[DATALAD RUNCMD] run codespell throughout fixing typos automagically

=== Do not change lines below ===
{
 "chain": [],
 "cmd": "codespell -w",
 "exit": 0,
 "extra_inputs": [],
 "inputs": [],
 "outputs": [],
 "pwd": "."
}
^^^ Do not change lines above ^^^
This commit is contained in:
Yaroslav Halchenko 2024-03-28 15:31:24 -04:00
parent 0c031eee12
commit dceb3a182b
14 changed files with 23 additions and 23 deletions

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@ -17,7 +17,7 @@
#' Create OMOP CDM SQL files
#'
#' Writes DDL, ForeignKey, PrimaryKey and index SQL files for given cdmVersion
#' and targetDialect to the 'ddl' folder in specifed output folder.
#' and targetDialect to the 'ddl' folder in specified output folder.
#'
#' @param cdmVersions The versions of the CDM you are creating, e.g. 5.3, 5.4.
#' Defaults to all supported CDM versions.
@ -26,7 +26,7 @@
#' @param outputfolder The base folder where the SQL files will be written.
#' Subfolders will be created for each cdmVersion and targetDialect.
#' @return Writes DDL, ForeignKey, PrimaryKey and index SQL files for given cdmVersion
#' and targetDialect to the 'ddl' folder in specifed output folder.
#' and targetDialect to the 'ddl' folder in specified output folder.
#' @export
buildRelease <- function(cdmVersions = listSupportedVersions(),
targetDialects = listSupportedDialects(),

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@ -1124,7 +1124,7 @@ CONCEPT
<p><strong>Table Description</strong></p>
<p>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) absense of
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.</p>
<p><strong>User Guide</strong></p>
<p>For each Person, one or more OBSERVATION_PERIOD records may be

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@ -1232,7 +1232,7 @@ CONCEPT
<p><strong>Table Description</strong></p>
<p>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) absense of
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.</p>
<p><strong>User Guide</strong></p>
<p>For each Person, one or more OBSERVATION_PERIOD records may be

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@ -504,7 +504,7 @@ prioritise in the mapping. Most value will be gained from populating
fields support across the OHDSI tooling.</li>
<li>For OHDSI tooling developers, this page provides insight in the gaps
of support and can drive future development efforts.</li>
<li>For CDM extenstions, it helps to known what it means for an OMOP CDM
<li>For CDM extensions, it helps to known what it means for an OMOP CDM
table/field to be part of the standard. In other words: what OHDSI
tooling do we at least expect to support the new extensions?</li>
</ul>
@ -582,7 +582,7 @@ Achilles only checked for a valid foreign key to the provider table.</p>
</colgroup>
<thead>
<tr class="header">
<th><strong>Abbrevations</strong></th>
<th><strong>Abbreviations</strong></th>
<th> </th>
</tr>
</thead>

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@ -1218,7 +1218,7 @@ CONCEPT
<p><strong>Table Description</strong></p>
<p>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) absense of
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.</p>
<p><strong>User Guide</strong></p>
<p>For each Person, one or more OBSERVATION_PERIOD records may be

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@ -1087,7 +1087,7 @@ $(document).ready(function () {
</tr>
<tr class="odd">
<td align="left">5</td>
<td align="left">Concept Relationships define direct relationships between Concepts. Indirect relationships through 3rd Concepts are not captured in this table. However, the <a href="https://github.com/OHDSI/CommonDataModel/wiki/CONCEPT_ANCESTOR">CONCEPT_ANCESTOR</a> table does this for hierachical relationships over several “generations” of direct relationships.</td>
<td align="left">Concept Relationships define direct relationships between Concepts. Indirect relationships through 3rd Concepts are not captured in this table. However, the <a href="https://github.com/OHDSI/CommonDataModel/wiki/CONCEPT_ANCESTOR">CONCEPT_ANCESTOR</a> table does this for hierarchical relationships over several “generations” of direct relationships.</td>
</tr>
</tbody>
</table>
@ -5203,7 +5203,7 @@ Person, 2, Person, 1, child of
<td align="left">payer_concept_id</td>
<td align="left">Yes</td>
<td align="left">integer</td>
<td align="left">A foreign key that refers to a standard Payer concept identifier in the Standarized Vocabularies</td>
<td align="left">A foreign key that refers to a standard Payer concept identifier in the Standardized Vocabularies</td>
</tr>
<tr class="odd">
<td align="left">payer_source_value</td>

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@ -1000,7 +1000,7 @@ $(document).ready(function () {
</tr>
<tr class="odd">
<td align="left">5</td>
<td align="left">Concept Relationships define direct relationships between Concepts. Indirect relationships through 3rd Concepts are not captured in this table. However, the <a href="https://github.com/OHDSI/CommonDataModel/wiki/CONCEPT_ANCESTOR">CONCEPT_ANCESTOR</a> table does this for hierachical relationships over several “generations” of direct relationships.</td>
<td align="left">Concept Relationships define direct relationships between Concepts. Indirect relationships through 3rd Concepts are not captured in this table. However, the <a href="https://github.com/OHDSI/CommonDataModel/wiki/CONCEPT_ANCESTOR">CONCEPT_ANCESTOR</a> table does this for hierarchical relationships over several “generations” of direct relationships.</td>
</tr>
</tbody>
</table>

