept, or a
non-standard Source Concept. The
allowable values are 'S' (Standard
Concept) and 'C' (Classification
Concept), otherwise the content is NULL.",NA,No,No,NA,NA,NA,NA,NA
concept,concept_code,Yes,varchar(50),"The concept code represents the identifier
of the Concept in the source vocabulary,
such as SNOMED-CT concept IDs,
RxNorm RXCUIs etc. Note that concept
concept,concept_code,Yes,varchar(50),"The concept code represents the identifier
of the Concept in the source vocabulary,
such as SNOMED-CT concept IDs,
RxNorm RXCUIs etc. Note that concept
codes are not unique across vocabularies.",NA,No,No,NA,NA,NA,NA,NA
concept,valid_start_date,Yes,date,"The date when the Concept was first
recorded. The default value is
1-Jan-1970, meaning, the Concept has no
concept,valid_start_date,Yes,date,"The date when the Concept was first
recorded. The default value is
1-Jan-1970, meaning, the Concept has no
(known) date of inception.",NA,No,No,NA,NA,NA,NA,NA
concept,valid_end_date,Yes,date,"The date when the Concept became
invalid because it was deleted or
superseded (updated) by a new concept.
The default value is 31-Dec-2099,
meaning, the Concept is valid until it
concept,valid_end_date,Yes,date,"The date when the Concept became
invalid because it was deleted or
superseded (updated) by a new concept.
The default value is 31-Dec-2099,
meaning, the Concept is valid until it
becomes deprecated.",NA,No,No,NA,NA,NA,NA,NA
concept,invalid_reason,No,varchar(1),"Reason the Concept was invalidated.
Possible values are D (deleted), U
(replaced with an update) or NULL when
concept,invalid_reason,No,varchar(1),"Reason the Concept was invalidated.
Possible values are D (deleted), U
(replaced with an update) or NULL when
valid_end_date has the default value.",NA,No,No,NA,NA,NA,NA,NA
vocabulary,vocabulary_id,Yes,varchar(20),"A unique identifier for each Vocabulary, such
vocabulary,vocabulary_id,Yes,varchar(20),"A unique identifier for each Vocabulary, such
as ICD9CM, SNOMED, Visit.",NA,Yes,No,NA,NA,NA,NA,NA
vocabulary,vocabulary_name,Yes,varchar(255),"The name describing the vocabulary, for
example International Classification of
Diseases, Ninth Revision, Clinical
vocabulary,vocabulary_name,Yes,varchar(255),"The name describing the vocabulary, for
example International Classification of
Diseases, Ninth Revision, Clinical
Modification, Volume 1 and 2 (NCHS) etc.",NA,No,No,NA,NA,NA,NA,NA
vocabulary,vocabulary_reference,Yes,varchar(255),"External reference to documentation or
available download of the about the
vocabulary,vocabulary_reference,Yes,varchar(255),"External reference to documentation or
available download of the about the
vocabulary.",NA,No,No,NA,NA,NA,NA,NA
vocabulary,vocabulary_version,No,varchar(255),"Version of the Vocabulary as indicated in
vocabulary,vocabulary_version,No,varchar(255),"Version of the Vocabulary as indicated in
the source.",NA,No,No,NA,NA,NA,NA,NA
vocabulary,vocabulary_concept_id,Yes,integer,A Concept that represents the Vocabulary the VOCABULARY record belongs to.,NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
domain,domain_id,Yes,varchar(20),A unique key for each domain.,NA,Yes,No,NA,NA,NA,NA,NA
domain,domain_name,Yes,varchar(255),"The name describing the Domain, e.g.
Condition, Procedure, Measurement
domain,domain_name,Yes,varchar(255),"The name describing the Domain, e.g.
Condition, Procedure, Measurement
etc.",NA,No,No,NA,NA,NA,NA,NA
domain,domain_concept_id,Yes,integer,A Concept representing the Domain Concept the DOMAIN record belongs to.,NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
concept_class,concept_class_id,Yes,varchar(20),A unique key for each class.,NA,Yes,No,NA,NA,NA,NA,NA
concept_class,concept_class_name,Yes,varchar(255),"The name describing the Concept Class, e.g.
concept_class,concept_class_name,Yes,varchar(255),"The name describing the Concept Class, e.g.
Clinical Finding, Ingredient, etc.",NA,No,No,NA,NA,NA,NA,NA
concept_class,concept_class_concept_id,Yes,integer,A Concept that represents the Concept Class.,NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
concept_relationship,concept_id_1,Yes,integer,NA,NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
@ -475,50 +475,50 @@ relationship,relationship_concept_id,Yes,integer,NA,NA,No,Yes,CONCEPT,CONCEPT_ID
concept_synonym,concept_id,Yes,integer,NA,NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
concept_synonym,concept_synonym_name,Yes,varchar(1000),NA,NA,No,No,NA,NA,NA,NA,NA
concept_synonym,language_concept_id,Yes,integer,NA,NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
concept_ancestor,ancestor_concept_id,Yes,integer,"The Concept Id for the higher-level concept
concept_ancestor,ancestor_concept_id,Yes,integer,"The Concept Id for the higher-level concept
that forms the ancestor in the relationship.",NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
concept_ancestor,descendant_concept_id,Yes,integer,"The Concept Id for the lower-level concept
that forms the descendant in the
concept_ancestor,descendant_concept_id,Yes,integer,"The Concept Id for the lower-level concept
that forms the descendant in the
relationship.",NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
concept_ancestor,min_levels_of_separation,Yes,integer,"The minimum separation in number of
levels of hierarchy between ancestor and
descendant concepts. This is an attribute
concept_ancestor,min_levels_of_separation,Yes,integer,"The minimum separation in number of
levels of hierarchy between ancestor and
descendant concepts. This is an attribute
that is used to simplify hierarchic analysis.",NA,No,No,NA,NA,NA,NA,NA
concept_ancestor,max_levels_of_separation,Yes,integer,"The maximum separation in number of
levels of hierarchy between ancestor and
descendant concepts. This is an attribute
concept_ancestor,max_levels_of_separation,Yes,integer,"The maximum separation in number of
levels of hierarchy between ancestor and
descendant concepts. This is an attribute
that is used to simplify hierarchic analysis.",NA,No,No,NA,NA,NA,NA,NA
source_to_concept_map,source_code,Yes,varchar(50),"The source code being translated
source_to_concept_map,source_code,Yes,varchar(50),"The source code being translated
into a Standard Concept.",NA,No,No,NA,NA,NA,NA,NA
source_to_concept_map,source_concept_id,Yes,integer,"A foreign key to the Source
Concept that is being translated
source_to_concept_map,source_concept_id,Yes,integer,"A foreign key to the Source
Concept that is being translated
into a Standard Concept.","This is either 0 or should be a number above 2 billion, which are the Concepts reserved for site-specific codes and mappings.",No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
source_to_concept_map,source_vocabulary_id,Yes,varchar(20),"A foreign key to the
VOCABULARY table defining the
vocabulary of the source code that
is being translated to a Standard
source_to_concept_map,source_vocabulary_id,Yes,varchar(20),"A foreign key to the
VOCABULARY table defining the
vocabulary of the source code that
is being translated to a Standard
Concept.",NA,No,No,NA,NA,NA,NA,NA
source_to_concept_map,source_code_description,No,varchar(255),"An optional description for the
source code. This is included as a
convenience to compare the
description of the source code to
source_to_concept_map,source_code_description,No,varchar(255),"An optional description for the
source code. This is included as a
convenience to compare the
description of the source code to
the name of the concept.",NA,No,No,NA,NA,NA,NA,NA
source_to_concept_map,target_concept_id,Yes,integer,"The target Concept
to which the source code is being
source_to_concept_map,target_concept_id,Yes,integer,"The target Concept
to which the source code is being
mapped.",NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
source_to_concept_map,target_vocabulary_id,Yes,varchar(20),The Vocabulary of the target Concept.,NA,No,Yes,VOCABULARY,VOCABULARY_ID,NA,NA,NA
source_to_concept_map,valid_start_date,Yes,date,"The date when the mapping
source_to_concept_map,valid_start_date,Yes,date,"The date when the mapping
instance was first recorded.",NA,No,No,NA,NA,NA,NA,NA
source_to_concept_map,valid_end_date,Yes,date,"The date when the mapping
instance became invalid because it
was deleted or superseded
(updated) by a new relationship.
source_to_concept_map,valid_end_date,Yes,date,"The date when the mapping
instance became invalid because it
was deleted or superseded
(updated) by a new relationship.
Default value is 31-Dec-2099.",NA,No,No,NA,NA,NA,NA,NA
source_to_concept_map,invalid_reason,No,varchar(1),"Reason the mapping instance was
invalidated. Possible values are D
(deleted), U (replaced with an
update) or NULL when
valid_end_date has the default
source_to_concept_map,invalid_reason,No,varchar(1),"Reason the mapping instance was
invalidated. Possible values are D
(deleted), U (replaced with an
update) or NULL when
valid_end_date has the default
value.",NA,No,No,NA,NA,NA,NA,NA
drug_strength,drug_concept_id,Yes,integer,The Concept representing the Branded Drug or Clinical Drug Product.,NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
drug_strength,ingredient_concept_id,Yes,integer,The Concept representing the active ingredient contained within the drug product.,"Combination Drugs will have more than one record in this table, one for each active Ingredient.",No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
@ -529,8 +529,8 @@ drug_strength,numerator_unit_concept_id,No,integer,The Concept representing the
drug_strength,denominator_value,No,float,"The amount of total liquid (or other divisible product, such as ointment, gel, spray, etc.).",NA,No,No,NA,NA,NA,NA,NA
drug_strength,denominator_unit_concept_id,No,integer,The Concept representing the denominator unit for the concentration of active ingredient.,NA,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
drug_strength,box_size,No,integer,The number of units of Clinical Branded Drug or Quantified Clinical or Branded Drug contained in a box as dispensed to the patient.,NA,No,No,NA,NA,NA,NA,NA
drug_strength,valid_start_date,Yes,date,"The date when the Concept was first
recorded. The default value is
drug_strength,valid_start_date,Yes,date,"The date when the Concept was first
recorded. The default value is
1-Jan-1970.",NA,No,No,NA,NA,NA,NA,NA
drug_strength,valid_end_date,Yes,date,The date when then Concept became invalid.,NA,No,No,NA,NA,NA,NA,NA
drug_strength,invalid_reason,No,varchar(1),"Reason the concept was invalidated. Possible values are D (deleted), U (replaced with an update) or NULL when valid_end_date has the default value.",NA,No,No,NA,NA,NA,NA,NA

1 cdmTableName cdmFieldName isRequired cdmDatatype userGuidance etlConventions isPrimaryKey isForeignKey fkTableName fkFieldName fkDomain fkClass unique DQ identifiers
28 visit_occurrence visit_concept_id Yes integer This field contains a concept id representing the kind of visit, like inpatient or outpatient. All concepts in this field should be standard and belong to the Visit domain. Populate this field based on the kind of visit that took place for the person. For example this could be "Inpatient Visit", "Outpatient Visit", "Ambulatory Visit", etc. This table will contain standard concepts in the Visit domain. These concepts are arranged in a hierarchical structure to facilitate cohort definitions by rolling up to generally familiar Visits adopted in most healthcare systems worldwide. No Yes CONCEPT CONCEPT_ID Visit NA NA
29 visit_occurrence visit_start_date No date For inpatient visits, the start date is typically the admission date. For outpatient visits the start date and end date will be the same. When populating visit_start_date, you should think about the patient experience to make decisions on how to define visits. In the case of an inpatient visit this should be the date the patient was admitted to the hospital or institution. In all other cases this should be the date of the patient-provider interaction. No No NA NA NA NA NA
30 visit_occurrence visit_start_datetime Yes datetime NA If no time is given for the start date of a visit, set it to midnight (00:00:0000). No No NA NA NA NA NA
31 visit_occurrence visit_end_date No date For inpatient visits the end date is typically the discharge date. Visit end dates are mandatory. If end dates are not provided in the source there are three ways in which to derive them: Outpatient Visit: visit_end_datetime = visit_start_datetime Emergency Room Visit: visit_end_datetime = visit_start_datetime Inpatient Visit: Usually there is information about discharge. If not, you should be able to derive the end date from the sudden decline of activity or from the absence of inpatient procedures/drugs. Non-hospital institution Visits: Particularly for claims data, if end dates are not provided assume the visit is for the duration of month that it occurs. For Inpatient Visits ongoing at the date of ETL, put date of processing the data into visit_end_datetime and visit_type_concept_id with 32220 "Still patient" to identify the visit as incomplete. All other Visits: visit_end_datetime = visit_start_datetime. If this is a one-day visit the end date should match the start date. No No NA NA NA NA NA
32 visit_occurrence visit_end_datetime Yes datetime NA If no time is given for the end date of a visit, set it to midnight (00:00:0000). No No NA NA NA NA NA
33 visit_occurrence visit_type_concept_id Yes Integer Use this field to understand the provenance of the visit record, or where the record comes from. Populate this field based on the provenance of the visit record, as in whether it came from an EHR record or billing claim. No Yes CONCEPT CONCEPT_ID Type Concept NA NA
