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Merge pull request #650 from OHDSI/olympians_week2 

Olympians week2
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@ -524,7 +524,10 @@ 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.</p>
BIRTH_DAY, BIRTH_MONTH and BIRTH_YEAR.<br><br>For detailed conventions
for how to populate this table, please refer to the <a
href="https://ohdsi.github.io/Themis/person.html">THEMIS
repository</a>.</p>
<table class="table table-condensed table-hover" style="font-size: 13px; margin-left: auto; margin-right: auto;">
<thead>
<tr>
@ -604,7 +607,9 @@ gender identity it should be stored in the <a
href="https://ohdsi.github.io/CommonDataModel/cdm531.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>
gender concepts</a>. Please refer to the <a
href="https://ohdsi.github.io/Themis/tag_gender_concept_id.html">THEMIS
repository</a> for detailed conventions on how to populate this field.
</td>
<td style="text-align:left;">
integer
@ -633,11 +638,12 @@ year_of_birth
Compute age using year_of_birth.
</td>
<td style="text-align:left;">
For data sources with date of birth, the year should be extracted. For
data sources where the year of birth is not available, the approximate
year of birth could be derived based on age group categorization, if
available. If no year of birth is available all the person’s data should
be dropped from the CDM instance.
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 <a
href="https://ohdsi.github.io/Themis/tag_year_of_birth.html">THEMIS
repository</a>.
</td>
<td style="text-align:left;">
integer
@ -719,13 +725,9 @@ birth_datetime
<td style="text-align:left;">
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. If birth_datetime is not provided in the source, use the
following logic to infer the date: If day_of_birth is null and
month_of_birth is not null then use the first of the month in that year.
If month_of_birth is null or if day_of_birth AND month_of_birth are both
null and the person has records during their year of birth then use the
date of the earliest record, otherwise use the 15th of June of that
year. If time of birth is not given use midnight (00:00:0000).
this field. For more information on how to populate this field, please
refer to the <a href="https://ohdsi.github.io/Themis/person.html">THEMIS
repository</a>.
</td>
<td style="text-align:left;">
datetime
@ -828,11 +830,10 @@ should capture the last known location of the person.
Put the location_id from the <a
href="https://ohdsi.github.io/CommonDataModel/cdm531.html#location">LOCATION</a>
table here that represents the most granular location information for
the person. This could represent anything from postal code or parts
thereof, state, or county for example. Since many databases contain
deidentified data, it is common that the precision of the location is
reduced to prevent re-identification. This field should capture the last
known location.
the person. For additional information on how to populate this field,
please refer to the <a
href="https://ohdsi.github.io/Themis/populate_person_location_id.html">THEMIS
repository</a>.
</td>
<td style="text-align:left;">
integer
@ -953,7 +954,8 @@ source data. It is not intended for use in standard analytics but for
reference only.
</td>
<td style="text-align:left;">
Put the biological sex of the person as it appears in the source data.
Put the assigned sex at birth of the person as it appears in the source
data.
</td>
<td style="text-align:left;">
varchar(50)
@ -980,8 +982,8 @@ 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 biological sex in a non-standard vocabulary,
store the concept_id here.
If the source data codes asigned sex at birth in a non-standard
vocabulary, store the concept_id here.
</td>
<td style="text-align:left;">
integer
@ -3310,7 +3312,10 @@ 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.</p>
on how to handle refills for prescriptions written.<br><br>For detailed
conventions on how to populate this table, please refer to the <a
href="https://ohdsi.github.io/Themis/drug_exposure.html">THEMIS
repository</a>.</p>
<table class="table table-condensed table-hover" style="font-size: 13px; margin-left: auto; margin-right: auto;">
<thead>
<tr>
@ -3432,14 +3437,16 @@ 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. <a
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
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
@ -3542,7 +3549,10 @@ 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>
by dose form</a><br><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>
<td style="text-align:left;">
date
@ -5248,12 +5258,13 @@ measurement_concept_id
</td>
<td style="text-align:left;">
The MEASUREMENT_CONCEPT_ID field is recommended for primary use in
analyses, and must be used for network studies.
analyses, and must be used for network studies. This is the standard
concept mapped from the source value which represents a measurement.
</td>
<td style="text-align:left;">
The CONCEPT_ID that the MEASUREMENT_SOURCE_CONCEPT_ID maps to. Only
records whose SOURCE_CONCEPT_IDs map to Standard Concepts with a domain
of “Measurement” should go in this table.
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>
</td>
<td style="text-align:left;">
integer
@ -5517,19 +5528,17 @@ CONCEPT
unit_concept_id
</td>
<td style="text-align:left;">
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.
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.
</td>
<td style="text-align:left;">
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. 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.
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.
</td>
<td style="text-align:left;">
integer
@ -5782,12 +5791,13 @@ CONCEPT
unit_source_value
</td>
<td style="text-align:left;">
This field houses the verbatim value from the source data representing
the unit of the Measurement that occurred.
This field contains the exact value from the source data that represents
the unit of measurement used.
</td>
<td style="text-align:left;">
This code is mapped to a Standard Condition Concept in the Standardized
Vocabularies and the original code is stored here for reference.
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.
</td>
<td style="text-align:left;">
varchar(50)
@ -5858,10 +5868,18 @@ 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 though they still should be Standard Concepts.</p>
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.</p>
<p><strong>ETL Conventions</strong></p>
<p>Records whose Source Values map to any domain besides Condition,
Procedure, Drug, Measurement or Device should be stored in the
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
@ -5999,9 +6017,9 @@ CONCEPT
observation_date
</td>
<td style="text-align:left;">
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.