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@ -1018,7 +1018,7 @@ NA
observation_period_start_date
</td>
<td style="text-align:left;">
Use this date to determine the start date of the period for which we can assume that all events for a Person are recorded and any absense of records indicates an absence of events.
Use this date to determine the start date of the period for which we can assume that all events for a Person are recorded and any absence of records indicates an absence of events.
</td>
<td style="text-align:left;">
It is often the case that the idea of observation periods does not exist in source data. In those cases the observation_period_start_date can be inferred as the earliest event date available for the Person. In US claims, the observation period can be considered as the time period the person is enrolled with an insurer. If a Person switches plans but stays with the same insurer, that change would be captured in payer_plan_period.
@ -1050,7 +1050,7 @@ NA
observation_period_end_date
</td>
<td style="text-align:left;">
Use this date to determine the end date of the period for which we can assume that all events for a Person are recorded and any absense of records indicates an absence of events.
Use this date to determine the end date of the period for which we can assume that all events for a Person are recorded and any absence of records indicates an absence of events.
</td>
<td style="text-align:left;">
It is often the case that the idea of observation periods does not exist in source data. In those cases the observation_period_start_end_date can be inferred as the latest event date available for the Person. The event dates include insurance enrollment dates.
@ -1667,7 +1667,7 @@ NA
preceding_visit_occurrence_id
</td>
<td style="text-align:left;">
Use this field to find the visit that occured for the person prior to the given visit. There could be a few days or a few years in between.
Use this field to find the visit that occurred for the person prior to the given visit. There could be a few days or a few years in between.
</td>
<td style="text-align:left;">
The preceding_visit_id can be used to link a visit immediately preceding the current visit. Note this is not symmetrical, and there is no such thing as a “following_visit_id”.
@ -10200,7 +10200,7 @@ NA
<p>The Drug Era End Date is the end date of the last Drug Exposure. The End Date of each Drug Exposure is either taken from the field drug_exposure_end_date or, as it is typically not available, inferred using the following rules:</p>
<p>For pharmacy prescription data, the date when the drug was dispensed plus the number of days of supply are used to extrapolate the End Date for the Drug Exposure. Depending on the country-specific healthcare system, this supply information is either explicitly provided in the day_supply field or inferred from package size or similar information.</p>
<p>For Procedure Drugs, usually the drug is administered on a single date (i.e., the administration date).</p>
A standard Persistence Window of 30 days (gap, slack) is permitted between two subsequent such extrapolated DRUG_EXPOSURE records to be considered to be merged into a single Drug Era. (ARENT WE REQUIRING TO USE DRUG_EXPOSURE_END_DATE NOW????)
A standard Persistence Window of 30 days (gap, slack) is permitted between two subsequent such extrapolated DRUG_EXPOSURE records to be considered to be merged into a single Drug Era. (AREN'T WE REQUIRING TO USE DRUG_EXPOSURE_END_DATE NOW????)
</td>
<td style="text-align:left;">
datetime
@ -20702,7 +20702,7 @@ NA
payer_concept_id
</td>
<td style="text-align:left;">
A foreign key that refers to a standard Payer concept identifier in the Standarized Vocabularies
A foreign key that refers to a standard Payer concept identifier in the Standardized Vocabularies
</td>
<td style="text-align:left;">
NA

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@ -10,7 +10,7 @@ episode,episode_parent_id,No,bigint,Use this field to find the Episode that subs
episode,episode_number,No,integer,"For sequences of episodes, this is used to indicate the order the episodes occurred. For example, lines of treatment could be indicated here. ",Please see [article] for the details of how to count episodes.,No,No,,,,
episode,episode_object_concept_id,Yes,integer,"A Standard Concept representing the disease phase, outcome, or other abstraction of which the episode consists. For example, if the episode_concept_id is [treatment regimen](https://athena.ohdsi.org/search-terms/terms/32531) then the episode_object_concept_id should contain the chemotherapy regimen concept, like [Afatinib monotherapy](https://athena.ohdsi.org/search-terms/terms/35804392). ",Episode entries from the 'Disease Episode' concept class should have an episode_object_concept_id that comes from the Condition domain. Episode entries from the 'Treatment Episode' concept class should have an episode_object_concept_id that scome from the 'Procedure' domain or 'Regimen' concept class.,No,Yes,concept,concept_id,"Procedure, Regimen",
episode,episode_type_concept_id,Yes,integer,"This field can be used to determine the provenance of the Episode record, as in whether the episode was from an EHR system, insurance claim, registry, or other sources.",Choose the episode_type_concept_id that best represents the provenance of the record. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Type+Concept&standardConcept=Standard&page=1&pageSize=15&query=).,No,Yes,concept,concept_id,Type Concept,
episode,episode_source_value,No,varchar(50),The source code for the Episdoe as it appears in the source data. This code is mapped to a Standard Condition Concept in the Standardized Vocabularies and the original code is stored here for reference.,,No,No,,,,
episode,episode_source_value,No,varchar(50),The source code for the Episode as it appears in the source data. This code is mapped to a Standard Condition Concept in the Standardized Vocabularies and the original code is stored here for reference.,,No,No,,,,
episode,episode_source_concept_id,No,integer,A foreign key to a Episode Concept that refers to the code used in the source.,Given that the Episodes are user-defined it is unlikely that there will be a Source Concept available. If that is the case then set this field to zero. ,No,Yes,concept,concept_id,,
episode_event,episode_id,Yes,bigint,Use this field to link the episode_event record to its episode.,Put the episode_id that subsumes the episode_event record here.,No,Yes,episode,episode_id,,
episode_event,event_id,Yes,bigint,"This field is the primary key of the linked record in the database. For example, if the Episode Event is a Condition Occurrence, then the condition_occurrence_id of the linked record goes in this field. ",Put the primary key of the linked record here. ,No,No,,,,