34 visit_occurrence provider_id No bigint There will only be one provider per visit record and the ETL document should clearly state how they were chosen (attending, admitting, etc.). If there are multiple providers associated with a visit in the source, this can be reflected in the event tables (CONDITION_OCCURRENCE, PROCEDURE_OCCURRENCE, etc.) or in the VISIT_DETAIL table. If there are multiple providers associated with a visit, you will need to choose which one to put here. The additional providers can be stored in the visit_detail table. No Yes PROVIDER PROVIDER_ID NA NA NA
35 visit_occurrence care_site_id No bigint This field provides information about the care site where the visit took place. There should only be one care site associated with a visit. No Yes CARE_SITE CARE_SITE_ID NA NA NA
36 visit_occurrence visit_source_value No varchar(50) This field houses the verbatim value from the source data representing the kind of visit that took place (inpatient, outpatient, emergency, etc.) If there is information about the kind of visit in the source data that value should be stored here. If a visit is an amalgamation of visits from the source then use a hierarchy to choose the visit source value, such as IP -> ER-> OP. This should line up with the logic chosen to determine how visits are created. No No NA NA NA NA NA
37 visit_occurrence visit_source_concept_id Yes integer NA If the visit source value is coded in the source data using an OMOP supported vocabulary put the concept id representing the source value here. If not available set to 0. No Yes CONCEPT CONCEPT_ID NA NA NA
38 visit_occurrence admitted_from_concept_id Yes integer Use this field to determine where the patient was admitted from. This concept is part of the visit domain and can indicate if a patient was admitted to the hospital from a long-term care facility, for example. If available, map the admitted_from_source_value to a standard concept in the visit domain. If not available set to 0. No Yes CONCEPT CONCEPT_ID Visit NA NA
39 visit_occurrence admitted_from_source_value No varchar(50) NA This information may be called something different in the source data but the field is meant to contain a value indicating where a person was admitted from. Typically this applies only to visits that have a length of stay, like inpatient visits or long-term care visits. No No NA NA NA NA NA
51 visit_detail provider_id No bigint There will only be one provider per **visit** record and the ETL document should clearly state how they were chosen (attending, admitting, etc.). This is a typical reason for leveraging the VISIT_DETAIL table as even though each VISIT_DETAIL record can only have one provider, there is no limit to the number of VISIT_DETAIL records that can be associated to a VISIT_OCCURRENCE record. The additional providers associated to a Visit can be stored in this table where each VISIT_DETAIL record represents a different provider. No Yes PROVIDER PROVIDER_ID NA NA NA
52 visit_detail care_site_id No bigint This field provides information about the Care Site where the Visit Detail took place. There should only be one Care Site associated with a Visit Detail. No Yes CARE_SITE CARE_SITE_ID NA NA NA
53 visit_detail visit_detail_source_value No varchar(50) This field houses the verbatim value from the source data representing the kind of visit detail that took place (inpatient, outpatient, emergency, etc.) If there is information about the kind of visit detail in the source data that value should be stored here. If a visit is an amalgamation of visits from the source then use a hierarchy to choose the VISIT_DETAIL_SOURCE_VALUE, such as IP -> ER-> OP. This should line up with the logic chosen to determine how visits are created. No No NA NA NA NA NA
54 visit_detail visit_detail_source_concept_id Yes integer NA If the VISIT_DETAIL_SOURCE_VALUE is coded in the source data using an OMOP supported vocabulary put the concept id representing the source value here. If not available, map to 0. No Yes CONCEPT CONCEPT_ID NA NA NA
55 visit_detail admitted_from_concept_id admitted_from_source_value No varchar(50) NA This information may be called something different in the source data but the field is meant to contain a value indicating where a person was admitted from. Typically this applies only to visits that have a length of stay, like inpatient visits or long-term care visits. No No NA NA NA NA NA
56 visit_detail admitted_from_source_value admitted_from_concept_id Yes integer Use this field to determine where the patient was admitted from. This concept is part of the visit domain and can indicate if a patient was admitted to the hospital from a long-term care facility, for example. If available, map the admitted_from_source_value to a standard concept in the visit domain. If not available, map to 0. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Visit&standardConcept=Standard&page=1&pageSize=15&query=). No Yes CONCEPT CONCEPT_ID Visit NA NA
57 visit_detail discharge_to_source_value No varchar(50) NA This information may be called something different in the source data but the field is meant to contain a value indicating where a person was discharged to after a visit, as in they went home or were moved to long-term care. Typically this applies only to visits that have a length of stay of a day or more. No No NA NA NA NA NA
58 visit_detail discharge_to_concept_id Yes integer Use this field to determine where the patient was discharged to after a visit detail record. This concept is part of the visit domain and can indicate if a patient was discharged to home or sent to a long-term care facility, for example. If available, map the DISCHARGE_TO_SOURCE_VALUE to a Standard Concept in the Visit domain. If not available, set to 0. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Visit&standardConcept=Standard&page=1&pageSize=15&query=). No Yes CONCEPT CONCEPT_ID Visit NA NA
59 visit_detail preceding_visit_detail_id No bigint Use this field to find the visit detail that occurred for the person prior to the given visit detail record. There could be a few days or a few years in between. The PRECEDING_VISIT_DETAIL_ID can be used to link a visit immediately preceding the current Visit Detail. Note this is not symmetrical, and there is no such thing as a "following_visit_id". No Yes VISIT_DETAIL VISIT_DETAIL_ID NA NA NA
60 visit_detail visit_detail_parent_id No bigint Use this field to find the visit detail that subsumes the given visit detail record. This is used in the case that a visit detail record needs to be nested beyond the VISIT_OCCURRENCE/VISIT_DETAIL relationship. If there are multiple nested levels to how Visits are represented in the source, the VISIT_DETAIL_PARENT_ID can be used to record this relationship. No Yes VISIT_DETAIL VISIT_DETAIL_ID NA NA NA
61 visit_detail visit_occurrence_id Yes bigint Use this field to link the VISIT_DETAIL record to its VISIT_OCCURRENCE. Put the VISIT_OCCURRENCE_ID that subsumes the VISIT_DETAIL record here. No Yes VISIT_OCCURRENCE VISIT_OCCURRENCE_ID NA NA NA
62 condition_occurrence condition_occurrence_id Yes bigint The unique key given to a condition record for a person. Refer to the ETL for how duplicate conditions during the same visit were handled. Each instance of a condition present in the source data should be assigned this unique key. In some cases, a person can have multiple records of the same condition within the same visit. It is valid to keep these duplicates and assign them individual, unique, CONDITION_OCCURRENCE_IDs, though it is up to the ETL how they should be handled. Yes No NA NA NA NA NA
64 condition_occurrence condition_concept_id Yes integer The CONDITION_CONCEPT_ID field is recommended for primary use in analyses, and must be used for network studies. This is the standard concept mapped from the source value which represents a condition The CONCEPT_ID that the CONDITION_SOURCE_VALUE maps to. Only records whose source values map to concepts with a domain of "Condition" should go in this table. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Condition&standardConcept=Standard&page=1&pageSize=15&query=). No Yes CONCEPT CONCEPT_ID Condition NA NA
65 condition_occurrence condition_start_date Yes date Use this date to determine the start date of the condition Most often data sources do not have the idea of a start date for a condition. Rather, if a source only has one date associated with a condition record it is acceptable to use that date for both the CONDITION_START_DATE and the CONDITION_END_DATE. No No NA NA NA NA NA
66 condition_occurrence condition_start_datetime No datetime NA If a source does not specify datetime the convention is to set the time to midnight (00:00:0000) No No NA NA NA NA NA
67 condition_occurrence condition_end_date No date Use this date to determine the end date of the condition Most often data sources do not have the idea of a start date for a condition. Rather, if a source only has one date associated with a condition record it is acceptable to use that date for both the CONDITION_START_DATE and the CONDITION_END_DATE. No No NA NA NA NA NA
68 condition_occurrence condition_end_datetime No datetime NA If a source does not specify datetime the convention is to set the time to midnight (00:00:0000) No No NA NA NA NA NA
69 condition_occurrence condition_type_concept_id Yes integer This field can be used to determine the provenance of the Condition record, as in whether the condition was from an EHR system, insurance claim, registry, or other sources. Choose the condition_type_concept_id that best represents the provenance of the record. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Type+Concept&standardConcept=Standard&page=1&pageSize=15&query=). No Yes CONCEPT CONCEPT_ID Type Concept NA NA
70 condition_occurrence condition_status_concept_id Yes integer This concept represents the point during the visit the diagnosis was given (admitting diagnosis, final diagnosis), whether the diagnosis was determined due to laboratory findings, if the diagnosis was exclusionary, or if it was a preliminary diagnosis, among others. Choose the Concept in the Condition Status domain that best represents the point during the visit when the diagnosis was given. These can include admitting diagnosis, principal diagnosis, and secondary diagnosis. If not available, set to 0. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Condition+Status&standardConcept=Standard&page=1&pageSize=15&query=). No Yes CONCEPT CONCEPT_ID NA NA NA
71 condition_occurrence stop_reason No varchar(20) The Stop Reason indicates why a Condition is no longer valid with respect to the purpose within the source data. Note that a Stop Reason does not necessarily imply that the condition is no longer occurring. This information is often not populated in source data and it is a valid etl choice to leave it blank if the information does not exist. No No NA NA NA NA NA
89 drug_exposure quantity No float NA To find the dose form of a drug the RELATIONSHIP table can be used where the relationship_id is 'Has dose form'. If liquid, quantity stands for the total amount dispensed or ordered of ingredient in the units given by the drug_strength table. If the unit from the source data does not align with the unit in the DRUG_STRENGTH table the quantity should be converted to the correct unit given in DRUG_STRENGTH. For clinical drugs with fixed dose forms (tablets etc.) the quantity is the number of units/tablets/capsules prescribed or dispensed (can be partial, but then only 1/2 or 1/3, not 0.01). Clinical drugs with divisible dose forms (injections) the quantity is the amount of ingredient the patient got. For example, if the injection is 2mg/mL but the patient got 80mL then quantity is reported as 160. Quantified clinical drugs with divisible dose forms (prefilled syringes), the quantity is the amount of ingredient similar to clinical drugs. Please see [how to calculate drug dose](https://ohdsi.github.io/CommonDataModel/drug_dose.html) for more information. No No NA NA NA NA NA
90 drug_exposure days_supply No integer The number of days of supply of the medication as recorded in the original prescription or dispensing record. Days supply can differ from actual drug duration (i.e. prescribed days supply vs actual exposure). The field should be left empty if the source data does not contain a verbatim days_supply, and should not be calculated from other fields. Negative values are not allowed. Several actions are possible: 1) record is not trustworthy and we remove the record entirely. 2) we trust the record and leave days_supply empty or 3) record needs to be combined with other record (e.g. reversal of prescription). High values (>365 days) should be investigated. If considered an error in the source data (e.g. typo), the value needs to be excluded to prevent creation of unrealistic long eras. No No NA NA NA NA NA
91 drug_exposure sig No varchar(MAX) This is the verbatim instruction for the drug as written by the provider. Put the written out instructions for the drug as it is verbatim in the source, if available. No No NA NA NA NA NA
92 drug_exposure route_concept_id No integer NA The standard CONCEPT_ID that the ROUTE_SOURCE_VALUE maps to in the route domain. The standard CONCEPT_ID that the ROUTE_SOURCE_VALUE maps to in the route domain. This is meant to represent the route of administration of the drug. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Route&standardConcept=Standard&page=1&pageSize=15&query=) No Yes CONCEPT CONCEPT_ID Route NA NA
93 drug_exposure lot_number No varchar(50) NA NA No No NA NA NA NA NA
94 drug_exposure provider_id No bigint The Provider associated with drug record, e.g. the provider who wrote the prescription or the provider who administered the drug. The ETL may need to make a choice as to which PROVIDER_ID to put here. Based on what is available this may or may not be different than the provider associated with the overall VISIT_OCCURRENCE record, for example the ordering vs administering physician on an EHR record. No Yes PROVIDER PROVIDER_ID NA NA NA