The date of when the Observation was obtained. 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.
</td>
<td style="text-align:left;">
For some observations the ETL may need to make a choice as to which date
@ -6498,7 +6516,9 @@ explicit record in EHR data.</p>
<p><strong>User Guide</strong></p>
<p>NA</p>
<p><strong>ETL Conventions</strong></p>
<p>NA</p>
<p>For specific conventions on how to populate this table, please refer
to the <a href="https://ohdsi.github.io/Themis/death.html">THEMIS
repository</a>.</p>
<table class="table table-condensed table-hover" style="font-size: 13px; margin-left: auto; margin-right: auto;">
<thead>
<tr>
@ -6568,7 +6588,10 @@ The date the person was deceased.
<td style="text-align:left;">
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.
default day. For additional conventions related to this field, please
refer to the <a
href="https://ohdsi.github.io/Themis/tag_death_date.html">THEMIS
repository</a>.
</td>
<td style="text-align:left;">
date
@ -6711,7 +6734,8 @@ cause_source_concept_id
</td>
<td style="text-align:left;">
If the cause of death was coded using a Vocabulary present in the OMOP
Vocabularies put the CONCEPT_ID representing the cause of death here.
Vocabularies (not necessarily a standard concept) put the CONCEPT_ID
representing the cause of death here.
</td>
<td style="text-align:left;">
integer
@ -8542,11 +8566,12 @@ delivery is practiced (offices, wards, hospitals, clinics, etc.).</p>
<p><strong>User Guide</strong></p>
<p>NA</p>
<p><strong>ETL Conventions</strong></p>
<p>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,
<p>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
@ -8554,7 +8579,10 @@ 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.</p>
the FACT_RELATIONSHIP table.<br><br>For additional detailed conventions
on how to populate this table, please refer to <a
href="https://ohdsi.github.io/Themis/care_site.html">THEMIS
repository</a>.</p>
<table class="table table-condensed table-hover" style="font-size: 13px; margin-left: auto; margin-right: auto;">
<thead>
<tr>
@ -8657,7 +8685,10 @@ 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. <a
href="https://athena.ohdsi.org/search-terms/terms?domain=Visit&amp;standardConcept=Standard&amp;page=2&amp;pageSize=15&amp;query=">Accepted
Concepts</a>.
Concepts</a>. For information about how to populate this field please
see the <a
href="https://ohdsi.github.io/Themis/tag_place_of_service.html">THEMIS
Conventions</a>.
</td>
<td style="text-align:left;">
integer

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docs/cdm54.html
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@ -632,7 +632,10 @@ 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.</p>
BIRTH_DAY, BIRTH_MONTH and BIRTH_YEAR.<br><br>For detailed conventions
for how to populate this table, please refer to the <a
href="https://ohdsi.github.io/Themis/person.html">THEMIS
repository</a>.</p>
<table class="table table-condensed table-hover" style="font-size: 13px; margin-left: auto; margin-right: auto;">
<thead>
<tr>
@ -712,7 +715,9 @@ gender identity it should be stored in the <a
href="https://ohdsi.github.io/CommonDataModel/cdm531.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>
gender concepts</a>. Please refer to the <a
href="https://ohdsi.github.io/Themis/tag_gender_concept_id.html">THEMIS
repository</a> for detailed conventions on how to populate this field.
</td>
<td style="text-align:left;">
integer
@ -741,11 +746,12 @@ year_of_birth
Compute age using year_of_birth.
</td>
<td style="text-align:left;">
For data sources with date of birth, the year should be extracted. For
data sources where the year of birth is not available, the approximate
year of birth could be derived based on age group categorization, if
available. If no year of birth is available all the person’s data should
be dropped from the CDM instance.
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 <a
href="https://ohdsi.github.io/Themis/tag_year_of_birth.html">THEMIS
repository</a>.
</td>
<td style="text-align:left;">
integer
@ -825,15 +831,11 @@ birth_datetime
<td style="text-align:left;">
</td>
<td style="text-align:left;">
This field is not required but highly encouraged for data sources that
provide the precise datetime of birth. If birth_datetime is not provided
in the source, use the following logic to infer the date: If
day_of_birth is null and month_of_birth is not null then use the first
of the month in that year. If month_of_birth is null or if day_of_birth
AND month_of_birth are both null and the person has records during their
year of birth then use the date of the earliest record, otherwise use
the 15th of June of that year. If time of birth is not given use
midnight (00:00:0000).
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 <a href="https://ohdsi.github.io/Themis/person.html">THEMIS
repository</a>.
</td>
<td style="text-align:left;">
datetime
@ -934,13 +936,12 @@ 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/cdm54.html#LOCATION">LOCATION</a>
href="https://ohdsi.github.io/CommonDataModel/cdm531.html#location">LOCATION</a>
table here that represents the most granular location information for
the person. This could represent anything from postal code or parts
thereof, state, or county for example. Since many databases contain
deidentified data, it is common that the precision of the location is
reduced to prevent re-identification. This field should capture the last
known location.
the person. For additional information on how to populate this field,
please refer to the <a
href="https://ohdsi.github.io/Themis/populate_person_location_id.html">THEMIS
repository</a>.
</td>
<td style="text-align:left;">
integer
@ -1061,7 +1062,8 @@ source data. It is not intended for use in standard analytics but for
reference only.