1 cdmTableName cdmFieldName isRequired cdmDatatype userGuidance etlConventions isPrimaryKey isForeignKey fkTableName fkFieldName fkDomain fkClass
10 episode episode_number No integer For sequences of episodes, this is used to indicate the order the episodes occurred. For example, lines of treatment could be indicated here. Please see [article] for the details of how to count episodes. No No
11 episode episode_object_concept_id Yes integer A Standard Concept representing the disease phase, outcome, or other abstraction of which the episode consists. For example, if the episode_concept_id is [treatment regimen](https://athena.ohdsi.org/search-terms/terms/32531) then the episode_object_concept_id should contain the chemotherapy regimen concept, like [Afatinib monotherapy](https://athena.ohdsi.org/search-terms/terms/35804392). Episode entries from the 'Disease Episode' concept class should have an episode_object_concept_id that comes from the Condition domain. Episode entries from the 'Treatment Episode' concept class should have an episode_object_concept_id that scome from the 'Procedure' domain or 'Regimen' concept class. No Yes concept concept_id Procedure, Regimen
12 episode episode_type_concept_id Yes integer This field can be used to determine the provenance of the Episode record, as in whether the episode was from an EHR system, insurance claim, registry, or other sources. Choose the episode_type_concept_id that best represents the provenance of the record. [Accepted Concepts](https://athena.ohdsi.org/search-terms/terms?domain=Type+Concept&standardConcept=Standard&page=1&pageSize=15&query=). No Yes concept concept_id Type Concept
13 episode episode_source_value No varchar(50) The source code for the Episdoe as it appears in the source data. This code is mapped to a Standard Condition Concept in the Standardized Vocabularies and the original code is stored here for reference. The source code for the Episode as it appears in the source data. This code is mapped to a Standard Condition Concept in the Standardized Vocabularies and the original code is stored here for reference. No No
14 episode episode_source_concept_id No integer A foreign key to a Episode Concept that refers to the code used in the source. Given that the Episodes are user-defined it is unlikely that there will be a Source Concept available. If that is the case then set this field to zero. No Yes concept concept_id
15 episode_event episode_id Yes bigint Use this field to link the episode_event record to its episode. Put the episode_id that subsumes the episode_event record here. No Yes episode episode_id
16 episode_event event_id Yes bigint This field is the primary key of the linked record in the database. For example, if the Episode Event is a Condition Occurrence, then the condition_occurrence_id of the linked record goes in this field. Put the primary key of the linked record here. No No

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@ -1,6 +1,6 @@
cdmTableName,schema,isRequired,conceptPrefix,measurePersonCompleteness,measurePersonCompletenessThreshold,validation,tableDescription,userGuidance,etlConventions
person,CDM,Yes,NA,No,NA,NA,"This table serves as the central identity management for all Persons in the database. It contains records that uniquely identify each person or patient, and some demographic information.",All records in this table are independent Persons.,"All Persons in a database needs one record in this table, unless they fail data quality requirements specified in the ETL. Persons with no Events should have a record nonetheless. If more than one data source contributes Events to the database, Persons must be reconciled, if possible, across the sources to create one single record per Person. The content of the BIRTH_DATETIME must be equivalent to the content of BIRTH_DAY, BIRTH_MONTH and BIRTH_YEAR."
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) absense of records indicate such Events did not occur during this span of time.","For each Person, one or more OBSERVATION_PERIOD records may be present, but they will not overlap or be back to back to each other. Events may exist outside all of the time spans of the OBSERVATION_PERIOD records for a patient, however, absence of an Event outside these time spans cannot be construed as evidence of absence of an Event. Incidence or prevalence rates should only be calculated for the time of active OBSERVATION_PERIOD records. When constructing cohorts, outside Events can be used for inclusion criteria definition, but without any guarantee for the performance of these criteria. Also, OBSERVATION_PERIOD records can be as short as a single day, greatly disturbing the denominator of any rate calculation as part of cohort characterizations. To avoid that, apply minimal observation time as a requirement for any cohort definition.","Each Person needs to have at least one OBSERVATION_PERIOD record, which should represent time intervals with a high capture rate of Clinical Events. Some source data have very similar concepts, such as enrollment periods in insurance claims data. In other source data such as most EHR systems these time spans need to be inferred under a set of assumptions. It is the discretion of the ETL developer to define these assumptions. In many ETL solutions the start date of the first occurrence or the first high quality occurrence of a Clinical Event (Condition, Drug, Procedure, Device, Measurement, Visit) is defined as the start of the OBSERVATION_PERIOD record, and the end date of the last occurrence of last high quality occurrence of a Clinical Event, or the end of the database period becomes the end of the OBSERVATOIN_PERIOD for each Person. If a Person only has a single Clinical Event the OBSERVATION_PERIOD record can be as short as one day. Depending on these definitions it is possible that Clinical Events fall outside the time spans defined by OBSERVATION_PERIOD records. Family history or history of Clinical Events generally are not used to generate OBSERVATION_PERIOD records around the time they are referring to. Any two overlapping or adjacent OBSERVATION_PERIOD records have to be merged into one."
observation_period,CDM,Yes,NA,Yes,0,NA,"This table contains records which define spans of time during which two conditions are expected to hold: (i) Clinical Events that happened to the Person are recorded in the Event tables, and (ii) absence of records indicate such Events did not occur during this span of time.","For each Person, one or more OBSERVATION_PERIOD records may be present, but they will not overlap or be back to back to each other. Events may exist outside all of the time spans of the OBSERVATION_PERIOD records for a patient, however, absence of an Event outside these time spans cannot be construed as evidence of absence of an Event. Incidence or prevalence rates should only be calculated for the time of active OBSERVATION_PERIOD records. When constructing cohorts, outside Events can be used for inclusion criteria definition, but without any guarantee for the performance of these criteria. Also, OBSERVATION_PERIOD records can be as short as a single day, greatly disturbing the denominator of any rate calculation as part of cohort characterizations. To avoid that, apply minimal observation time as a requirement for any cohort definition.","Each Person needs to have at least one OBSERVATION_PERIOD record, which should represent time intervals with a high capture rate of Clinical Events. Some source data have very similar concepts, such as enrollment periods in insurance claims data. In other source data such as most EHR systems these time spans need to be inferred under a set of assumptions. It is the discretion of the ETL developer to define these assumptions. In many ETL solutions the start date of the first occurrence or the first high quality occurrence of a Clinical Event (Condition, Drug, Procedure, Device, Measurement, Visit) is defined as the start of the OBSERVATION_PERIOD record, and the end date of the last occurrence of last high quality occurrence of a Clinical Event, or the end of the database period becomes the end of the OBSERVATOIN_PERIOD for each Person. If a Person only has a single Clinical Event the OBSERVATION_PERIOD record can be as short as one day. Depending on these definitions it is possible that Clinical Events fall outside the time spans defined by OBSERVATION_PERIOD records. Family history or history of Clinical Events generally are not used to generate OBSERVATION_PERIOD records around the time they are referring to. Any two overlapping or adjacent OBSERVATION_PERIOD records have to be merged into one."
visit_occurrence,CDM,No,VISIT_,Yes,0,NA,"This table contains Events where Persons engage with the healthcare system for a duration of time. They are often also called ""Encounters"". Visits are defined by a configuration of circumstances under which they occur, such as (i) whether the patient comes to a healthcare institution, the other way around, or the interaction is remote, (ii) whether and what kind of trained medical staff is delivering the service during the Visit, and (iii) whether the Visit is transient or for a longer period involving a stay in bed.","The configuration defining the Visit are described by Concepts in the Visit Domain, which form a hierarchical structure, but rolling up to generally familiar Visits adopted in most healthcare systems worldwide:
- [Inpatient Visit](https://athena.ohdsi.org/search-terms/terms/9201): Person visiting hospital, at a Care Site, in bed, for duration of more than one day, with physicians and other Providers permanently available to deliver service around the clock