95 drug_exposure visit_occurrence_id No bigint The Visit during which the drug was prescribed, administered or dispensed. To populate this field drug exposures must be explicitly initiated in the visit. No Yes VISIT_OCCURRENCE VISIT_OCCURRENCE_ID NA NA NA
96 drug_exposure visit_detail_id No bigint The VISIT_DETAIL record during which the drug exposure occurred. For example, if the person was in the ICU at the time of the drug administration the VISIT_OCCURRENCE record would reflect the overall hospital stay and the VISIT_DETAIL record would reflect the ICU stay during the hospital visit. Same rules apply as for the VISIT_OCCURRENCE_ID. No Yes VISIT_DETAIL VISIT_DETAIL_ID NA NA NA
97 drug_exposure drug_source_value No varchar(50) This field houses the verbatim value from the source data representing the drug exposure that occurred. For example, this could be an NDC or Gemscript code. This code is mapped to a Standard Drug Concept in the Standardized Vocabularies and the original code is stored here for reference. No No NA NA NA NA NA
98 drug_exposure drug_source_concept_id Yes integer This is the concept representing the drug source value and may not necessarily be standard. This field is discouraged from use in analysis because it is not required to contain Standard Concepts that are used across the OHDSI community, and should only be used when Standard Concepts do not adequately represent the source detail for the Drug necessary for a given analytic use case. Consider using DRUG_CONCEPT_ID instead to enable standardized analytics that can be consistent across the network. If the DRUG_SOURCE_VALUE is coded in the source data using an OMOP supported vocabulary put the concept id representing the source value here. If unavailable, set to 0. No Yes CONCEPT CONCEPT_ID NA NA NA
99 drug_exposure route_source_value No varchar(50) This field houses the verbatim value from the source data representing the drug route. This information may be called something different in the source data but the field is meant to contain a value indicating when and how a drug was given to a patient. This source value is mapped to a standard concept which is stored in the ROUTE_CONCEPT_ID field. No No NA NA NA NA NA
100 drug_exposure dose_unit_source_value No varchar(50) This field houses the verbatim value from the source data representing the dose unit of the drug given. This information may be called something different in the source data but the field is meant to contain a value indicating the unit of dosage of drug given to the patient. This is an older column and will be deprecated in an upcoming version. No No NA NA NA NA NA
101 procedure_occurrence procedure_occurrence_id Yes bigint The unique key given to a procedure record for a person. Refer to the ETL for how duplicate procedures during the same visit were handled. Each instance of a procedure occurrence in the source data should be assigned this unique key. In some cases, a person can have multiple records of the same procedure within the same visit. It is valid to keep these duplicates and assign them individual, unique, PROCEDURE_OCCURRENCE_IDs, though it is up to the ETL how they should be handled. Yes No NA NA NA NA NA
102 procedure_occurrence person_id Yes bigint The PERSON_ID of the PERSON for whom the procedure is recorded. This may be a system generated code. NA No Yes PERSON PERSON_ID NA NA NA
103 procedure_occurrence procedure_concept_id Yes integer The PROCEDURE_CONCEPT_ID field is recommended for primary use in analyses, and must be used for network studies. This is the standard concept mapped from the source value which represents a procedure The CONCEPT_ID that the PROCEDURE_SOURCE_VALUE maps to. Only records whose source values map to standard concepts with a domain of "Procedure" should go in this table. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Procedure&standardConcept=Standard&page=1&pageSize=15&query=). No Yes CONCEPT CONCEPT_ID Procedure NA NA
104 procedure_occurrence procedure_date No date Use this date to determine the date the procedure occurred. If a procedure lasts more than a day, then it should be recorded as a separate record for each day the procedure occurred, this logic is in lieu of the procedure_end_date, which will be added in a future version of the CDM. No No NA NA NA NA NA
105 procedure_occurrence procedure_datetime Yes datetime NA This is not required, though it is in v6. If a source does not specify datetime the convention is to set the time to midnight (00:00:0000) No No NA NA NA NA NA
106 procedure_occurrence procedure_type_concept_id Yes integer This field can be used to determine the provenance of the Procedure record, as in whether the procedure was from an EHR system, insurance claim, registry, or other sources. Choose the PROCEDURE_TYPE_CONCEPT_ID that best represents the provenance of the record, for example whether it came from an EHR record or billing claim. If a procedure is recorded as an EHR encounter, the PROCEDURE_TYPE_CONCEPT would be 'EHR encounter record'. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Type+Concept&standardConcept=Standard&page=1&pageSize=15&query=). No Yes CONCEPT CONCEPT_ID Type Concept NA NA
107 procedure_occurrence modifier_concept_id No integer The modifiers are intended to give additional information about the procedure but as of now the vocabulary is under review. It is up to the ETL to choose how to map modifiers if they exist in source data. These concepts are typically distinguished by 'Modifier' concept classes (e.g., 'CPT4 Modifier' as part of the 'CPT4' vocabulary). If there is more than one modifier on a record, one should be chosen that pertains to the procedure rather than provider. If not available, set to 0. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?conceptClass=CPT4+Modifier&conceptClass=HCPCS+Modifier&vocabulary=CPT4&vocabulary=HCPCS&standardConcept=Standard&page=1&pageSize=15&query=). No Yes CONCEPT CONCEPT_ID NA NA NA
108 procedure_occurrence quantity No integer If the quantity value is omitted, a single procedure is assumed. If a Procedure has a quantity of '0' in the source, this should default to '1' in the ETL. If there is a record in the source it can be assumed the exposure occurred at least once No No NA NA NA NA NA
109 procedure_occurrence provider_id No bigint The provider associated with the procedure record, e.g. the provider who performed the Procedure. The ETL may need to make a choice as to which PROVIDER_ID to put here. Based on what is available this may or may not be different than the provider associated with the overall VISIT_OCCURRENCE record, for example the admitting vs attending physician on an EHR record. No No PROVIDER PROVIDER_ID NA NA NA
133 measurement measurement_date Yes date Use this date to determine the date of the measurement. If there are multiple dates in the source data associated with a record such as order_date, draw_date, and result_date, choose the one that is closest to the date the sample was drawn from the patient. No No NA NA NA NA NA
134 measurement measurement_datetime No datetime NA This is not required, though it is in v6. If a source does not specify datetime the convention is to set the time to midnight (00:00:0000) No No NA NA NA NA NA
135 measurement measurement_time No varchar(10) NA This is present for backwards compatibility and will be deprecated in an upcoming version. No No NA NA NA NA NA
136 measurement measurement_type_concept_id Yes integer This field can be used to determine the provenance of the Measurement record, as in whether the measurement was from an EHR system, insurance claim, registry, or other sources. Choose the MEASUREMENT_TYPE_CONCEPT_ID that best represents the provenance of the record, for example whether it came from an EHR record or billing claim. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Type+Concept&standardConcept=Standard&page=1&pageSize=15&query=). No Yes CONCEPT CONCEPT_ID Type Concept NA NA
137 measurement operator_concept_id No integer The meaning of Concept [4172703](https://athena.ohdsi.org/search-terms/terms/4172703) for '=' is identical to omission of a OPERATOR_CONCEPT_ID value. Since the use of this field is rare, it's important when devising analyses to not to forget testing for the content of this field for values different from =. Operators are <, <=, =, >=, > and these concepts belong to the 'Meas Value Operator' domain. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Meas+Value+Operator&standardConcept=Standard&page=1&pageSize=15&query=). The operator_concept_id explictly refers to the value of the measurement. Operators are <, <=, =, >=, > and these concepts belong to the 'Meas Value Operator' domain. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Meas+Value+Operator&standardConcept=Standard&page=1&pageSize=15&query=). No Yes CONCEPT CONCEPT_ID NA NA NA
138 measurement value_as_number No float This is the numerical value of the Result of the Measurement, if available. Note that measurements such as blood pressures will be split into their component parts i.e. one record for systolic, one record for diastolic. If there is a negative value coming from the source, set the VALUE_AS_NUMBER to NULL, with the exception of the following Measurements (listed as LOINC codes):<br>- [1925-7](https://athena.ohdsi.org/search-terms/terms/3003396) Base excess in Arterial blood by calculation - [1927-3](https://athena.ohdsi.org/search-terms/terms/3002032) Base excess in Venous blood by calculation - [8632-2](https://athena.ohdsi.org/search-terms/terms/3006277) QRS-Axis - [11555-0](https://athena.ohdsi.org/search-terms/terms/3012501) Base excess in Blood by calculation - [1926-5](https://athena.ohdsi.org/search-terms/terms/3003129) Base excess in Capillary blood by calculation - [28638-5](https://athena.ohdsi.org/search-terms/terms/3004959) Base excess in Arterial cord blood by calculation [28639-3](https://athena.ohdsi.org/search-terms/terms/3007435) Base excess in Venous cord blood by calculation No No NA NA NA NA NA
139 measurement value_as_concept_id No integer If the raw data gives a categorial result for measurements those values are captured and mapped to standard concepts in the 'Meas Value' domain. If the raw data provides categorial results as well as continuous results for measurements, it is a valid ETL choice to preserve both values. The continuous value should go in the VALUE_AS_NUMBER field and the categorical value should be mapped to a standard concept in the 'Meas Value' domain and put in the VALUE_AS_CONCEPT_ID field. This is also the destination for the 'Maps to value' relationship. No Yes CONCEPT CONCEPT_ID NA NA NA
148 measurement unit_source_value No varchar(50) This field houses the verbatim value from the source data representing the unit of the Measurement that occurred. This code is mapped to a Standard Condition Concept in the Standardized Vocabularies and the original code is stored here for reference. No No NA NA NA NA NA
149 measurement value_source_value No varchar(50) This field houses the verbatim result value of the Measurement from the source data . If both a continuous and categorical result are given in the source data such that both VALUE_AS_NUMBER and VALUE_AS_CONCEPT_ID are both included, store the verbatim value that was mapped to VALUE_AS_CONCEPT_ID here. No No NA NA NA NA NA
150 observation observation_id Yes bigint The unique key given to an Observation record for a Person. Refer to the ETL for how duplicate Observations during the same Visit were handled. Each instance of an observation present in the source data should be assigned this unique key. Yes No NA NA NA NA NA
151 observation person_id Yes bigint The PERSON_ID of the Person for whom the Observation is recorded. This may be a system generated code. NA No Yes PERSON PERSON_ID NA NA NA
152 observation observation_concept_id Yes integer The OBSERVATION_CONCEPT_ID field is recommended for primary use in analyses, and must be used for network studies. The CONCEPT_ID that the OBSERVATION_SOURCE_CONCEPT_ID maps to. There is no specified domain that the Concepts in this table must adhere to. The only rule is that records with Concepts in the Condition, Procedure, Drug, Measurement, or Device domains MUST go to the corresponding table. No Yes CONCEPT CONCEPT_ID NA NA NA
153 observation observation_date No date The date of the Observation. Depending on what the Observation represents this could be the date of a lab test, the date of a survey, or the date a patient's family history was taken. For some observations the ETL may need to make a choice as to which date to choose. No No NA NA NA NA NA
154 observation observation_datetime Yes datetime NA If no time is given set to midnight (00:00:00). No No NA NA NA NA NA
196 note_nlp section_concept_id No integer NA The SECTION_CONCEPT_ID should be used to represent the note section contained in the NOTE_NLP record. These concepts can be found as parts of document panels and are based on the type of note written, i.e. a discharge summary. These panels can be found as concepts with the relationship 'Subsumes' to CONCEPT_ID [45875957](https://athena.ohdsi.org/search-terms/terms/45875957). No Yes CONCEPT CONCEPT_ID NA NA NA
197 note_nlp snippet No varchar(250) A small window of text surrounding the term NA No No NA NA NA NA NA
198 note_nlp \"offset\" No varchar(50) Character offset of the extracted term in the input note NA No No NA NA NA NA NA
199 note_nlp lexical_variant Yes varchar(250) Raw text extracted from the NLP tool. NA No No NA NA NA NA NA
200 note_nlp note_nlp_concept_id No integer NA NA No Yes CONCEPT CONCEPT_ID NA NA NA
201 note_nlp note_nlp_source_concept_id No integer NA NA No Yes CONCEPT CONCEPT_ID NA NA NA