</td>
<td style="text-align:left;">
Put the biological sex of the person as it appears in the source data.
Put the assigned sex at birth of the person as it appears in the source
data.
</td>
<td style="text-align:left;">
varchar(50)
@ -1088,8 +1090,8 @@ 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 biological sex in a non-standard vocabulary,
store the concept_id here.
If the source data codes asigned sex at birth in a non-standard
vocabulary, store the concept_id here.
</td>
<td style="text-align:left;">
integer
@ -3446,7 +3448,10 @@ 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.</p>
on how to handle refills for prescriptions written.<br><br>For detailed
conventions on how to populate this table, please refer to the <a
href="https://ohdsi.github.io/Themis/drug_exposure.html">THEMIS
repository</a>.</p>
<table class="table table-condensed table-hover" style="font-size: 13px; margin-left: auto; margin-right: auto;">
<thead>
<tr>
@ -3568,14 +3573,16 @@ 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. <a
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
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
@ -3678,7 +3685,10 @@ 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>
by dose form</a><br><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>
<td style="text-align:left;">
date
@ -5579,12 +5589,13 @@ measurement_concept_id
</td>
<td style="text-align:left;">
The MEASUREMENT_CONCEPT_ID field is recommended for primary use in
analyses, and must be used for network studies.
analyses, and must be used for network studies. This is the standard
concept mapped from the source value which represents a measurement.
</td>
<td style="text-align:left;">
The CONCEPT_ID that the MEASUREMENT_SOURCE_CONCEPT_ID maps to. Only
records whose SOURCE_CONCEPT_IDs map to Standard Concepts with a domain
of “Measurement” should go in this table.
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>
</td>
<td style="text-align:left;">
integer
@ -5851,19 +5862,17 @@ CONCEPT
unit_concept_id
</td>
<td style="text-align:left;">
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.
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.
</td>
<td style="text-align:left;">
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. 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.
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.
</td>
<td style="text-align:left;">
integer
@ -6116,12 +6125,13 @@ CONCEPT
unit_source_value
</td>
<td style="text-align:left;">
This field houses the verbatim value from the source data representing
the unit of the Measurement that occurred.
This field contains the exact value from the source data that represents
the unit of measurement used.
</td>
<td style="text-align:left;">
This code is mapped to a Standard Condition Concept in the Standardized
Vocabularies and the original code is stored here for reference.
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.
</td>
<td style="text-align:left;">
varchar(50)
@ -6288,10 +6298,18 @@ 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 though they still should be Standard Concepts.</p>
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.</p>
<p><strong>ETL Conventions</strong></p>
<p>Records whose Source Values map to any domain besides Condition,
Procedure, Drug, Measurement or Device should be stored in the
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
@ -6429,9 +6447,9 @@ CONCEPT
observation_date
</td>
<td style="text-align:left;">
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.
The date of when the Observation was obtained. 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.
</td>
<td style="text-align:left;">
For some observations the ETL may need to make a choice as to which date
@ -7027,7 +7045,9 @@ explicit record in EHR data.</p>
<p><strong>User Guide</strong></p>
<p>NA</p>
<p><strong>ETL Conventions</strong></p>
<p>NA</p>
<p>For specific conventions on how to populate this table, please refer
to the <a href="https://ohdsi.github.io/Themis/death.html">THEMIS
repository</a>.</p>
<table class="table table-condensed table-hover" style="font-size: 13px; margin-left: auto; margin-right: auto;">
<thead>
<tr>
@ -7097,7 +7117,10 @@ The date the person was deceased.
<td style="text-align:left;">
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.
default day. For additional conventions related to this field, please
refer to the <a
href="https://ohdsi.github.io/Themis/tag_death_date.html">THEMIS
repository</a>.
</td>
<td style="text-align:left;">
date
@ -7243,7 +7266,8 @@ cause_source_concept_id
</td>
<td style="text-align:left;">
If the cause of death was coded using a Vocabulary present in the OMOP
Vocabularies put the CONCEPT_ID representing the cause of death here.
Vocabularies (not necessarily a standard concept) put the CONCEPT_ID
representing the cause of death here.
</td>
<td style="text-align:left;">
integer
@ -9250,11 +9274,12 @@ delivery is practiced (offices, wards, hospitals, clinics, etc.).</p>
<p><strong>User Guide</strong></p>
<p>NA</p>
<p><strong>ETL Conventions</strong></p>
<p>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,
<p>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
@ -9262,7 +9287,10 @@ 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.</p>
the FACT_RELATIONSHIP table.<br><br>For additional detailed conventions
on how to populate this table, please refer to <a
href="https://ohdsi.github.io/Themis/care_site.html">THEMIS
repository</a>.</p>
<table class="table table-condensed table-hover" style="font-size: 13px; margin-left: auto; margin-right: auto;">
<thead>
<tr>
@ -9366,7 +9394,10 @@ 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. <a
href="https://athena.ohdsi.org/search-terms/terms?domain=Visit&amp;standardConcept=Standard&amp;page=2&amp;pageSize=15&amp;query=">Accepted
Concepts</a>.
Concepts</a>. For information about how to populate this field please
see the <a
href="https://ohdsi.github.io/Themis/tag_place_of_service.html">THEMIS
Conventions</a>.