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.
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) absense of records indicate such Events did not occur during this span of time. This table contains records which define spans of time during which two conditions are expected to hold: (i) Clinical Events that happened to the Person are recorded in the Event tables, and (ii) absence of records indicate such Events did not occur during this span of time. For each Person, one or more OBSERVATION_PERIOD records may be present, but they will not overlap or be back to back to each other. Events may exist outside all of the time spans of the OBSERVATION_PERIOD records for a patient, however, absence of an Event outside these time spans cannot be construed as evidence of absence of an Event. Incidence or prevalence rates should only be calculated for the time of active OBSERVATION_PERIOD records. When constructing cohorts, outside Events can be used for inclusion criteria definition, but without any guarantee for the performance of these criteria. Also, OBSERVATION_PERIOD records can be as short as a single day, greatly disturbing the denominator of any rate calculation as part of cohort characterizations. To avoid that, apply minimal observation time as a requirement for any cohort definition. Each Person needs to have at least one OBSERVATION_PERIOD record, which should represent time intervals with a high capture rate of Clinical Events. Some source data have very similar concepts, such as enrollment periods in insurance claims data. In other source data such as most EHR systems these time spans need to be inferred under a set of assumptions. It is the discretion of the ETL developer to define these assumptions. In many ETL solutions the start date of the first occurrence or the first high quality occurrence of a Clinical Event (Condition, Drug, Procedure, Device, Measurement, Visit) is defined as the start of the OBSERVATION_PERIOD record, and the end date of the last occurrence of last high quality occurrence of a Clinical Event, or the end of the database period becomes the end of the OBSERVATOIN_PERIOD for each Person. If a Person only has a single Clinical Event the OBSERVATION_PERIOD record can be as short as one day. Depending on these definitions it is possible that Clinical Events fall outside the time spans defined by OBSERVATION_PERIOD records. Family history or history of Clinical Events generally are not used to generate OBSERVATION_PERIOD records around the time they are referring to. Any two overlapping or adjacent OBSERVATION_PERIOD records have to be merged into one.
4 visit_occurrence CDM No VISIT_ Yes 0 NA This table contains Events where Persons engage with the healthcare system for a duration of time. They are often also called "Encounters". Visits are defined by a configuration of circumstances under which they occur, such as (i) whether the patient comes to a healthcare institution, the other way around, or the interaction is remote, (ii) whether and what kind of trained medical staff is delivering the service during the Visit, and (iii) whether the Visit is transient or for a longer period involving a stay in bed. The configuration defining the Visit are described by Concepts in the Visit Domain, which form a hierarchical structure, but rolling up to generally familiar Visits adopted in most healthcare systems worldwide: - [Inpatient Visit](https://athena.ohdsi.org/search-terms/terms/9201): Person visiting hospital, at a Care Site, in bed, for duration of more than one day, with physicians and other Providers permanently available to deliver service around the clock - [Emergency Room Visit](https://athena.ohdsi.org/search-terms/terms/9203): Person visiting dedicated healthcare institution for treating emergencies, at a Care Site, within one day, with physicians and Providers permanently available to deliver service around the clock - [Emergency Room and Inpatient Visit](https://athena.ohdsi.org/search-terms/terms/262): Person visiting ER followed by a subsequent Inpatient Visit, where Emergency department is part of hospital, and transition from the ER to other hospital departments is undefined - [Non-hospital institution Visit](https://athena.ohdsi.org/search-terms/terms/42898160): Person visiting dedicated institution for reasons of poor health, at a Care Site, long-term or permanently, with no physician but possibly other Providers permanently available to deliver service around the clock - [Outpatient Visit](https://athena.ohdsi.org/search-terms/terms/9202): Person visiting dedicated ambulatory healthcare institution, at a Care Site, within one day, without bed, with physicians or medical Providers delivering service during Visit - [Home Visit](https://athena.ohdsi.org/search-terms/terms/581476): Provider visiting Person, without a Care Site, within one day, delivering service - [Telehealth Visit](https://athena.ohdsi.org/search-terms/terms/5083): Patient engages with Provider through communication media - [Pharmacy Visit](https://athena.ohdsi.org/search-terms/terms/581458): Person visiting pharmacy for dispensing of Drug, at a Care Site, within one day - [Laboratory Visit](https://athena.ohdsi.org/search-terms/terms/32036): Patient visiting dedicated institution, at a Care Site, within one day, for the purpose of a Measurement. - [Ambulance Visit](https://athena.ohdsi.org/search-terms/terms/581478): Person using transportation service for the purpose of initiating one of the other Visits, without a Care Site, within one day, potentially with Providers accompanying the Visit and delivering service - [Case Management Visit](https://athena.ohdsi.org/search-terms/terms/38004193): Person interacting with healthcare system, without a Care Site, within a day, with no Providers involved, for administrative purposes The Visit duration, or 'length of stay', is defined as VISIT_END_DATE - VISIT_START_DATE. For all Visits this is <1 day, except Inpatient Visits and Non-hospital institution Visits. The CDM also contains the VISIT_DETAIL table where additional information about the Visit is stored, for example, transfers between units during an inpatient Visit. Visits can be derived easily if the source data contain coding systems for Place of Service or Procedures, like CPT codes for well visits. In those cases, the codes can be looked up and mapped to a Standard Visit Concept. Otherwise, Visit Concepts have to be identified in the ETL process. This table will contain concepts in the Visit domain. These concepts are arranged in a hierarchical structure to facilitate cohort definitions by rolling up to generally familiar Visits adopted in most healthcare systems worldwide. Visits can be adjacent to each other, i.e. the end date of one can be identical with the start date of the other. As a consequence, more than one-day Visits or their descendants can be recorded for the same day. Multi-day visits must not overlap, i.e. share days other than start and end days. It is often the case that some logic should be written for how to define visits and how to assign Visit_Concept_Id. For example, in US claims outpatient visits that appear to occur within the time period of an inpatient visit can be rolled into one with the same Visit_Occurrence_Id. In EHR data inpatient visits that are within one day of each other may be strung together to create one visit. It will all depend on the source data and how encounter records should be translated to visit occurrences. Providers can be associated with a Visit through the PROVIDER_ID field, or indirectly through PROCEDURE_OCCURRENCE records linked both to the VISIT and PROVIDER tables.
5 visit_detail CDM No VISIT_DETAIL_ Yes 0 NA The VISIT_DETAIL table is an optional table used to represents details of each record in the parent VISIT_OCCURRENCE table. A good example of this would be the movement between units in a hospital during an inpatient stay or claim lines associated with a one insurance claim. For every record in the VISIT_OCCURRENCE table there may be 0 or more records in the VISIT_DETAIL table with a 1:n relationship where n may be 0. The VISIT_DETAIL table is structurally very similar to VISIT_OCCURRENCE table and belongs to the visit domain. The configuration defining the Visit Detail is described by Concepts in the Visit Domain, which form a hierarchical structure. The Visit Detail record will have an associated to the Visit Occurrence record in two ways: <br> 1. The Visit Detail record will have the VISIT_OCCURRENCE_ID it is associated to 2. The VISIT_DETAIL_CONCEPT_ID will be a descendant of the VISIT_CONCEPT_ID for the Visit. It is not mandatory that the VISIT_DETAIL table be filled in, but if you find that the logic to create VISIT_OCCURRENCE records includes the roll-up of multiple smaller records to create one picture of a Visit then it is a good idea to use VISIT_DETAIL. In EHR data, for example, a Person may be in the hospital but instead of one over-arching Visit their encounters are recorded as times they interacted with a health care provider. A Person in the hospital interacts with multiple providers multiple times a day so the encounters must be strung together using some heuristic (defined by the ETL) to identify the entire Visit. In this case the encounters would be considered Visit Details and the entire Visit would be the Visit Occurrence. In this example it is also possible to use the Vocabulary to distinguish Visit Details from a Visit Occurrence by setting the VISIT_CONCEPT_ID to [9201](https://athena.ohdsi.org/search-terms/terms/9201) and the VISIT_DETAIL_CONCEPT_IDs either to 9201 or its children to indicate where the patient was in the hospital at the time of care.
6 condition_occurrence CDM No CONDITION_ Yes 0 NA This table contains records of Events of a Person suggesting the presence of a disease or medical condition stated as a diagnosis, a sign, or a symptom, which is either observed by a Provider or reported by the patient. Conditions are defined by Concepts from the Condition domain, which form a complex hierarchy. As a result, the same Person with the same disease may have multiple Condition records, which belong to the same hierarchical family. Most Condition records are mapped from diagnostic codes, but recorded signs, symptoms and summary descriptions also contribute to this table. Rule out diagnoses should not be recorded in this table, but in reality their negating nature is not always captured in the source data, and other precautions must be taken when when identifying Persons who should suffer from the recorded Condition. Record all conditions as they exist in the source data. Any decisions about diagnosis/phenotype definitions would be done through cohort specifications. These cohorts can be housed in the [COHORT](https://ohdsi.github.io/CommonDataModel/cdm531.html#payer_plan_period) table. Conditions span a time interval from start to end, but are typically recorded as single snapshot records with no end date. The reason is twofold: (i) At the time of the recording the duration is not known and later not recorded, and (ii) the Persons typically cease interacting with the healthcare system when they feel better, which leads to incomplete capture of resolved Conditions. The [CONDITION_ERA](https://ohdsi.github.io/CommonDataModel/cdm531.html#condition_era) table addresses this issue. Family history and past diagnoses ('history of') are not recorded in this table. Instead, they are listed in the [OBSERVATION](https://ohdsi.github.io/CommonDataModel/cdm531.html#observation) table. Codes written in the process of establishing the diagnosis, such as 'question of' of and 'rule out', should not represented here. Instead, they should be recorded in the [OBSERVATION](https://ohdsi.github.io/CommonDataModel/cdm531.html#observation) table, if they are used for analyses. However, this information is not always available. Source codes and source text fields mapped to Standard Concepts of the Condition Domain have to be recorded here.