202 note_nlp nlp_system No varchar(250) NA Name and version of the NLP system that extracted the term. Useful for data provenance. No No NA NA NA NA NA
217 specimen disease_status_concept_id No integer NA NA No Yes CONCEPT CONCEPT_ID NA NA NA
218 specimen specimen_source_id No varchar(50) This is the identifier for the specimen from the source system. NA No No NA NA NA NA NA
219 specimen specimen_source_value No varchar(50) NA NA No No NA NA NA NA NA
220 specimen unit_source_value No varchar(50) NA This unit for the quantity of the specimen, as represented in the source. No No NA NA NA NA NA
221 specimen anatomic_site_source_value No varchar(50) NA This is the site on the body where the specimen was taken from, as represented in the source. No No NA NA NA NA NA
222 specimen disease_status_source_value No varchar(50) NA NA No No NA NA NA NA NA
223 fact_relationship domain_concept_id_1 Yes integer NA NA No Yes CONCEPT CONCEPT_ID NA NA NA
224 fact_relationship fact_id_1 Yes bigint NA NA No No NA NA NA NA NA
225 fact_relationship domain_concept_id_2 Yes integer NA NA No Yes CONCEPT CONCEPT_ID NA NA NA
226 fact_relationship fact_id_2 Yes bigint NA NA No No NA NA NA NA NA
227 fact_relationship relationship_concept_id Yes integer NA NA No Yes CONCEPT CONCEPT_ID NA NA NA
228 survey_conduct survey_conduct_id Yes bigint Unique identifier for each completed survey. For each instance of a survey completion create a unique identifier. Yes No NA NA NA NA NA
229 survey_conduct person_id Yes bigint NA NA No Yes PERSON PERSON_ID NA NA NA
230 survey_conduct survey_concept_id Yes integer This is the Concept that represents the survey that was completed. Put the CONCEPT_ID that identifies the survey that the Person completed. There is no specified domain for this table but the concept class 'staging/scales' contains many common surveys. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?standardConcept=Standard&conceptClass=Staging+%2F+Scales&page=5&pageSize=15&query=). No Yes CONCEPT CONCEPT_ID NA NA NA
231 survey_conduct survey_start_date No date Date on which the survey was started. NA No No NA NA NA NA NA
232 survey_conduct survey_start_datetime No datetime NA If no time given, set to midnight. No No NA NA NA NA NA
233 survey_conduct survey_end_date No date Date on which the survey was completed. NA No No NA NA NA NA NA
234 survey_conduct survey_end_datetime Yes datetime NA If no time given, set to midnight. No No NA NA NA NA NA
235 survey_conduct provider_id No bigint This is the Provider associated with the survey completion. The ETL may need to make a choice as to which Provider to put here. This could either be the provider that ordered the survey or the provider who observed the completion of the survey. No Yes PROVIDER PROVIDER_ID NA NA NA
236 survey_conduct assisted_concept_id Yes integer This is a Concept that represents whether the survey was completed with assistance or independently. There is no specific domain or class for this field, just choose the one that best represents the value given in the source. No Yes CONCEPT CONCEPT_ID NA NA NA
237 survey_conduct respondent_type_concept_id Yes integer This is a Concept that represents who actually recorded the answers to the survey. For example, this could be the patient or a research associate. There is no specific domain or class for this field, just choose the one that best represents the value given in the source. No Yes CONCEPT CONCEPT_ID NA NA NA
238 survey_conduct timing_concept_id Yes integer This is a Concept that represents the timing of the survey. For example this could be the 3-month follow-up appointment. There is no specific domain or class for this field, just choose the one that best represents the value given in the source. No Yes CONCEPT CONCEPT_ID NA NA NA
356 cdm_source source_description No varchar(MAX) The description of the CDM instance. NA No No NA NA NA NA NA
357 cdm_source source_documentation_reference No varchar(255) NA NA No No NA NA NA NA NA
358 cdm_source cdm_etl_reference No varchar(255) NA Put the link to the CDM version used. No No NA NA NA NA NA
359 cdm_source source_release_date No date The release date of the source data. NA No No NA NA NA NA NA
360 cdm_source cdm_release_date No date The release data of the CDM instance. NA No No NA NA NA NA NA
361 cdm_source cdm_version No varchar(10) NA NA No No NA NA NA NA NA
362 cdm_source vocabulary_version No varchar(20) NA NA No No NA NA NA NA NA
363 concept concept_id Yes integer A unique identifier for each Concept across all domains. NA Yes No NA NA NA NA NA
364 concept concept_name Yes varchar(255) An unambiguous, meaningful and descriptive name for the Concept. NA No No NA NA NA NA NA
372 concept invalid_reason No varchar(1) Reason the Concept was invalidated. Possible values are D (deleted), U (replaced with an update) or NULL when valid_end_date has the default value. NA No No NA NA NA NA NA
373 vocabulary vocabulary_id Yes varchar(20) A unique identifier for each Vocabulary, such as ICD9CM, SNOMED, Visit. NA Yes No NA NA NA NA NA
374 vocabulary vocabulary_name Yes varchar(255) The name describing the vocabulary, for example International Classification of Diseases, Ninth Revision, Clinical Modification, Volume 1 and 2 (NCHS) etc. NA No No NA NA NA NA NA
375 vocabulary vocabulary_reference Yes varchar(255) External reference to documentation or available download of the about the vocabulary. NA No No NA NA NA NA NA
376 vocabulary vocabulary_version No varchar(255) Version of the Vocabulary as indicated in the source. NA No No NA NA NA NA NA
377 vocabulary vocabulary_concept_id Yes integer A Concept that represents the Vocabulary the VOCABULARY record belongs to. NA No Yes CONCEPT CONCEPT_ID NA NA NA
378 domain domain_id Yes varchar(20) A unique key for each domain. NA Yes No NA NA NA NA NA
379 domain domain_name Yes varchar(255) The name describing the Domain, e.g. Condition, Procedure, Measurement etc. NA No No NA NA NA NA NA
380 domain domain_concept_id Yes integer A Concept representing the Domain Concept the DOMAIN record belongs to. NA No Yes CONCEPT CONCEPT_ID NA NA NA
381 concept_class concept_class_id Yes varchar(20) A unique key for each class. NA Yes No NA NA NA NA NA
382 concept_class concept_class_name Yes varchar(255) The name describing the Concept Class, e.g. Clinical Finding, Ingredient, etc. NA No No NA NA NA NA NA
383 concept_class concept_class_concept_id Yes integer A Concept that represents the Concept Class. NA No Yes CONCEPT CONCEPT_ID NA NA NA
384 concept_relationship concept_id_1 Yes integer NA NA No Yes CONCEPT CONCEPT_ID NA NA NA
385 concept_relationship concept_id_2 Yes integer NA NA No Yes CONCEPT CONCEPT_ID NA NA NA
386 concept_relationship relationship_id Yes varchar(20) The relationship between CONCEPT_ID_1 and CONCEPT_ID_2. Please see the [Vocabulary Conventions](https://ohdsi.github.io/CommonDataModel/dataModelConventions.html#concept_relationships). for more information. NA No Yes RELATIONSHIP RELATIONSHIP_ID NA NA NA
387 concept_relationship valid_start_date Yes date The date when the relationship is first recorded. NA No No NA NA NA NA NA
388 concept_relationship valid_end_date Yes date The date when the relationship is invalidated. NA No No NA NA NA NA NA
389 concept_relationship invalid_reason No varchar(1) Reason the relationship was invalidated. Possible values are 'D' (deleted), 'U' (updated) or NULL. NA No No NA NA NA NA NA
390 relationship relationship_id Yes varchar(20) NA NA Yes No NA NA NA NA NA
391 relationship relationship_name Yes varchar(255) NA NA No No NA NA NA NA NA
406 source_to_concept_map source_code_description No varchar(255) An optional description for the source code. This is included as a convenience to compare the description of the source code to the name of the concept. NA No No NA NA NA NA NA
407 source_to_concept_map target_concept_id Yes integer The target Concept to which the source code is being mapped. NA No Yes CONCEPT CONCEPT_ID NA NA NA
408 source_to_concept_map target_vocabulary_id Yes varchar(20) The Vocabulary of the target Concept. NA No Yes VOCABULARY VOCABULARY_ID NA NA NA
409 source_to_concept_map valid_start_date Yes date The date when the mapping instance was first recorded. NA No No NA NA NA NA NA
410 source_to_concept_map valid_end_date Yes date The date when the mapping instance became invalid because it was deleted or superseded (updated) by a new relationship. Default value is 31-Dec-2099. NA No No NA NA NA NA NA
411 source_to_concept_map invalid_reason No varchar(1) Reason the mapping instance was invalidated. Possible values are D (deleted), U (replaced with an update) or NULL when valid_end_date has the default value. NA No No NA NA NA NA NA
412 drug_strength drug_concept_id Yes integer The Concept representing the Branded Drug or Clinical Drug Product. NA No Yes CONCEPT CONCEPT_ID NA NA NA
413 drug_strength ingredient_concept_id Yes integer The Concept representing the active ingredient contained within the drug product. Combination Drugs will have more than one record in this table, one for each active Ingredient. No Yes CONCEPT CONCEPT_ID NA NA NA
414 drug_strength amount_value No float The numeric value or the amount of active ingredient contained within the drug product. NA No No NA NA NA NA NA
415 drug_strength amount_unit_concept_id No integer The Concept representing the Unit of measure for the amount of active ingredient contained within the drug product. NA No Yes CONCEPT CONCEPT_ID NA NA NA
416 drug_strength numerator_value No float The concentration of the active ingredient contained within the drug product. NA No No NA NA NA NA NA
417 drug_strength numerator_unit_concept_id No integer The Concept representing the Unit of measure for the concentration of active ingredient. NA No Yes CONCEPT CONCEPT_ID NA NA NA
418 drug_strength denominator_value No float The amount of total liquid (or other divisible product, such as ointment, gel, spray, etc.). NA No No NA NA NA NA NA
419 drug_strength denominator_unit_concept_id No integer The Concept representing the denominator unit for the concentration of active ingredient. NA No Yes CONCEPT CONCEPT_ID NA NA NA
420 drug_strength box_size No integer The number of units of Clinical Branded Drug or Quantified Clinical or Branded Drug contained in a box as dispensed to the patient. NA No No NA NA NA NA NA
421 drug_strength valid_start_date Yes date The date when the Concept was first recorded. The default value is 1-Jan-1970. NA No No NA NA NA NA NA
422 drug_strength valid_end_date Yes date The date when then Concept became invalid. NA No No NA NA NA NA NA
423 drug_strength invalid_reason No varchar(1) Reason the concept was invalidated. Possible values are D (deleted), U (replaced with an update) or NULL when valid_end_date has the default value. NA No No NA NA NA NA NA
424 cohort cohort_definition_id Yes integer NA NA No No NA NA NA NA NA
425 cohort subject_id Yes integer NA NA No No NA NA NA NA NA
426 cohort cohort_start_date Yes date NA NA No No NA NA NA NA NA
427 cohort cohort_end_date Yes date NA NA No No NA NA NA NA NA
428 cohort_definition cohort_definition_id Yes integer This is the identifier given to the cohort, usually by the ATLAS application NA No Yes COHORT COHORT_DEFINITION_ID NA NA NA
429 cohort_definition cohort_definition_name Yes varchar(255) A short description of the cohort NA No No NA NA NA NA NA
430 cohort_definition cohort_definition_description No varchar(MAX) A complete description of the cohort. NA No No NA NA NA NA NA
431 cohort_definition definition_type_concept_id Yes integer Type defining what kind of Cohort Definition the record represents and how the syntax may be executed. NA No Yes CONCEPT CONCEPT_ID NA NA NA
432 cohort_definition cohort_definition_syntax No varchar(MAX) Syntax or code to operationalize the Cohort Definition. NA No No NA NA NA NA NA
433 cohort_definition subject_concept_id Yes integer This field contains a Concept that represents the domain of the subjects that are members of the cohort (e.g., Person, Provider, Visit). NA No Yes CONCEPT CONCEPT_ID NA NA NA
434 cohort_definition cohort_initiation_date No date A date to indicate when the Cohort was initiated in the COHORT table. NA No No NA NA NA NA NA
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@ -1,6 +1,6 @@
cdmTableName,schema,isRequired,conceptPrefix,measurePersonCompleteness,measurePersonCompletenessThreshold,validation,tableDescription,userGuidance,etlConventions
person,CDM,Yes,NA,No,NA,NA,"This table serves as the central identity management for all Persons in the database. It contains records that uniquely identify each person or patient, and some demographic information.",All records in this table are independent Persons.,"All Persons in a database needs one record in this table, unless they fail data quality requirements specified in the ETL. Persons with no Events should have a record nonetheless. If more than one data source contributes Events to the database, Persons must be reconciled, if possible, across the sources to create one single record per Person. The BIRTH_DATETIME must be equivalent to the content of BIRTH_DAY, BIRTH_MONTH and BIRTH_YEAR. There is a helpful rule listed in table below for how to derive BIRTH_DATETIME if it is not available in the source. **New to CDM v6.0** The person's death date is now stored in this table instead of the separate DEATH table. In the case that multiple dates of death are given in the source data the ETL should make a choice as to which death date to put in the PERSON table. Any additional dates can be stored in the OBSERVATION table using the concept [4265167](https://athena.ohdsi.org/search-terms/terms/4265167) which stands for 'Date of death' . Similarly, the cause of death is stored in the CONDITION_OCCURRENCE table using the CONDITION_STATUS_CONCEPT_ID [32891](https://athena.ohdsi.org/search-terms/terms/32891) for 'Cause of death'."