</td>
<td style="text-align:left;">
integer

30
inst/csv/OMOP_CDMv5.3_Field_Level.csv
View File

@ -1,18 +1,18 @@
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=),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. For data sources where the year of birth is not available, the approximate year of birth could be derived based on age group categorization, if available. If no year of birth is available all the person's data should be dropped from the CDM instance.",No,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,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. If birth_datetime is not provided in the source, use the following logic to infer the date: If day_of_birth is null and month_of_birth is not null then use the first of the month in that year. If month_of_birth is null or if day_of_birth AND month_of_birth are both null and the person has records during their year of birth then use the date of the earliest record, otherwise use the 15th of June of that year. If time of birth is not given use midnight (00:00:0000).",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. This could represent anything from postal code or parts thereof, state, or county for example. Since many databases contain deidentified data, it is common that the precision of the location is reduced to prevent re-identification. This field should capture the last known location.",No,Yes,LOCATION,LOCATION_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/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,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 biological sex 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 biological sex in a non-standard vocabulary, store the concept_id here.",No,Yes,CONCEPT,CONCEPT_ID,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,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
@ -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: '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: 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_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)",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_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
@ -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.","The CONCEPT_ID that the MEASUREMENT_SOURCE_CONCEPT_ID maps to. Only records whose SOURCE_CONCEPT_IDs map to Standard Concepts with a domain of ""Measurement"" 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 ÒMeasurementÓ 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
@ -150,7 +150,7 @@ measurement,measurement_type_concept_id,Yes,integer,"This field can be used to d
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,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. 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
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. 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
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
measurement,range_low,No,float,Ranges have the same unit as the VALUE_AS_NUMBER. These ranges are provided by the source and should remain NULL if not given.,If reference ranges for upper and lower limit of normal as provided (typically by a laboratory) these are stored in the RANGE_HIGH and RANGE_LOW fields. This should be set to NULL if not provided.,No,No,NA,NA,NA,NA,NA
measurement,range_high,No,float,Ranges have the same unit as the VALUE_AS_NUMBER. These ranges are provided by the source and should remain NULL if not given.,If reference ranges for upper and lower limit of normal as provided (typically by a laboratory) these are stored in the RANGE_HIGH and RANGE_LOW fields. This should be set to NULL if not provided.,No,No,NA,NA,NA,NA,NA
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
@ -158,12 +158,12 @@ measurement,visit_occurrence_id,No,integer,The visit during which the Measuremen
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
measurement,measurement_source_value,No,varchar(50),"This field houses the verbatim value from the source data representing the Measurement that occurred. For example, this could be an ICD10 or Read code.",This code is mapped to a Standard Measurement Concept in the Standardized Vocabularies and the original code is stored here for reference.,No,No,NA,NA,NA,NA,NA
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 an OMOP supported vocabulary put the concept id representing the source value here.,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
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
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
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
observation,observation_id,Yes,integer,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
observation,person_id,Yes,integer,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
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
observation,observation_date,Yes,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
observation,observation_date,Yes,date,"The date of when the Observation was obtained. 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
observation,observation_datetime,No,datetime,NA,If no time is given set to midnight (00:00:00).,No,No,NA,NA,NA,NA,NA
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=).",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
@ -179,12 +179,12 @@ 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
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.",No,No,NA,NA,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
death,death_datetime,No,datetime,NA,If not available set time to midnight (00:00:00),No,No,NA,NA,NA,NA,NA
death,death_type_concept_id,No,integer,"This is the provenance of the death record, i.e., where it came from. It is possible that an administrative claims database would source death information from a government file so do not assume the Death Type is the same as the Visit Type, etc.",Use the type concept that be reflects the source of the death 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
death,cause_concept_id,No,integer,"This is the Standard Concept representing the Person's cause of death, if available.","There is no specified domain for this concept, just choose the Standard Concept Id that best represents the person's cause of death.",No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
death,cause_source_value,No,varchar(50),NA,"If available, put the source code representing the cause of death here.",No,No,NA,NA,NA,NA,NA
death,cause_source_concept_id,No,integer,NA,If the cause of death was coded using a Vocabulary present in the OMOP Vocabularies put the CONCEPT_ID representing the cause of death here.,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
death,cause_source_concept_id,No,integer,NA,If the cause of death was coded using a Vocabulary present in the OMOP Vocabularies (not necessarily a standard concept) put the CONCEPT_ID representing the cause of death here.,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
note,note_id,Yes,integer,A unique identifier for each note.,NA,Yes,No,NA,NA,NA,NA,NA
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
@ -258,7 +258,7 @@ location,county,No,varchar(20),NA,NA,No,No,NA,NA,NA,NA,NA
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
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
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
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=).",No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
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
care_site,location_id,No,integer,The location_id from the LOCATION table representing the physical location of the care_site.,NA,No,Yes,LOCATION,LOCATION_ID,NA,NA,NA
care_site,care_site_source_value,No,varchar(50),The identifier of the care_site as it appears in the source data. This could be an identifier separate from the name of the care_site.,NA,No,No,NA,NA,NA,NA,NA
care_site,place_of_service_source_value,No,varchar(50),NA,Put the place of service of the care_site as it appears in the source data.,No,No,NA,NA,NA,NA,NA

1 cdmTableName cdmFieldName isRequired cdmDatatype userGuidance etlConventions isPrimaryKey isForeignKey fkTableName fkFieldName fkDomain fkClass unique DQ identifiers
2 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
3 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=) 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
4 person year_of_birth Yes integer Compute age using year_of_birth. For data sources with date of birth, the year should be extracted. For data sources where the year of birth is not available, the approximate year of birth could be derived based on age group categorization, if available. If no year of birth is available all the person's data should be dropped from the CDM instance. 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
5 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
6 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