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@ -1,6 +1,6 @@
cdmTableName,schema,isRequired,conceptPrefix,measurePersonCompleteness,measurePersonCompletenessThreshold,validation,tableDescription,userGuidance,etlConventions
person,CDM,Yes,NA,No,NA,NA,"This table serves as the central identity management for all Persons in the database. It contains records that uniquely identify each person or patient, and some demographic information.",All records in this table are independent Persons.,"All Persons in a database needs one record in this table, unless they fail data quality requirements specified in the ETL. Persons with no Events should have a record nonetheless. If more than one data source contributes Events to the database, Persons must be reconciled, if possible, across the sources to create one single record per Person. The content of the BIRTH_DATETIME must be equivalent to the content of BIRTH_DAY, BIRTH_MONTH and BIRTH_YEAR."
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) absense of records indicate such Events did not occur during this span of time.","For each Person, one or more OBSERVATION_PERIOD records may be present, but they will not overlap or be back to back to each other. Events may exist outside all of the time spans of the OBSERVATION_PERIOD records for a patient, however, absence of an Event outside these time spans cannot be construed as evidence of absence of an Event. Incidence or prevalence rates should only be calculated for the time of active OBSERVATION_PERIOD records. When constructing cohorts, outside Events can be used for inclusion criteria definition, but without any guarantee for the performance of these criteria. Also, OBSERVATION_PERIOD records can be as short as a single day, greatly disturbing the denominator of any rate calculation as part of cohort characterizations. To avoid that, apply minimal observation time as a requirement for any cohort definition.","Each Person needs to have at least one OBSERVATION_PERIOD record, which should represent time intervals with a high capture rate of Clinical Events. Some source data have very similar concepts, such as enrollment periods in insurance claims data. In other source data such as most EHR systems these time spans need to be inferred under a set of assumptions. It is the discretion of the ETL developer to define these assumptions. In many ETL solutions the start date of the first occurrence or the first high quality occurrence of a Clinical Event (Condition, Drug, Procedure, Device, Measurement, Visit) is defined as the start of the OBSERVATION_PERIOD record, and the end date of the last occurrence of last high quality occurrence of a Clinical Event, or the end of the database period becomes the end of the OBSERVATOIN_PERIOD for each Person. If a Person only has a single Clinical Event the OBSERVATION_PERIOD record can be as short as one day. Depending on these definitions it is possible that Clinical Events fall outside the time spans defined by OBSERVATION_PERIOD records. Family history or history of Clinical Events generally are not used to generate OBSERVATION_PERIOD records around the time they are referring to. Any two overlapping or adjacent OBSERVATION_PERIOD records have to be merged into one."
observation_period,CDM,Yes,NA,Yes,0,NA,"This table contains records which define spans of time during which two conditions are expected to hold: (i) Clinical Events that happened to the Person are recorded in the Event tables, and (ii) absence of records indicate such Events did not occur during this span of time.","For each Person, one or more OBSERVATION_PERIOD records may be present, but they will not overlap or be back to back to each other. Events may exist outside all of the time spans of the OBSERVATION_PERIOD records for a patient, however, absence of an Event outside these time spans cannot be construed as evidence of absence of an Event. Incidence or prevalence rates should only be calculated for the time of active OBSERVATION_PERIOD records. When constructing cohorts, outside Events can be used for inclusion criteria definition, but without any guarantee for the performance of these criteria. Also, OBSERVATION_PERIOD records can be as short as a single day, greatly disturbing the denominator of any rate calculation as part of cohort characterizations. To avoid that, apply minimal observation time as a requirement for any cohort definition.","Each Person needs to have at least one OBSERVATION_PERIOD record, which should represent time intervals with a high capture rate of Clinical Events. Some source data have very similar concepts, such as enrollment periods in insurance claims data. In other source data such as most EHR systems these time spans need to be inferred under a set of assumptions. It is the discretion of the ETL developer to define these assumptions. In many ETL solutions the start date of the first occurrence or the first high quality occurrence of a Clinical Event (Condition, Drug, Procedure, Device, Measurement, Visit) is defined as the start of the OBSERVATION_PERIOD record, and the end date of the last occurrence of last high quality occurrence of a Clinical Event, or the end of the database period becomes the end of the OBSERVATOIN_PERIOD for each Person. If a Person only has a single Clinical Event the OBSERVATION_PERIOD record can be as short as one day. Depending on these definitions it is possible that Clinical Events fall outside the time spans defined by OBSERVATION_PERIOD records. Family history or history of Clinical Events generally are not used to generate OBSERVATION_PERIOD records around the time they are referring to. Any two overlapping or adjacent OBSERVATION_PERIOD records have to be merged into one."
visit_occurrence,CDM,No,VISIT_,Yes,0,NA,"This table contains Events where Persons engage with the healthcare system for a duration of time. They are often also called ""Encounters"". Visits are defined by a configuration of circumstances under which they occur, such as (i) whether the patient comes to a healthcare institution, the other way around, or the interaction is remote, (ii) whether and what kind of trained medical staff is delivering the service during the Visit, and (iii) whether the Visit is transient or for a longer period involving a stay in bed.","The configuration defining the Visit are described by Concepts in the Visit Domain, which form a hierarchical structure, but rolling up to generally familiar Visits adopted in most healthcare systems worldwide:
- [Inpatient Visit](https://athena.ohdsi.org/search-terms/terms/9201): Person visiting hospital, at a Care Site, in bed, for duration of more than one day, with physicians and other Providers permanently available to deliver service around the clock