observation_period,CDM,Yes,NA,Yes,0,NA,"This table contains records which define spans of time during which two conditions are expected to hold: (i) Clinical Events that happened to the Person are recorded in the Event tables, and (ii) absence of records indicate such Events did not occur during this span of time.","For each Person, one or more OBSERVATION_PERIOD records may be present, but they will not overlap or be back to back to each other. Events may exist outside all of the time spans of the OBSERVATION_PERIOD records for a patient, however, absence of an Event outside these time spans cannot be construed as evidence of absence of an Event. Incidence or prevalence rates should only be calculated for the time of active OBSERVATION_PERIOD records. When constructing cohorts, outside Events can be used for inclusion criteria definition, but without any guarantee for the performance of these criteria. Also, OBSERVATION_PERIOD records can be as short as a single day, greatly disturbing the denominator of any rate calculation as part of cohort characterizations. To avoid that, apply minimal observation time as a requirement for any cohort definition.","Each Person needs to have at least one OBSERVATION_PERIOD record, which should represent time intervals with a high capture rate of Clinical Events. Some source data have very similar concepts, such as enrollment periods in insurance claims data. In other source data such as most EHR systems these time spans need to be inferred under a set of assumptions. It is the discretion of the ETL developer to define these assumptions. In many ETL solutions the start date of the first occurrence or the first high quality occurrence of a Clinical Event (Condition, Drug, Procedure, Device, Measurement, Visit) is defined as the start of the OBSERVATION_PERIOD record, and the end date of the last occurrence of last high quality occurrence of a Clinical Event, or the end of the database period becomes the end of the OBSERVATOIN_PERIOD for each Person. If a Person only has a single Clinical Event the OBSERVATION_PERIOD record can be as short as one day. Depending on these definitions it is possible that Clinical Events fall outside the time spans defined by OBSERVATION_PERIOD records. Family history or history of Clinical Events generally are not used to generate OBSERVATION_PERIOD records around the time they are referring to. Any two overlapping or adjacent OBSERVATION_PERIOD records have to be merged into one."
observation_period,CDM,Yes,NA,Yes,0,NA,"This table contains records which define spans of time during which two conditions are expected to hold: (i) Clinical Events that happened to the Person are recorded in the Event tables, and (ii) absence of records indicate such Events did not occur during this span of time.","For each Person, one or more OBSERVATION_PERIOD records may be present, but they will not overlap or be back to back to each other. Events may exist outside all of the time spans of the OBSERVATION_PERIOD records for a patient, however, absence of an Event outside these time spans cannot be construed as evidence of absence of an Event. Incidence or prevalence rates should only be calculated for the time of active OBSERVATION_PERIOD records. When constructing cohorts, outside Events can be used for inclusion criteria definition, but without any guarantee for the performance of these criteria. Also, OBSERVATION_PERIOD records can be as short as a single day, greatly disturbing the denominator of any rate calculation as part of cohort characterizations. To avoid that, apply minimal observation time as a requirement for any cohort definition.","Each Person needs to have at least one OBSERVATION_PERIOD record, which should represent time intervals with a high capture rate of Clinical Events. Some source data have very similar concepts, such as enrollment periods in insurance claims data. In other source data such as most EHR systems these time spans need to be inferred under a set of assumptions. It is the discretion of the ETL developer to define these assumptions. In many ETL solutions the start date of the first occurrence or the first high quality occurrence of a Clinical Event (Condition, Drug, Procedure, Device, Measurement, Visit) is defined as the start of the OBSERVATION_PERIOD record, and the end date of the last occurrence of last high quality occurrence of a Clinical Event, or the end of the database period becomes the end of the OBSERVATION_PERIOD for each Person. If a Person only has a single Clinical Event the OBSERVATION_PERIOD record can be as short as one day. Depending on these definitions it is possible that Clinical Events fall outside the time spans defined by OBSERVATION_PERIOD records. Family history or history of Clinical Events generally are not used to generate OBSERVATION_PERIOD records around the time they are referring to. Any two overlapping or adjacent OBSERVATION_PERIOD records have to be merged into one."
visit_occurrence,CDM,No,VISIT_,Yes,0,NA,"This table contains Events where Persons engage with the healthcare system for a duration of time. They are often also called ""Encounters"". Visits are defined by a configuration of circumstances under which they occur, such as (i) whether the patient comes to a healthcare institution, the other way around, or the interaction is remote, (ii) whether and what kind of trained medical staff is delivering the service during the Visit, and (iii) whether the Visit is transient or for a longer period involving a stay in bed.","The configuration defining the Visit are described by Concepts in the Visit Domain, which form a hierarchical structure, but rolling up to generally familiar Visits adopted in most healthcare systems worldwide:
- [Inpatient Visit](https://athena.ohdsi.org/search-terms/terms/9201): Person visiting hospital, at a Care Site, in bed, for duration of more than one day, with physicians and other Providers permanently available to deliver service around the clock
@ -17,7 +17,7 @@ visit_occurrence,CDM,No,VISIT_,Yes,0,NA,"This table contains Events where Person
The Visit duration, or 'length of stay', is defined as VISIT_END_DATE - VISIT_START_DATE. For all Visits this is <1 day, except Inpatient Visits and Non-hospital institution Visits. The CDM also contains the VISIT_DETAIL table where additional information about the Visit is stored, for example, transfers between units during an inpatient Visit.","Visits can be derived easily if the source data contain coding systems for Place of Service or Procedures, like CPT codes for well visits. In those cases, the codes can be looked up and mapped to a Standard Visit Concept. Otherwise, Visit Concepts have to be identified in the ETL process. This table will contain concepts in the Visit domain. These concepts are arranged in a hierarchical structure to facilitate cohort definitions by rolling up to generally familiar Visits adopted in most healthcare systems worldwide. Visits can be adjacent to each other, i.e. the end date of one can be identical with the start date of the other. As a consequence, more than one-day Visits or their descendants can be recorded for the same day. Multi-day visits must not overlap, i.e. share days other than start and end days. It is often the case that some logic should be written for how to define visits and how to assign Visit_Concept_Id. For example, in US claims outpatient visits that appear to occur within the time period of an inpatient visit can be rolled into one with the same Visit_Occurrence_Id. In EHR data inpatient visits that are within one day of each other may be strung together to create one visit. It will all depend on the source data and how encounter records should be translated to visit occurrences. Providers can be associated with a Visit through the PROVIDER_ID field, or indirectly through PROCEDURE_OCCURRENCE records linked both to the VISIT and PROVIDER tables."
visit_detail,CDM,No,VISIT_DETAIL_,Yes,0,NA,The VISIT_DETAIL table is an optional table used to represents details of each record in the parent VISIT_OCCURRENCE table. A good example of this would be the movement between units in a hospital during an inpatient stay or claim lines associated with a one insurance claim. For every record in the VISIT_OCCURRENCE table there may be 0 or more records in the VISIT_DETAIL table with a 1:n relationship where n may be 0. The VISIT_DETAIL table is structurally very similar to VISIT_OCCURRENCE table and belongs to the visit domain.,"The configuration defining the Visit Detail is described by Concepts in the Visit Domain, which form a hierarchical structure. The Visit Detail record will have an associated to the Visit Occurrence record in two ways: <br> 1. The Visit Detail record will have the VISIT_OCCURRENCE_ID it is associated to 2. The VISIT_DETAIL_CONCEPT_ID will be a descendant of the VISIT_CONCEPT_ID for the Visit.","It is not mandatory that the VISIT_DETAIL table be filled in, but if you find that the logic to create VISIT_OCCURRENCE records includes the roll-up of multiple smaller records to create one picture of a Visit then it is a good idea to use VISIT_DETAIL. In EHR data, for example, a Person may be in the hospital but instead of one over-arching Visit their encounters are recorded as times they interacted with a health care provider. A Person in the hospital interacts with multiple providers multiple times a day so the encounters must be strung together using some heuristic (defined by the ETL) to identify the entire Visit. In this case the encounters would be considered Visit Details and the entire Visit would be the Visit Occurrence. In this example it is also possible to use the Vocabulary to distinguish Visit Details from a Visit Occurrence by setting the VISIT_CONCEPT_ID to [9201](https://athena.ohdsi.org/search-terms/terms/9201) and the VISIT_DETAIL_CONCEPT_IDs either to 9201 or its children to indicate where the patient was in the hospital at the time of care."
condition_occurrence,CDM,No,CONDITION_,Yes,0,NA,"This table contains records of Events of a Person suggesting the presence of a disease or medical condition stated as a diagnosis, a sign, or a symptom, which is either observed by a Provider or reported by the patient.","Conditions are defined by Concepts from the Condition domain, which form a complex hierarchy. As a result, the same Person with the same disease may have multiple Condition records, which belong to the same hierarchical family. Most Condition records are mapped from diagnostic codes, but recorded signs, symptoms and summary descriptions also contribute to this table. Rule out diagnoses should not be recorded in this table, but in reality their negating nature is not always captured in the source data, and other precautions must be taken when when identifying Persons who should suffer from the recorded Condition. Record all conditions as they exist in the source data. Any decisions about diagnosis/phenotype definitions would be done through cohort specifications. These cohorts can be housed in the [COHORT](https://ohdsi.github.io/CommonDataModel/cdm531.html#payer_plan_period) table. Conditions span a time interval from start to end, but are typically recorded as single snapshot records with no end date. The reason is twofold: (i) At the time of the recording the duration is not known and later not recorded, and (ii) the Persons typically cease interacting with the healthcare system when they feel better, which leads to incomplete capture of resolved Conditions. The [CONDITION_ERA](https://ohdsi.github.io/CommonDataModel/cdm531.html#condition_era) table addresses this issue. Family history and past diagnoses ('history of') are not recorded in this table. Instead, they are listed in the [OBSERVATION](https://ohdsi.github.io/CommonDataModel/cdm531.html#observation) table. Codes written in the process of establishing the diagnosis, such as 'question of' of and 'rule out', should not represented here. Instead, they should be recorded in the [OBSERVATION](https://ohdsi.github.io/CommonDataModel/cdm531.html#observation) table, if they are used for analyses. However, this information is not always available.",Source codes and source text fields mapped to Standard Concepts of the Condition Domain have to be recorded here.