7 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. If birth_datetime is not provided in the source, use the following logic to infer the date: If day_of_birth is null and month_of_birth is not null then use the first of the month in that year. If month_of_birth is null or if day_of_birth AND month_of_birth are both null and the person has records during their year of birth then use the date of the earliest record, otherwise use the 15th of June of that year. If time of birth is not given use midnight (00:00:0000). 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
8 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
9 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
10 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. This could represent anything from postal code or parts thereof, state, or county for example. Since many databases contain deidentified data, it is common that the precision of the location is reduced to prevent re-identification. This field should capture the last known location. 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
11 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
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 biological sex of the person as it appears in the source data. 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 biological sex in a non-standard vocabulary, store the concept_id here. 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
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
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
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 houses the verbatim value from the source data representing the Measurement that occurred. For example, this could be an ICD10 or Read code. This code is mapped to a Standard Measurement Concept in the Standardized Vocabularies and the original code is stored here for reference. 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 an OMOP supported vocabulary put 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 houses the verbatim value from the source data representing the unit of the Measurement that occurred. This field contains the exact value from the source data that represents the unit of measurement used. This code is mapped to a Standard Condition Concept in the Standardized Vocabularies and the original code is stored here for reference. 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
150 observation person_id Yes integer 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
151 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
152 observation observation_date Yes 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. The date of when the Observation was obtained. 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
153 observation observation_datetime No datetime NA If no time is given set to midnight (00:00:00). No No NA NA NA NA NA
154 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=). No Yes CONCEPT CONCEPT_ID Type Concept NA NA
155 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
156 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
158 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
159 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
160 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
161 observation visit_occurrence_id No integer The visit during which the Observation occurred. Depending on the structure of the source data, this may have to be determined based on dates. If an OBSERVATION_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 observation record. If an observation is related to a visit explicitly in the source data, it is possible that the result date of the Observation falls outside of the bounds of the Visit dates. No Yes VISIT_OCCURRENCE VISIT_OCCURRENCE_ID NA NA NA
162 observation visit_detail_id No integer The VISIT_DETAIL record during which the Observation 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
163 observation observation_source_value No varchar(50) This field houses the verbatim value from the source data representing the Observation that occurred. For example, this could be an ICD10 or Read code. This code is mapped to a Standard Concept in the Standardized Vocabularies and the original code is stored here for reference. No No NA NA NA NA NA
164 observation observation_source_concept_id No integer This is the concept representing the OBSERVATION_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 Observation necessary for a given analytic use case. Consider using OBSERVATION_CONCEPT_ID instead to enable standardized analytics that can be consistent across the network. If the OBSERVATION_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
165 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
166 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
167 death person_id Yes integer NA NA No Yes PERSON PERSON_ID NA NA NA
168 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. 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
169 death death_datetime No datetime NA If not available set time to midnight (00:00:00) No No NA NA NA NA NA
179 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
180 note note_title No varchar(250) The title of the note. NA No No NA NA NA NA NA
181 note note_text Yes varchar(MAX) The content of the note. NA No No NA NA NA NA NA
182 note encoding_concept_id Yes integer This is the Concept representing the character encoding type. Put the Concept Id that represents the encoding character type here. Currently the only option is UTF-8 ([32678](https://athena.ohdsi.org/search-terms/terms/32678)). It the note is encoded in any other type, like ASCII then put 0. No Yes CONCEPT CONCEPT_ID NA NA NA
183 note language_concept_id Yes integer The language of the note. Use Concepts that are descendants of the concept [4182347](https://athena.ohdsi.org/search-terms/terms/4182347) (World Languages). No Yes CONCEPT CONCEPT_ID NA NA NA
184 note provider_id No integer The Provider who wrote the note. The ETL may need to make a determination on which provider to put here. No Yes PROVIDER PROVIDER_ID NA NA NA
185 note visit_occurrence_id No integer The Visit during which the note was written. NA No Yes VISIT_OCCURRENCE VISIT_OCCURRENCE_ID NA NA NA
186 note visit_detail_id No integer The Visit Detail during which the note was written. NA No Yes VISIT_DETAIL VISIT_DETAIL_ID NA NA NA
187 note note_source_value No varchar(50) NA The source value mapped to the NOTE_CLASS_CONCEPT_ID. No No NA NA NA NA NA
188 note_nlp note_nlp_id Yes integer A unique identifier for the NLP record. NA Yes No NA NA NA NA NA
189 note_nlp note_id Yes integer This is the NOTE_ID for the NOTE record the NLP record is associated to. NA 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
258 payer_plan_period plan_source_concept_id No integer NA If the source data codes the Plan in an OMOP supported vocabulary store the concept_id here. No Yes CONCEPT CONCEPT_ID NA NA NA
259 payer_plan_period sponsor_concept_id No integer This field represents the sponsor of the Plan who finances the Plan. This includes self-insured, small group health plan and large group health plan. Map the sponsor directly to a standard CONCEPT_ID. If one does not exists please contact the vocabulary team. There is no global controlled vocabulary available for this information. The point is to stratify on this information and identify if Persons have the same sponsor though the name of the sponsor is not necessary. [Accepted Concepts](http://athena.ohdsi.org/search-terms/terms?domain=Sponsor&standardConcept=Standard&page=1&pageSize=15&query=). No Yes CONCEPT CONCEPT_ID NA NA NA
260 payer_plan_period sponsor_source_value No varchar(50) The Plan sponsor as it appears in the source data. NA No No NA NA NA NA NA
261 payer_plan_period sponsor_source_concept_id No integer NA If the source data codes the sponsor in an OMOP supported vocabulary store the concept_id here. No Yes CONCEPT CONCEPT_ID NA NA NA
262 payer_plan_period family_source_value No varchar(50) The common identifier for all people (often a family) that covered by the same policy. Often these are the common digits of the enrollment id of the policy members. No No NA NA NA NA NA
263 payer_plan_period stop_reason_concept_id No integer This field represents the reason the Person left the Plan, if known. Map the stop reason directly to a standard CONCEPT_ID. If one does not exists please contact the vocabulary team. There is no global controlled vocabulary available for this information. [Accepted Concepts](http://athena.ohdsi.org/search-terms/terms?domain=Plan+Stop+Reason&standardConcept=Standard&page=1&pageSize=15&query=). No Yes CONCEPT CONCEPT_ID NA NA NA
264 payer_plan_period stop_reason_source_value No varchar(50) The Plan stop reason as it appears in the source data. NA No No NA NA NA NA NA

10
inst/csv/OMOP_CDMv5.3_Table_Level.csv
View File

@ -1,5 +1,5 @@
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."