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.
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) absense of records indicate such Events did not occur during this span of time. This table contains records which define spans of time during which two conditions are expected to hold: (i) Clinical Events that happened to the Person are recorded in the Event tables, and (ii) absence of records indicate such Events did not occur during this span of time. For each Person, one or more OBSERVATION_PERIOD records may be present, but they will not overlap or be back to back to each other. Events may exist outside all of the time spans of the OBSERVATION_PERIOD records for a patient, however, absence of an Event outside these time spans cannot be construed as evidence of absence of an Event. Incidence or prevalence rates should only be calculated for the time of active OBSERVATION_PERIOD records. When constructing cohorts, outside Events can be used for inclusion criteria definition, but without any guarantee for the performance of these criteria. Also, OBSERVATION_PERIOD records can be as short as a single day, greatly disturbing the denominator of any rate calculation as part of cohort characterizations. To avoid that, apply minimal observation time as a requirement for any cohort definition. Each Person needs to have at least one OBSERVATION_PERIOD record, which should represent time intervals with a high capture rate of Clinical Events. Some source data have very similar concepts, such as enrollment periods in insurance claims data. In other source data such as most EHR systems these time spans need to be inferred under a set of assumptions. It is the discretion of the ETL developer to define these assumptions. In many ETL solutions the start date of the first occurrence or the first high quality occurrence of a Clinical Event (Condition, Drug, Procedure, Device, Measurement, Visit) is defined as the start of the OBSERVATION_PERIOD record, and the end date of the last occurrence of last high quality occurrence of a Clinical Event, or the end of the database period becomes the end of the OBSERVATOIN_PERIOD for each Person. If a Person only has a single Clinical Event the OBSERVATION_PERIOD record can be as short as one day. Depending on these definitions it is possible that Clinical Events fall outside the time spans defined by OBSERVATION_PERIOD records. Family history or history of Clinical Events generally are not used to generate OBSERVATION_PERIOD records around the time they are referring to. Any two overlapping or adjacent OBSERVATION_PERIOD records have to be merged into one.
4 visit_occurrence CDM No VISIT_ Yes 0 NA This table contains Events where Persons engage with the healthcare system for a duration of time. They are often also called "Encounters". Visits are defined by a configuration of circumstances under which they occur, such as (i) whether the patient comes to a healthcare institution, the other way around, or the interaction is remote, (ii) whether and what kind of trained medical staff is delivering the service during the Visit, and (iii) whether the Visit is transient or for a longer period involving a stay in bed. The configuration defining the Visit are described by Concepts in the Visit Domain, which form a hierarchical structure, but rolling up to generally familiar Visits adopted in most healthcare systems worldwide: - [Inpatient Visit](https://athena.ohdsi.org/search-terms/terms/9201): Person visiting hospital, at a Care Site, in bed, for duration of more than one day, with physicians and other Providers permanently available to deliver service around the clock - [Emergency Room Visit](https://athena.ohdsi.org/search-terms/terms/9203): Person visiting dedicated healthcare institution for treating emergencies, at a Care Site, within one day, with physicians and Providers permanently available to deliver service around the clock - [Emergency Room and Inpatient Visit](https://athena.ohdsi.org/search-terms/terms/262): Person visiting ER followed by a subsequent Inpatient Visit, where Emergency department is part of hospital, and transition from the ER to other hospital departments is undefined - [Non-hospital institution Visit](https://athena.ohdsi.org/search-terms/terms/42898160): Person visiting dedicated institution for reasons of poor health, at a Care Site, long-term or permanently, with no physician but possibly other Providers permanently available to deliver service around the clock - [Outpatient Visit](https://athena.ohdsi.org/search-terms/terms/9202): Person visiting dedicated ambulatory healthcare institution, at a Care Site, within one day, without bed, with physicians or medical Providers delivering service during Visit - [Home Visit](https://athena.ohdsi.org/search-terms/terms/581476): Provider visiting Person, without a Care Site, within one day, delivering service - [Telehealth Visit](https://athena.ohdsi.org/search-terms/terms/5083): Patient engages with Provider through communication media - [Pharmacy Visit](https://athena.ohdsi.org/search-terms/terms/581458): Person visiting pharmacy for dispensing of Drug, at a Care Site, within one day - [Laboratory Visit](https://athena.ohdsi.org/search-terms/terms/32036): Patient visiting dedicated institution, at a Care Site, within one day, for the purpose of a Measurement. - [Ambulance Visit](https://athena.ohdsi.org/search-terms/terms/581478): Person using transportation service for the purpose of initiating one of the other Visits, without a Care Site, within one day, potentially with Providers accompanying the Visit and delivering service - [Case Management Visit](https://athena.ohdsi.org/search-terms/terms/38004193): Person interacting with healthcare system, without a Care Site, within a day, with no Providers involved, for administrative purposes The Visit duration, or 'length of stay', is defined as VISIT_END_DATE - VISIT_START_DATE. For all Visits this is <1 day, except Inpatient Visits and Non-hospital institution