condition_occurrence,CDM,No,CONDITION_,Yes,0,NA,"This table contains records of Events of a Person suggesting the presence of a disease or medical condition stated as a diagnosis, a sign, or a symptom, which is either observed by a Provider or reported by the patient.","Conditions are defined by Concepts from the Condition domain, which form a complex hierarchy. As a result, the same Person with the same disease may have multiple Condition records, which belong to the same hierarchical family. Most Condition records are mapped from diagnostic codes, but recorded signs, symptoms and summary descriptions also contribute to this table. Rule out diagnoses should not be recorded in this table, but in reality their negating nature is not always captured in the source data, and other precautions must be taken when when identifying Persons who should suffer from the recorded Condition. Record all conditions as they exist in the source data. Any decisions about diagnosis/phenotype definitions would be done through cohort specifications. These cohorts can be housed in the [COHORT](https://ohdsi.github.io/CommonDataModel/cdm60.html#payer_plan_period) table. Conditions span a time interval from start to end, but are typically recorded as single snapshot records with no end date. The reason is twofold: (i) At the time of the recording the duration is not known and later not recorded, and (ii) the Persons typically cease interacting with the healthcare system when they feel better, which leads to incomplete capture of resolved Conditions. The [CONDITION_ERA](https://ohdsi.github.io/CommonDataModel/cdm60.html#condition_era) table addresses this issue. Family history and past diagnoses ('history of') are not recorded in this table. Instead, they are listed in the [OBSERVATION](https://ohdsi.github.io/CommonDataModel/cdm60.html#observation) table. Codes written in the process of establishing the diagnosis, such as 'question of' of and 'rule out', should not represented here. Instead, they should be recorded in the [OBSERVATION](https://ohdsi.github.io/CommonDataModel/cdm60.html#observation) table, if they are used for analyses. However, this information is not always available.",Source codes and source text fields mapped to Standard Concepts of the Condition Domain have to be recorded here.
drug_exposure,CDM,No,DRUG_,Yes,0,NA,"This table captures records about the exposure to a Drug ingested or otherwise introduced into the body. A Drug is a biochemical substance formulated in such a way that when administered to a Person it will exert a certain biochemical effect on the metabolism. Drugs include prescription and over-the-counter medicines, vaccines, and large-molecule biologic therapies. Radiological devices ingested or applied locally do not count as Drugs.","The purpose of records in this table is to indicate an exposure to a certain drug as best as possible. In this context a drug is defined as an active ingredient. Drug Exposures are defined by Concepts from the Drug domain, which form a complex hierarchy. As a result, one DRUG_SOURCE_CONCEPT_ID may map to multiple standard concept ids if it is a combination product. Records in this table represent prescriptions written, prescriptions dispensed, and drugs administered by a provider to name a few. The DRUG_TYPE_CONCEPT_ID can be used to find and filter on these types. This table includes additional information about the drug products, the quantity given, and route of administration.",Information about quantity and dose is provided in a variety of different ways and it is important for the ETL to provide as much information as possible from the data. Depending on the provenance of the data fields may be captured differently i.e. quantity for drugs administered may have a separate meaning from quantity for prescriptions dispensed. If a patient has multiple records on the same day for the same drug or procedures the ETL should not de-dupe them unless there is probable reason to believe the item is a true data duplicate. Take note on how to handle refills for prescriptions written.
procedure_occurrence,CDM,No,PROCEDURE_,Yes,0,NA,"This table contains records of activities or processes ordered by, or carried out by, a healthcare provider on the patient with a diagnostic or therapeutic purpose.","Lab tests are not a procedure, if something is observed with an expected resulting amount and unit then it should be a measurement. Phlebotomy is a procedure but so trivial that it tends to be rarely captured. It can be assumed that there is a phlebotomy procedure associated with many lab tests, therefore it is unnecessary to add them as separate procedures. If the user finds the same procedure over concurrent days, it is assumed those records are part of a procedure lasting more than a day. This logic is in lieu of the procedure_end_date, which will be added in a future version of the CDM.","If a procedure lasts more than a day, then it should be recorded as a separate record for each day the procedure occurred, this logic is in lieu of the PROCEDURE_END_DATE, which will be added in a future version of the CDM. When dealing with duplicate records, the ETL must determine whether to sum them up into one record or keep them separate. Things to consider are: - Same Procedure - Same PROCEDURE_DATETIME - Same Visit Occurrence or Visit Detail - Same Provider - Same Modifier for Procedures. Source codes and source text fields mapped to Standard Concepts of the Procedure Domain have to be recorded here."
device_exposure,CDM,No,DEVICE_,Yes,0,NA,"The Device domain captures information about a person's exposure to a foreign physical object or instrument which is used for diagnostic or therapeutic purposes through a mechanism beyond chemical action. Devices include implantable objects (e.g. pacemakers, stents, artificial joints), medical equipment and supplies (e.g. bandages, crutches, syringes), other instruments used in medical procedures (e.g. sutures, defibrillators) and material used in clinical care (e.g. adhesives, body material, dental material, surgical material).","The distinction between Devices or supplies and Procedures are sometimes blurry, but the former are physical objects while the latter are actions, often to apply a Device or supply.",Source codes and source text fields mapped to Standard Concepts of the Device Domain have to be recorded here.
@ -69,11 +69,9 @@ vocabulary,VOCAB,No,NA,No,NA,NA,The VOCABULARY table includes a list of the Voca
domain,VOCAB,No,NA,No,NA,NA,"The DOMAIN table includes a list of OMOP-defined Domains the Concepts of the Standardized Vocabularies can belong to. A Domain defines the set of allowable Concepts for the standardized fields in the CDM tables. For example, the ""Condition"" Domain contains Concepts that describe a condition of a patient, and these Concepts can only be stored in the condition_concept_id field of the CONDITION_OCCURRENCE and CONDITION_ERA tables. This reference table is populated with a single record for each Domain and includes a descriptive name for the Domain.",NA,NA
concept_class,VOCAB,No,NA,No,NA,NA,"The CONCEPT_CLASS table is a reference table, which includes a list of the classifications used to differentiate Concepts within a given Vocabulary. This reference table is populated with a single record for each Concept Class.",NA,NA
concept_relationship,VOCAB,No,NA,No,NA,NA,The CONCEPT_RELATIONSHIP table contains records that define direct relationships between any two Concepts and the nature or type of the relationship. Each type of a relationship is defined in the RELATIONSHIP table.,NA,NA
relationship,VOCAB,No,NA,No,NA,NA,The RELATIONSHIP table provides a reference list of all types of relationships that can be used to associate any two concepts in the CONCEPT_RELATIONSHP table.,NA,NA
concept_synonym,VOCAB,No,NA,No,NA,NA,The CONCEPT_SYNONYM table is used to store alternate names and descriptions for Concepts.,NA,NA
concept_ancestor,VOCAB,No,NA,No,NA,NA,"The CONCEPT_ANCESTOR table is designed to simplify observational analysis by providing the complete hierarchical relationships between Concepts. Only direct parent-child relationships between Concepts are stored in the CONCEPT_RELATIONSHIP table. To determine higher level ancestry connections, all individual direct relationships would have to be navigated at analysis time. The CONCEPT_ANCESTOR table includes records for all parent-child relationships, as well as grandparent-grandchild relationships and those of any other level of lineage. Using the CONCEPT_ANCESTOR table allows for querying for all descendants of a hierarchical concept. For example, drug ingredients and drug products are all descendants of a drug class ancestor.
This table is entirely derived from the CONCEPT, CONCEPT_RELATIONSHIP and RELATIONSHIP tables.",NA,NA
relationship,VOCAB,No,NA,No,NA,NA,"The RELATIONSHIP table provides a reference list of all types of relationships that can be used to associate any two Concepts in the CONCEPT_RELATIONSHIP table, the respective reverse relationships, and their hierarchical characteristics. Note, that Concepts representing relationships between the clinical facts, used for filling in the FACT_RELATIONSHIP table are stored in the CONCEPT table and belong to the Relationship Domain.","Users can leverage the RELATIONSHIP table to explore the full list of direct and reverse relationships within the OMOP vocabulary system. Also, users can get insight into how these relationships can be used in ETL, cohort creation, and other tasks according to their ancestral characteristics.",NA
concept_synonym,VOCAB,No,NA,No,NA,NA,"The CONCEPT_SYNONYM table captures alternative terms, synonyms, and translations of Concept Name into various languages linked to specific concepts, providing users with a comprehensive view of how Concepts may be expressed or referenced.","Users can leverage the CONCEPT_SYNONYM table to expand search capabilities and improve query accuracy by incorporating synonymous terms into data analysis and retrieval processes. Also, users can enhance their mapping efforts between local terminologies and standardized concepts by identifying synonymous terms associated with concepts in the CONCEPT_SYNONYM table.",NA
concept_ancestor,VOCAB,No,NA,No,NA,NA,"The CONCEPT_ANCESTOR table is designed to simplify observational analysis by providing the complete hierarchical relationships between Concepts. Only direct parent-child relationships between Concepts are stored in the CONCEPT_RELATIONSHIP table. To determine higher-level ancestry connections, all individual direct relationships would have to be navigated at analysis time. The CONCEPT_ANCESTOR table includes records for all parent-child relationships, as well as grandparent-grandchild relationships and those of any other level of lineage for Standard or Classification concepts. Using the CONCEPT_ANCESTOR table allows for querying for all descendants of a hierarchical concept, and the other way around. For example, drug ingredients and drug products, beneath them in the hierarchy, are all descendants of a drug class ancestor. This table is entirely derived from the CONCEPT, CONCEPT_RELATIONSHIP, and RELATIONSHIP tables.","The CONCEPT_ANCESTOR table can be used to explore the hierarchical relationships captured in the table to gain insights into the hierarchical structure of clinical concepts. Understanding the hierarchical relationships of concepts can facilitate accurate interpretation and analysis of healthcare data. Also, by incorporating hierarchical relationships from the CONCEPT_ANCESTOR table, users can create cohorts containing related concepts within a hierarchical structure, enabling more comprehensive cohort definitions.",NA
source_to_concept_map,VOCAB,No,NA,No,NA,NA,"The source to concept map table is a legacy data structure within the OMOP Common Data Model, recommended for use in ETL processes to maintain local source codes which are not available as Concepts in the Standardized Vocabularies, and to establish mappings for each source code into a Standard Concept as target_concept_ids that can be used to populate the Common Data Model tables. The SOURCE_TO_CONCEPT_MAP table is no longer populated with content within the Standardized Vocabularies published to the OMOP community.",NA,NA
drug_strength,VOCAB,No,NA,No,NA,NA,The DRUG_STRENGTH table contains structured content about the amount or concentration and associated units of a specific ingredient contained within a particular drug product. This table is supplemental information to support standardized analysis of drug utilization.,NA,NA
cohort,RESULTS,No,NA,No,NA,NA,The COHORT table contains records of subjects that satisfy a given set of criteria for a duration of time. The definition of the cohort is contained within the COHORT_DEFINITION table. It is listed as part of the RESULTS schema because it is a table that users of the database as well as tools such as ATLAS need to be able to write to. The CDM and Vocabulary tables are all read-only so it is suggested that the COHORT and COHORT_DEFINTION tables are kept in a separate schema to alleviate confusion.,NA,"Cohorts typically include patients diagnosed with a specific condition, patients exposed to a particular drug, but can also be Providers who have performed a specific Procedure. Cohort records must have a Start Date and an End Date, but the End Date may be set to Start Date or could have an applied censor date using the Observation Period Start Date. Cohort records must contain a Subject Id, which can refer to the Person, Provider, Visit record or Care Site though they are most often Person Ids. The Cohort Definition will define the type of subject through the subject concept id. A subject can belong (or not belong) to a cohort at any moment in time. A subject can only have one record in the cohort table for any moment of time, i.e. it is not possible for a person to contain multiple records indicating cohort membership that are overlapping in time"

1 cdmTableName schema isRequired conceptPrefix measurePersonCompleteness measurePersonCompletenessThreshold validation tableDescription userGuidance etlConventions
2 person CDM Yes NA No NA NA This table serves as the central identity management for all Persons in the database. It contains records that uniquely identify each person or patient, and some demographic information. All records in this table are independent Persons. All Persons in a database needs one record in this table, unless they fail data quality requirements specified in the ETL. Persons with no Events should have a record nonetheless. If more than one data source contributes Events to the database, Persons must be reconciled, if possible, across the sources to create one single record per Person. The BIRTH_DATETIME must be equivalent to the content of BIRTH_DAY, BIRTH_MONTH and BIRTH_YEAR. There is a helpful rule listed in table below for how to derive BIRTH_DATETIME if it is not available in the source. **New to CDM v6.0** The person's death date is now stored in this table instead of the separate DEATH table. In the case that multiple dates of death are given in the source data the ETL should make a choice as to which death date to put in the PERSON table. Any additional dates can be stored in the OBSERVATION table using the concept [4265167](https://athena.ohdsi.org/search-terms/terms/4265167) which stands for 'Date of death' . Similarly, the cause of death is stored in the CONDITION_OCCURRENCE table using the CONDITION_STATUS_CONCEPT_ID [32891](https://athena.ohdsi.org/search-terms/terms/32891) for 'Cause of death'.