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:
@ -18,12 +18,12 @@ 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.
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.
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.","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 though they still should be Standard Concepts.","Records whose Source Values map to any domain besides Condition, Procedure, Drug, 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,NA
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)."
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)
@ -41,7 +41,7 @@ fact_relationship,CDM,No,NA,No,NA,NA,"The FACT_RELATIONSHIP table contains recor
- 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 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."
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. 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
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.

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. 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.
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 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. 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. 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
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 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 within standardized analytics. Each Standard Concept belongs to one domain, which defines the location where the Concept would be expected to occur within data tables of the CDM. Concepts can represent broad categories (like '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 Concepts defined to cover various aspects of observational data analysis. NA NA
28 vocabulary VOCAB No NA No NA NA The VOCABULARY table includes a list of the Vocabularies collected from various sources or created de novo by the OMOP community. This reference table is populated with a single record for each Vocabulary source and includes a descriptive name and other associated attributes for the Vocabulary. NA NA
29 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
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inst/csv/OMOP_CDMv5.4_Field_Level.csv
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@ -1,18 +1,18 @@
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=),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. For data sources where the year of birth is not available, the approximate year of birth could be derived based on age group categorization, if available. If no year of birth is available all the person's data should be dropped from the CDM instance.",No,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,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. If birth_datetime is not provided in the source, use the following logic to infer the date: If day_of_birth is null and month_of_birth is not null then use the first of the month in that year. If month_of_birth is null or if day_of_birth AND month_of_birth are both null and the person has records during their year of birth then use the date of the earliest record, otherwise use the 15th of June of that year. If time of birth is not given use midnight (00:00:0000).",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/cdm54.html#LOCATION) table here that represents the most granular location information for the person. This could represent anything from postal code or parts thereof, state, or county for example. Since many databases contain deidentified data, it is common that the precision of the location is reduced to prevent re-identification. This field should capture the last known location.",No,Yes,LOCATION,LOCATION_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/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,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 biological sex 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 biological sex in a non-standard vocabulary, store the concept_id here.",No,Yes,CONCEPT,CONCEPT_ID,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,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
@ -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: '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: 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_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)",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_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
@ -148,7 +148,7 @@ 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.","The CONCEPT_ID that the MEASUREMENT_SOURCE_CONCEPT_ID maps to. Only records whose SOURCE_CONCEPT_IDs map to Standard Concepts with a domain of ""Measurement"" 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 ÒMeasurementÓ 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
@ -156,7 +156,7 @@ measurement,measurement_type_concept_id,Yes,integer,"This field can be used to d
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,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. 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
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. 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
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
measurement,range_low,No,float,Ranges have the same unit as the VALUE_AS_NUMBER. These ranges are provided by the source and should remain NULL if not given.,If reference ranges for upper and lower limit of normal as provided (typically by a laboratory) these are stored in the RANGE_HIGH and RANGE_LOW fields. This should be set to NULL if not provided.,No,No,NA,NA,NA,NA,NA
measurement,range_high,No,float,Ranges have the same unit as the VALUE_AS_NUMBER. These ranges are provided by the source and should remain NULL if not given.,If reference ranges for upper and lower limit of normal as provided (typically by a laboratory) these are stored in the RANGE_HIGH and RANGE_LOW fields. This should be set to NULL if not provided.,No,No,NA,NA,NA,NA,NA
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
@ -164,7 +164,7 @@ measurement,visit_occurrence_id,No,integer,The visit during which the Measuremen
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
measurement,measurement_source_value,No,varchar(50),"This field houses the verbatim value from the source data representing the Measurement that occurred. For example, this could be an ICD10 or Read code.",This code is mapped to a Standard Measurement Concept in the Standardized Vocabularies and the original code is stored here for reference.,No,No,NA,NA,NA,NA,NA
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 an OMOP supported vocabulary put the concept id representing the source value here.,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
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
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
measurement,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 Measurement 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,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
measurement,measurement_event_id,No,integer,"If the Measurement 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.",No,No,NA,NA,NA,NA,NA
@ -172,7 +172,7 @@ measurement,meas_event_field_concept_id,No,integer,"If the Measurement record is
observation,observation_id,Yes,integer,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
observation,person_id,Yes,integer,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
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
observation,observation_date,Yes,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
observation,observation_date,Yes,date,"The date of when the Observation was obtained. 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