Visits. The CDM also contains the VISIT_DETAIL table where additional information about the Visit is stored, for example, transfers between units during an inpatient Visit. Visits can be derived easily if the source data contain coding systems for Place of Service or Procedures, like CPT codes for well visits. In those cases, the codes can be looked up and mapped to a Standard Visit Concept. Otherwise, Visit Concepts have to be identified in the ETL process. This table will contain concepts in the Visit domain. These concepts are arranged in a hierarchical structure to facilitate cohort definitions by rolling up to generally familiar Visits adopted in most healthcare systems worldwide. Visits can be adjacent to each other, i.e. the end date of one can be identical with the start date of the other. As a consequence, more than one-day Visits or their descendants can be recorded for the same day. Multi-day visits must not overlap, i.e. share days other than start and end days. It is often the case that some logic should be written for how to define visits and how to assign Visit_Concept_Id. For example, in US claims outpatient visits that appear to occur within the time period of an inpatient visit can be rolled into one with the same Visit_Occurrence_Id. In EHR data inpatient visits that are within one day of each other may be strung together to create one visit. It will all depend on the source data and how encounter records should be translated to visit occurrences. Providers can be associated with a Visit through the PROVIDER_ID field, or indirectly through PROCEDURE_OCCURRENCE records linked both to the VISIT and PROVIDER tables.
5 visit_detail CDM No VISIT_DETAIL_ Yes 0 NA The VISIT_DETAIL table is an optional table used to represents details of each record in the parent VISIT_OCCURRENCE table. A good example of this would be the movement between units in a hospital during an inpatient stay or claim lines associated with a one insurance claim. For every record in the VISIT_OCCURRENCE table there may be 0 or more records in the VISIT_DETAIL table with a 1:n relationship where n may be 0. The VISIT_DETAIL table is structurally very similar to VISIT_OCCURRENCE table and belongs to the visit domain. The configuration defining the Visit Detail is described by Concepts in the Visit Domain, which form a hierarchical structure. The Visit Detail record will have an associated to the Visit Occurrence record in two ways: <br> 1. The Visit Detail record will have the VISIT_OCCURRENCE_ID it is associated to 2. The VISIT_DETAIL_CONCEPT_ID will be a descendant of the VISIT_CONCEPT_ID for the Visit. It is not mandatory that the VISIT_DETAIL table be filled in, but if you find that the logic to create VISIT_OCCURRENCE records includes the roll-up of multiple smaller records to create one picture of a Visit then it is a good idea to use VISIT_DETAIL. In EHR data, for example, a Person may be in the hospital but instead of one over-arching Visit their encounters are recorded as times they interacted with a health care provider. A Person in the hospital interacts with multiple providers multiple times a day so the encounters must be strung together using some heuristic (defined by the ETL) to identify the entire Visit. In this case the encounters would be considered Visit Details and the entire Visit would be the Visit Occurrence. In this example it is also possible to use the Vocabulary to distinguish Visit Details from a Visit Occurrence by setting the VISIT_CONCEPT_ID to [9201](https://athena.ohdsi.org/search-terms/terms/9201) and the VISIT_DETAIL_CONCEPT_IDs either to 9201 or its children to indicate where the patient was in the hospital at the time of care.
6 condition_occurrence CDM No CONDITION_ Yes 0 NA This table contains records of Events of a Person suggesting the presence of a disease or medical condition stated as a diagnosis, a sign, or a symptom, which is either observed by a Provider or reported by the patient. Conditions are defined by Concepts from the Condition domain, which form a complex hierarchy. As a result, the same Person with the same disease may have multiple Condition records, which belong to the same hierarchical family. Most Condition records are mapped from diagnostic codes, but recorded signs, symptoms and summary descriptions also contribute to this table. Rule out diagnoses should not be recorded in this table, but in reality their negating nature is not always captured in the source data, and other precautions must be taken when when identifying Persons who should suffer from the recorded Condition. Record all conditions as they exist in the source data. Any decisions about diagnosis/phenotype definitions would be done through cohort specifications. These cohorts can be housed in the [COHORT](https://ohdsi.github.io/CommonDataModel/cdm531.html#payer_plan_period) table. Conditions span a time interval from start to end, but are typically recorded as single snapshot records with no end date. The reason is twofold: (i) At the time of the recording the duration is not known and later not recorded, and (ii) the Persons typically cease interacting with the healthcare system when they feel better, which leads to incomplete capture of resolved Conditions. The [CONDITION_ERA](https://ohdsi.github.io/CommonDataModel/cdm531.html#condition_era) table addresses this issue. Family history and past diagnoses ('history of') are not recorded in this table. Instead, they are listed in the [OBSERVATION](https://ohdsi.github.io/CommonDataModel/cdm531.html#observation) table. Codes written in the process of establishing the diagnosis, such as 'question of' of and 'rule out', should not represented here. Instead, they should be recorded in the [OBSERVATION](https://ohdsi.github.io/CommonDataModel/cdm531.html#observation) table, if they are used for analyses. However, this information is not always available. Source codes and source text fields mapped to Standard Concepts of the Condition Domain have to be recorded here.