3 observation_period CDM Yes NA Yes 0 NA This table contains records which define spans of time during which two conditions are expected to hold: (i) Clinical Events that happened to the Person are recorded in the Event tables, and (ii) absence of records indicate such Events did not occur during this span of time. For each Person, one or more OBSERVATION_PERIOD records may be present, but they will not overlap or be back to back to each other. Events may exist outside all of the time spans of the OBSERVATION_PERIOD records for a patient, however, absence of an Event outside these time spans cannot be construed as evidence of absence of an Event. Incidence or prevalence rates should only be calculated for the time of active OBSERVATION_PERIOD records. When constructing cohorts, outside Events can be used for inclusion criteria definition, but without any guarantee for the performance of these criteria. Also, OBSERVATION_PERIOD records can be as short as a single day, greatly disturbing the denominator of any rate calculation as part of cohort characterizations. To avoid that, apply minimal observation time as a requirement for any cohort definition. Each Person needs to have at least one OBSERVATION_PERIOD record, which should represent time intervals with a high capture rate of Clinical Events. Some source data have very similar concepts, such as enrollment periods in insurance claims data. In other source data such as most EHR systems these time spans need to be inferred under a set of assumptions. It is the discretion of the ETL developer to define these assumptions. In many ETL solutions the start date of the first occurrence or the first high quality occurrence of a Clinical Event (Condition, Drug, Procedure, Device, Measurement, Visit) is defined as the start of the OBSERVATION_PERIOD record, and the end date of the last occurrence of last high quality occurrence of a Clinical Event, or the end of the database period becomes the end of the OBSERVATOIN_PERIOD for each Person. If a Person only has a single Clinical Event the OBSERVATION_PERIOD record can be as short as one day. Depending on these definitions it is possible that Clinical Events fall outside the time spans defined by OBSERVATION_PERIOD records. Family history or history of Clinical Events generally are not used to generate OBSERVATION_PERIOD records around the time they are referring to. Any two overlapping or adjacent OBSERVATION_PERIOD records have to be merged into one. Each Person needs to have at least one OBSERVATION_PERIOD record, which should represent time intervals with a high capture rate of Clinical Events. Some source data have very similar concepts, such as enrollment periods in insurance claims data. In other source data such as most EHR systems these time spans need to be inferred under a set of assumptions. It is the discretion of the ETL developer to define these assumptions. In many ETL solutions the start date of the first occurrence or the first high quality occurrence of a Clinical Event (Condition, Drug, Procedure, Device, Measurement, Visit) is defined as the start of the OBSERVATION_PERIOD record, and the end date of the last occurrence of last high quality occurrence of a Clinical Event, or the end of the database period becomes the end of the OBSERVATION_PERIOD for each Person. If a Person only has a single Clinical Event the OBSERVATION_PERIOD record can be as short as one day. Depending on these definitions it is possible that Clinical Events fall outside the time spans defined by OBSERVATION_PERIOD records. Family history or history of Clinical Events generally are not used to generate OBSERVATION_PERIOD records around the time they are referring to. Any two overlapping or adjacent OBSERVATION_PERIOD records have to be merged into one.
4 visit_occurrence CDM No VISIT_ Yes 0 NA This table contains Events where Persons engage with the healthcare system for a duration of time. They are often also called "Encounters". Visits are defined by a configuration of circumstances under which they occur, such as (i) whether the patient comes to a healthcare institution, the other way around, or the interaction is remote, (ii) whether and what kind of trained medical staff is delivering the service during the Visit, and (iii) whether the Visit is transient or for a longer period involving a stay in bed. The configuration defining the Visit are described by Concepts in the Visit Domain, which form a hierarchical structure, but rolling up to generally familiar Visits adopted in most healthcare systems worldwide: - [Inpatient Visit](https://athena.ohdsi.org/search-terms/terms/9201): Person visiting hospital, at a Care Site, in bed, for duration of more than one day, with physicians and other Providers permanently available to deliver service around the clock - [Emergency Room Visit](https://athena.ohdsi.org/search-terms/terms/9203): Person visiting dedicated healthcare institution for treating emergencies, at a Care Site, within one day, with physicians and Providers permanently available to deliver service around the clock - [Emergency Room and Inpatient Visit](https://athena.ohdsi.org/search-terms/terms/262): Person visiting ER followed by a subsequent Inpatient Visit, where Emergency department is part of hospital, and transition from the ER to other hospital departments is undefined - [Non-hospital institution Visit](https://athena.ohdsi.org/search-terms/terms/42898160): Person visiting dedicated institution for reasons of poor health, at a Care Site, long-term or permanently, with no physician but possibly other Providers permanently available to deliver service around the clock - [Outpatient Visit](https://athena.ohdsi.org/search-terms/terms/9202): Person visiting dedicated ambulatory healthcare institution, at a Care Site, within one day, without bed, with physicians or medical Providers delivering service during Visit - [Home Visit](https://athena.ohdsi.org/search-terms/terms/581476): Provider visiting Person, without a Care Site, within one day, delivering service - [Telehealth Visit](https://athena.ohdsi.org/search-terms/terms/5083): Patient engages with Provider through communication media - [Pharmacy Visit](https://athena.ohdsi.org/search-terms/terms/581458): Person visiting pharmacy for dispensing of Drug, at a Care Site, within one day - [Laboratory Visit](https://athena.ohdsi.org/search-terms/terms/32036): Patient visiting dedicated institution, at a Care Site, within one day, for the purpose of a Measurement. - [Ambulance Visit](https://athena.ohdsi.org/search-terms/terms/581478): Person using transportation service for the purpose of initiating one of the other Visits, without a Care Site, within one day, potentially with Providers accompanying the Visit and delivering service - [Case Management Visit](https://athena.ohdsi.org/search-terms/terms/38004193): Person interacting with healthcare system, without a Care Site, within a day, with no Providers involved, for administrative purposes The Visit duration, or 'length of stay', is defined as VISIT_END_DATE - VISIT_START_DATE. For all Visits this is <1 day, except Inpatient Visits and Non-hospital institution Visits. The CDM also contains the VISIT_DETAIL table where additional information about the Visit is stored, for example, transfers between units during an inpatient Visit. Visits can be derived easily if the source data contain coding systems for Place of Service or Procedures, like CPT codes for well visits. In those cases, the codes can be looked up and mapped to a Standard Visit Concept. Otherwise, Visit Concepts have to be identified in the ETL process. This table will contain concepts in the Visit domain. These concepts are arranged in a hierarchical structure to facilitate cohort definitions by rolling up to generally familiar Visits adopted in most healthcare systems worldwide. Visits can be adjacent to each other, i.e. the end date of one can be identical with the start date of the other. As a consequence, more than one-day Visits or their descendants can be recorded for the same day. Multi-day visits must not overlap, i.e. share days other than start and end days. It is often the case that some logic should be written for how to define visits and how to assign Visit_Concept_Id. For example, in US claims outpatient visits that appear to occur within the time period of an inpatient visit can be rolled into one with the same Visit_Occurrence_Id. In EHR data inpatient visits that are within one day of each other may be strung together to create one visit. It will all depend on the source data and how encounter records should be translated to visit occurrences. Providers can be associated with a Visit through the PROVIDER_ID field, or indirectly through PROCEDURE_OCCURRENCE records linked both to the VISIT and PROVIDER tables.
5 visit_detail CDM No VISIT_DETAIL_ Yes 0 NA The VISIT_DETAIL table is an optional table used to represents details of each record in the parent VISIT_OCCURRENCE table. A good example of this would be the movement between units in a hospital during an inpatient stay or claim lines associated with a one insurance claim. For every record in the VISIT_OCCURRENCE table there may be 0 or more records in the VISIT_DETAIL table with a 1:n relationship where n may be 0. The VISIT_DETAIL table is structurally very similar to VISIT_OCCURRENCE table and belongs to the visit domain. The configuration defining the Visit Detail is described by Concepts in the Visit Domain, which form a hierarchical structure. The Visit Detail record will have an associated to the Visit Occurrence record in two ways: <br> 1. The Visit Detail record will have the VISIT_OCCURRENCE_ID it is associated to 2. The VISIT_DETAIL_CONCEPT_ID will be a descendant of the VISIT_CONCEPT_ID for the Visit. It is not mandatory that the VISIT_DETAIL table be filled in, but if you find that the logic to create VISIT_OCCURRENCE records includes the roll-up of multiple smaller records to create one picture of a Visit then it is a good idea to use VISIT_DETAIL. In EHR data, for example, a Person may be in the hospital but instead of one over-arching Visit their encounters are recorded as times they interacted with a health care provider. A Person in the hospital interacts with multiple providers multiple times a day so the encounters must be strung together using some heuristic (defined by the ETL) to identify the entire Visit. In this case the encounters would be considered Visit Details and the entire Visit would be the Visit Occurrence. In this example it is also possible to use the Vocabulary to distinguish Visit Details from a Visit Occurrence by setting the VISIT_CONCEPT_ID to [9201](https://athena.ohdsi.org/search-terms/terms/9201) and the VISIT_DETAIL_CONCEPT_IDs either to 9201 or its children to indicate where the patient was in the hospital at the time of care.
6 condition_occurrence CDM No CONDITION_ Yes 0 NA This table contains records of Events of a Person suggesting the presence of a disease or medical condition stated as a diagnosis, a sign, or a symptom, which is either observed by a Provider or reported by the patient. Conditions are defined by Concepts from the Condition domain, which form a complex hierarchy. As a result, the same Person with the same disease may have multiple Condition records, which belong to the same hierarchical family. Most Condition records are mapped from diagnostic codes, but recorded signs, symptoms and summary descriptions also contribute to this table. Rule out diagnoses should not be recorded in this table, but in reality their negating nature is not always captured in the source data, and other precautions must be taken when when identifying Persons who should suffer from the recorded Condition. Record all conditions as they exist in the source data. Any decisions about diagnosis/phenotype definitions would be done through cohort specifications. These cohorts can be housed in the [COHORT](https://ohdsi.github.io/CommonDataModel/cdm531.html#payer_plan_period) table. Conditions span a time interval from start to end, but are typically recorded as single snapshot records with no end date. The reason is twofold: (i) At the time of the recording the duration is not known and later not recorded, and (ii) the Persons typically cease interacting with the healthcare system when they feel better, which leads to incomplete capture of resolved Conditions. The [CONDITION_ERA](https://ohdsi.github.io/CommonDataModel/cdm531.html#condition_era) table addresses this issue. Family history and past diagnoses ('history of') are not recorded in this table. Instead, they are listed in the [OBSERVATION](https://ohdsi.github.io/CommonDataModel/cdm531.html#observation) table. Codes written in the process of establishing the diagnosis, such as 'question of' of and 'rule out', should not represented here. Instead, they should be recorded in the [OBSERVATION](https://ohdsi.github.io/CommonDataModel/cdm531.html#observation) table, if they are used for analyses. However, this information is not always available. Conditions are defined by Concepts from the Condition domain, which form a complex hierarchy. As a result, the same Person with the same disease may have multiple Condition records, which belong to the same hierarchical family. Most Condition records are mapped from diagnostic codes, but recorded signs, symptoms and summary descriptions also contribute to this table. Rule out diagnoses should not be recorded in this table, but in reality their negating nature is not always captured in the source data, and other precautions must be taken when when identifying Persons who should suffer from the recorded Condition. Record all conditions as they exist in the source data. Any decisions about diagnosis/phenotype definitions would be done through cohort specifications. These cohorts can be housed in the [COHORT](https://ohdsi.github.io/CommonDataModel/cdm60.html#payer_plan_period) table. Conditions span a time interval from start to end, but are typically recorded as single snapshot records with no end date. The reason is twofold: (i) At the time of the recording the duration is not known and later not recorded, and (ii) the Persons typically cease interacting with the healthcare system when they feel better, which leads to incomplete capture of resolved Conditions. The [CONDITION_ERA](https://ohdsi.github.io/CommonDataModel/cdm60.html#condition_era) table addresses this issue. Family history and past diagnoses ('history of') are not recorded in this table. Instead, they are listed in the [OBSERVATION](https://ohdsi.github.io/CommonDataModel/cdm60.html#observation) table. Codes written in the process of establishing the diagnosis, such as 'question of' of and 'rule out', should not represented here. Instead, they should be recorded in the [OBSERVATION](https://ohdsi.github.io/CommonDataModel/cdm60.html#observation) table, if they are used for analyses. However, this information is not always available. Source codes and source text fields mapped to Standard Concepts of the Condition Domain have to be recorded here.