observation,observation_datetime,No,datetime,NA,If no time is given set to midnight (00:00:00).,No,No,NA,NA,NA,NA,NA
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
@ -191,12 +191,12 @@ observation,value_source_value,No,varchar(50),This field houses the verbatim res
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,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.",No,No,NA,NA,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
death,death_datetime,No,datetime,NA,If not available set time to midnight (00:00:00),No,No,NA,NA,NA,NA,NA
death,death_type_concept_id,No,integer,"This is the provenance of the death record, i.e., where it came from. It is possible that an administrative claims database would source death information from a government file so do not assume the Death Type is the same as the Visit Type, etc.",Use the type concept that be reflects the source of the death 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
death,cause_concept_id,No,integer,"This is the Standard Concept representing the Person's cause of death, if available.","There is no specified domain for this concept, just choose the Standard Concept Id that best represents the person's cause of death.",No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
death,cause_source_value,No,varchar(50),NA,"If available, put the source code representing the cause of death here.",No,No,NA,NA,NA,NA,NA
death,cause_source_concept_id,No,integer,NA,If the cause of death was coded using a Vocabulary present in the OMOP Vocabularies put the CONCEPT_ID representing the cause of death here.,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
death,cause_source_concept_id,No,integer,NA,If the cause of death was coded using a Vocabulary present in the OMOP Vocabularies (not necessarily a standard concept) put the CONCEPT_ID representing the cause of death here.,No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
note,note_id,Yes,integer,A unique identifier for each note.,NA,Yes,No,NA,NA,NA,NA,NA
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
@ -276,7 +276,7 @@ location,latitude,No,float,NA,Must be between -90 and 90.,No,No,NA,NA,NA,NA,NA
location,longitude,No,float,NA,Must be between -180 and 180.,No,No,NA,NA,NA,NA,NA
care_site,care_site_id,Yes,integer,NA,"Assign an ID to each combination of a location and nature of the site - the latter could be the Place of Service, name or another characteristic in your source data.",Yes,No,NA,NA,NA,NA,NA
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
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=).",No,Yes,CONCEPT,CONCEPT_ID,NA,NA,NA
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
care_site,location_id,No,integer,The location_id from the LOCATION table representing the physical location of the care_site.,NA,No,Yes,LOCATION,LOCATION_ID,NA,NA,NA
care_site,care_site_source_value,No,varchar(50),The identifier of the care_site as it appears in the source data. This could be an identifier separate from the name of the care_site.,NA,No,No,NA,NA,NA,NA,NA
care_site,place_of_service_source_value,No,varchar(50),NA,Put the place of service of the care_site as it appears in the source data.,No,No,NA,NA,NA,NA,NA

1 cdmTableName cdmFieldName isRequired cdmDatatype userGuidance etlConventions isPrimaryKey isForeignKey fkTableName fkFieldName fkDomain fkClass unique DQ identifiers
2 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
3 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=) 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
4 person year_of_birth Yes integer Compute age using year_of_birth. For data sources with date of birth, the year should be extracted. For data sources where the year of birth is not available, the approximate year of birth could be derived based on age group categorization, if available. If no year of birth is available all the person's data should be dropped from the CDM instance. 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
5 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
6 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
7 person birth_datetime No datetime NA This field is not required but highly encouraged for data sources that provide the precise datetime of birth. If birth_datetime is not provided in the source, use the following logic to infer the date: If day_of_birth is null and month_of_birth is not null then use the first of the month in that year. If month_of_birth is null or if day_of_birth AND month_of_birth are both null and the person has records during their year of birth then use the date of the earliest record, otherwise use the 15th of June of that year. If time of birth is not given use midnight (00:00:0000). 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
8 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
9 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
10 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. This could represent anything from postal code or parts thereof, state, or county for example. Since many databases contain deidentified data, it is common that the precision of the location is reduced to prevent re-identification. This field should capture the last known location. 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
11 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
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 biological sex of the person as it appears in the source data. 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 biological sex in a non-standard vocabulary, store the concept_id here. 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
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
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 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
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
148 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
149 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
150 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
151 measurement measurement_source_value No varchar(50) This field houses the verbatim value from the source data representing the Measurement that occurred. For example, this could be an ICD10 or Read code. This code is mapped to a Standard Measurement Concept in the Standardized Vocabularies and the original code is stored here for reference. No No NA NA NA NA NA
152 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 an OMOP supported vocabulary put the concept id representing the source value here. No Yes CONCEPT CONCEPT_ID NA NA NA
153 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 field contains the exact value from the source data that represents the unit of measurement used. This code is mapped to a Standard Condition Concept in the Standardized Vocabularies and the original code is stored here for reference. 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
154 measurement 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 Measurement 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
156 measurement measurement_event_id No integer If the Measurement 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. No No NA NA NA NA NA
157 measurement meas_event_field_concept_id No integer If the Measurement 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 MEASUREMENT_EVENT_ID came from. No Yes CONCEPT CONCEPT_ID NA NA NA
158 observation observation_id Yes integer 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
159 observation person_id Yes integer 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
160 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
161 observation observation_date Yes 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. The date of when the Observation was obtained. 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
162 observation observation_datetime No datetime NA If no time is given set to midnight (00:00:00). No No NA NA NA NA NA
164 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
165 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
166 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
167 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
168 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
169 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
170 observation visit_occurrence_id No integer The visit during which the Observation occurred. Depending on the structure of the source data, this may have to be determined based on dates. If an OBSERVATION_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 observation record. If an observation is related to a visit explicitly in the source data, it is possible that the result date of the Observation falls outside of the bounds of the Visit dates. No Yes VISIT_OCCURRENCE VISIT_OCCURRENCE_ID NA NA NA
172 observation observation_source_value No varchar(50) This field houses the verbatim value from the source data representing the Observation that occurred. For example, this could be an ICD10 or Read code. This code is mapped to a Standard Concept in the Standardized Vocabularies and the original code is stored here for reference. No No NA NA NA NA NA
173 observation observation_source_concept_id No integer This is the concept representing the OBSERVATION_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 Observation necessary for a given analytic use case. Consider using OBSERVATION_CONCEPT_ID instead to enable standardized analytics that can be consistent across the network. If the OBSERVATION_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
174 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
175 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
176 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
177 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
178 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
191 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
192 note note_title No varchar(250) The title of the note. NA No No NA NA NA NA NA
193 note note_text Yes varchar(MAX) The content of the note. NA No No NA NA NA NA NA
194 note encoding_concept_id Yes integer This is the Concept representing the character encoding type. Put the Concept Id that represents the encoding character type here. Currently the only option is UTF-8 ([32678](https://athena.ohdsi.org/search-terms/terms/32678)). It the note is encoded in any other type, like ASCII then put 0. No Yes CONCEPT CONCEPT_ID NA NA NA
195 note language_concept_id Yes integer The language of the note. Use Concepts that are descendants of the concept [4182347](https://athena.ohdsi.org/search-terms/terms/4182347) (World Languages). No Yes CONCEPT CONCEPT_ID NA NA NA
196 note provider_id No integer The Provider who wrote the note. The ETL may need to make a determination on which provider to put here. No Yes PROVIDER PROVIDER_ID NA NA NA
197 note visit_occurrence_id No integer The Visit during which the note was written. NA No Yes VISIT_OCCURRENCE VISIT_OCCURRENCE_ID NA NA NA
198 note visit_detail_id No integer The Visit Detail during which the note was written. NA No Yes VISIT_DETAIL VISIT_DETAIL_ID NA NA NA
199 note note_source_value No varchar(50) NA The source value mapped to the NOTE_CLASS_CONCEPT_ID. No No NA NA NA NA NA
200 note note_event_id No integer If the Note 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. No No NA NA NA NA NA
201 note note_event_field_concept_id No integer If the Note 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 NOTE_EVENT_ID came from. No Yes CONCEPT CONCEPT_ID NA NA NA
202 note_nlp note_nlp_id Yes integer A unique identifier for the NLP record. NA Yes No NA NA NA NA NA
276 payer_plan_period plan_source_concept_id No integer NA If the source data codes the Plan in an OMOP supported vocabulary store the concept_id here. No Yes CONCEPT CONCEPT_ID NA NA NA
277 payer_plan_period sponsor_concept_id No integer This field represents the sponsor of the Plan who finances the Plan. This includes self-insured, small group health plan and large group health plan. Map the sponsor directly to a standard CONCEPT_ID. If one does not exists please contact the vocabulary team. There is no global controlled vocabulary available for this information. The point is to stratify on this information and identify if Persons have the same sponsor though the name of the sponsor is not necessary. [Accepted Concepts](http://athena.ohdsi.org/search-terms/terms?domain=Sponsor&standardConcept=Standard&page=1&pageSize=15&query=). No Yes CONCEPT CONCEPT_ID NA NA NA
278 payer_plan_period sponsor_source_value No varchar(50) The Plan sponsor as it appears in the source data. NA No No NA NA NA NA NA
279 payer_plan_period sponsor_source_concept_id No integer NA If the source data codes the sponsor in an OMOP supported vocabulary store the concept_id here. No Yes CONCEPT CONCEPT_ID NA NA NA
280 payer_plan_period family_source_value No varchar(50) The common identifier for all people (often a family) that covered by the same policy. Often these are the common digits of the enrollment id of the policy members. No No NA NA NA NA NA
281 payer_plan_period stop_reason_concept_id No integer This field represents the reason the Person left the Plan, if known. Map the stop reason directly to a standard CONCEPT_ID. If one does not exists please contact the vocabulary team. There is no global controlled vocabulary available for this information. [Accepted Concepts](http://athena.ohdsi.org/search-terms/terms?domain=Plan+Stop+Reason&standardConcept=Standard&page=1&pageSize=15&query=). No Yes CONCEPT CONCEPT_ID NA NA NA
282 payer_plan_period stop_reason_source_value No varchar(50) The Plan stop reason as it appears in the source data. NA No No NA NA NA NA NA

10
inst/csv/OMOP_CDMv5.4_Table_Level.csv
View File

@ -1,5 +1,5 @@
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."
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:
@ -18,12 +18,12 @@ 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.
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.
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 though they still should be Standard Concepts.","Records whose Source Values map to any domain besides Condition, Procedure, Drug, 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,NA
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)."
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)
@ -41,7 +41,7 @@ fact_relationship,CDM,No,NA,No,NA,NA,"The FACT_RELATIONSHIP table contains recor
- 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 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."
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. 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
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.

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. 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.
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 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. 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. 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
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 within standardized analytics. Each Standard Concept belongs to one domain, which defines the location where the Concept would be expected to occur within data tables of the CDM. Concepts can represent broad categories (like '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 Concepts defined to cover various aspects of observational data analysis. NA NA
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