17 location CDM No NA No NA NA The LOCATION table represents a generic way to capture physical location or address information of Persons and Care Sites. **New to CDM v6.0** The LOCATION table now includes latitude and longitude. NA Each address or Location is unique and is present only once in the table. Locations do not contain names, such as the name of a hospital. In order to construct a full address that can be used in the postal service, the address information from the Location needs to be combined with information from the Care Site. For standardized geospatial visualization and analysis, addresses need to be, at the minimum be geocoded into latitude and longitude.
18 location_history CDM No NA No NA NA The LOCATION HISTORY table stores relationships between Persons or Care Sites and geographic locations over time. **This table is new to CDM v6.0** NA NA
19 care_site CDM No NA No NA NA The CARE_SITE table contains a list of uniquely identified institutional (physical or organizational) units where healthcare delivery is practiced (offices, wards, hospitals, clinics, etc.). NA Care site is a unique combination of location_id and place_of_service_source_value. Care site does not take into account the provider (human) information such a specialty. Many source data do not make a distinction between individual and institutional providers. The CARE_SITE table contains the institutional providers. If the source, instead of uniquely identifying individual Care Sites, only provides limited information such as Place of Service, generic or "pooled" Care Site records are listed in the CARE_SITE table. There can be hierarchical and business relationships between Care Sites. For example, wards can belong to clinics or departments, which can in turn belong to hospitals, which in turn can belong to hospital systems, which in turn can belong to HMOs.The relationships between Care Sites are defined in the FACT_RELATIONSHIP table.
20 provider CDM No NA No NA NA The PROVIDER table contains a list of uniquely identified healthcare providers. These are individuals providing hands-on healthcare to patients, such as physicians, nurses, midwives, physical therapists etc. Many sources do not make a distinction between individual and institutional providers. The PROVIDER table contains the individual providers. If the source, instead of uniquely identifying individual providers, only provides limited information such as specialty, generic or 'pooled' Provider records are listed in the PROVIDER table. NA
21 payer_plan_period CDM No NA Yes 0 NA The PAYER_PLAN_PERIOD table captures details of the period of time that a Person is continuously enrolled under a specific health Plan benefit structure from a given Payer. Each Person receiving healthcare is typically covered by a health benefit plan, which pays for (fully or partially), or directly provides, the care. These benefit plans are provided by payers, such as health insurances or state or government agencies. In each plan the details of the health benefits are defined for the Person or her family, and the health benefit Plan might change over time typically with increasing utilization (reaching certain cost thresholds such as deductibles), plan availability and purchasing choices of the Person. The unique combinations of Payer organizations, health benefit Plans and time periods in which they are valid for a Person are recorded in this table. A Person can have multiple, overlapping, Payer_Plan_Periods in this table. For example, medical and drug coverage in the US can be represented by two Payer_Plan_Periods. The details of the benefit structure of the Plan is rarely known, the idea is just to identify that the Plans are different. NA
22 cost CDM No NA No NA NA The COST table captures records containing the cost of any medical event recorded in one of the OMOP clinical event tables such as DRUG_EXPOSURE, PROCEDURE_OCCURRENCE, VISIT_OCCURRENCE, VISIT_DETAIL, DEVICE_OCCURRENCE, OBSERVATION or MEASUREMENT. Each record in the cost table account for the amount of money transacted for the clinical event. So, the COST table may be used to represent both receivables (charges) and payments (paid), each transaction type represented by its COST_CONCEPT_ID. The COST_TYPE_CONCEPT_ID field will use concepts in the Standardized Vocabularies to designate the source (provenance) of the cost data. A reference to the health plan information in the PAYER_PLAN_PERIOD table is stored in the record for information used for the adjudication system to determine the persons benefit for the clinical event. When dealing with summary costs, the cost of the goods or services the provider provides is often not known directly, but derived from the hospital charges multiplied by an average cost-to-charge ratio. One cost record is generated for each response by a payer. In a claims databases, the payment and payment terms reported by the payer for the goods or services billed will generate one cost record. If the source data has payment information for more than one payer (i.e. primary insurance and secondary insurance payment for one entity), then a cost record is created for each reporting payer. Therefore, it is possible for one procedure to have multiple cost records for each payer, but typically it contains one or no record per entity. Payer reimbursement cost records will be identified by using the PAYER_PLAN_ID field. Drug costs are composed of ingredient cost (the amount charged by the wholesale distributor or manufacturer), the dispensing fee (the amount charged by the pharmacy and the sales tax).
23 drug_era CDM No NA Yes 0 NA A Drug Era is defined as a span of time when the Person is assumed to be exposed to a particular active ingredient. A Drug Era is not the same as a Drug Exposure: Exposures are individual records corresponding to the source when Drug was delivered to the Person, while successive periods of Drug Exposures are combined under certain rules to produce continuous Drug Eras. NA The SQL script for generating DRUG_ERA records can be found [here](https://ohdsi.github.io/CommonDataModel/sqlScripts.html#drug_eras).
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@ -90,6 +90,9 @@ Notation:
## PAYER_PLAN_PERIOD
- No change
## PROVIDER
- No change
## COST
- No change

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@ -42,7 +42,7 @@ corresponding Concept reference data.
- The concept_id of a Concept is persistent, i.e. stays the same for the same Concept between releases of
the Standardized Vocabularies.
- A descriptive name for each Concept is stored as the Concept Name as part of the CONCEPT table. Additional
names and descriptions for the Concept are stored as Synonyms in the [CONCEPT_SYNONYM](https://ohdsi.github.io/CommonDataModel/cdm531.html#concept_synonym)
names and descriptions for the Concept are stored as Synonyms in the [CONCEPT_SYNONYM](https://ohdsi.github.io/CommonDataModel/cdm54.html#concept_synonym)
table.
- Each Concept is assigned to a Domain. For Standard Concepts, there is always a single Domain. Source
Concepts can be composite or coordinated entities, and therefore can belong to more than one Domain.
@ -61,7 +61,7 @@ field and can be used to reference the source vocabulary.
in all *_concept_id fields, whereas Classification Concepts (C) should not appear in the CDM
data, but participate in the construction of the CONCEPT_ANCESTOR table and can be used to
identify Descendants that may appear in the data. See CONCEPT_ANCESTOR table. Non-standard
Concepts can only appear in *_source_concept_id fields and are not used in [CONCEPT_ANCESTOR](https://ohdsi.github.io/CommonDataModel/cdm531.html#concept_ancestor)
Concepts can only appear in *_source_concept_id fields and are not used in [CONCEPT_ANCESTOR](https://ohdsi.github.io/CommonDataModel/cdm54.html#concept_ancestor)
table. Please refer to the Standardized Vocabularies specifications for details of the Standard Concept
designation.
- The lifespan of a Concept is recorded through its valid_start_date, valid_end_date and the invalid_
@ -144,10 +144,10 @@ and the relationship_id replaced by the reverse_relationship_id from the RELATIO
not necessary to query for the existence of a relationship both in the concept_id_1 and concept_id_2
fields.
- Concept Relationships define direct relationships between Concepts. Indirect relationships through 3rd
Concepts are not captured in this table. However, the [CONCEPT_ANCESTOR](https://ohdsi.github.io/CommonDataModel/cdm531.html#concept_ancestor) table does this for
Concepts are not captured in this table. However, the [CONCEPT_ANCESTOR](https://ohdsi.github.io/CommonDataModel/cdm54.html#concept_ancestor) table does this for
hierarchical relationships over several “generations” of direct relationships.
- In previous versions of the CDM, the relationship_id used to be a numerical identifier. See the
[RELATIONSHIP](https://ohdsi.github.io/CommonDataModel/cdm531.html#relationship) table.
[RELATIONSHIP](https://ohdsi.github.io/CommonDataModel/cdm54.html#relationship) table.
### Relationship Table
- There is one record for each Relationship.
@ -163,7 +163,7 @@ Relationship is provided in the reverse_relationship_id field.
concept_id field. This is for purposes of creating a closed Information Model, where all entities in
the OMOP CDM are covered by unique Concepts.
- Hierarchical Relationships are used to build a hierarchical tree out of the Concepts, which is recorded in
the [CONCEPT_ANCESTOR](https://ohdsi.github.io/CommonDataModel/cdm531.html#concept_ancestor) table. For example, “has_ingredient” is a Relationship between Concept
the [CONCEPT_ANCESTOR](https://ohdsi.github.io/CommonDataModel/cdm54.html#concept_ancestor) table. For example, “has_ingredient” is a Relationship between Concept
of the Concept Class Clinical Drug and those of Ingredient, and all Ingredients can be classified as
the “parental” hierarchical Concepts for the drug products they are part of. All Is a Relationships are
hierarchical.
@ -172,19 +172,19 @@ from different Vocabulary sources.
### Concept Synonyms
- The concept_synonym_name field contains a valid Synonym of a concept, including the description in
the concept_name itself. I.e. each Concept has at least one Synonym in the [CONCEPT_SYNONYM](https://ohdsi.github.io/CommonDataModel/cdm531.html#concept_synonym)
the concept_name itself. I.e. each Concept has at least one Synonym in the [CONCEPT_SYNONYM](https://ohdsi.github.io/CommonDataModel/cdm54.html#concept_synonym)
table. As an example, for a SNOMED-CT Concept, if the fully specified name is stored as the
concept_name of the [CONCEPT](https://ohdsi.github.io/CommonDataModel/cdm531.html#concept) table, then the Preferred Term and Synonyms associated with the Concept are stored in the [CONCEPT_SYNONYM](https://ohdsi.github.io/CommonDataModel/cdm531.html#concept_synonym) table.
- Only Synonyms that are active and current are stored in the [CONCEPT_SYNONYM](https://ohdsi.github.io/CommonDataModel/cdm531.html#concept_synonym) table. Tracking
concept_name of the [CONCEPT](https://ohdsi.github.io/CommonDataModel/cdm54.html#concept) table, then the Preferred Term and Synonyms associated with the Concept are stored in the [CONCEPT_SYNONYM](https://ohdsi.github.io/CommonDataModel/cdm54.html#concept_synonym) table.
- Only Synonyms that are active and current are stored in the [CONCEPT_SYNONYM](https://ohdsi.github.io/CommonDataModel/cdm54.html#concept_synonym) table. Tracking
synonym/description history and mapping of obsolete synonyms to current Concepts/Synonyms is out
of scope for the Standard Vocabularies.
- Currently, only English Synonyms are included.
### Concept Ancestor
- Each concept is also recorded as an ancestor of itself.
- Only valid and Standard Concepts participate in the [CONCEPT_ANCESTOR](https://ohdsi.github.io/CommonDataModel/cdm531.html#concept_ancestor) table. It is not possible
- Only valid and Standard Concepts participate in the [CONCEPT_ANCESTOR](https://ohdsi.github.io/CommonDataModel/cdm54.html#concept_ancestor) table. It is not possible
to find ancestors or descendants of deprecated or Source Concepts.
- Usually, only Concepts of the same Domain are connected through records of the [CONCEPT_ANCESTOR](https://ohdsi.github.io/CommonDataModel/cdm531.html#concept_ancestor) table, but there might be exceptions.
- Usually, only Concepts of the same Domain are connected through records of the [CONCEPT_ANCESTOR](https://ohdsi.github.io/CommonDataModel/cdm54.html#concept_ancestor) table, but there might be exceptions.
### Source to Concept Map
- This table is no longer used to distribute mapping information between source codes and Standard