View File

@ -1,6 +1,6 @@
cdmTableName,schema,isRequired,conceptPrefix,measurePersonCompleteness,measurePersonCompletenessThreshold,validation,tableDescription,userGuidance,etlConventions
person,CDM,Yes,NA,No,NA,NA,"This table serves as the central identity management for all Persons in the database. It contains records that uniquely identify each person or patient, and some demographic information.",All records in this table are independent Persons.,"All Persons in a database needs one record in this table, unless they fail data quality requirements specified in the ETL. Persons with no Events should have a record nonetheless. If more than one data source contributes Events to the database, Persons must be reconciled, if possible, across the sources to create one single record per Person. The BIRTH_DATETIME must be equivalent to the content of BIRTH_DAY, BIRTH_MONTH and BIRTH_YEAR. There is a helpful rule listed in table below for how to derive BIRTH_DATETIME if it is not available in the source. **New to CDM v6.0** The person's death date is now stored in this table instead of the separate DEATH table. In the case that multiple dates of death are given in the source data the ETL should make a choice as to which death date to put in the PERSON table. Any additional dates can be stored in the OBSERVATION table using the concept [4265167](https://athena.ohdsi.org/search-terms/terms/4265167) which stands for 'Date of death' . Similarly, the cause of death is stored in the CONDITION_OCCURRENCE table using the CONDITION_STATUS_CONCEPT_ID [32891](https://athena.ohdsi.org/search-terms/terms/32891) for 'Cause of death'."
observation_period,CDM,Yes,NA,Yes,0,NA,"This table contains records which define spans of time during which two conditions are expected to hold: (i) Clinical Events that happened to the Person are recorded in the Event tables, and (ii) absense of records indicate such Events did not occur during this span of time.","For each Person, one or more OBSERVATION_PERIOD records may be present, but they will not overlap or be back to back to each other. Events may exist outside all of the time spans of the OBSERVATION_PERIOD records for a patient, however, absence of an Event outside these time spans cannot be construed as evidence of absence of an Event. Incidence or prevalence rates should only be calculated for the time of active OBSERVATION_PERIOD records. When constructing cohorts, outside Events can be used for inclusion criteria definition, but without any guarantee for the performance of these criteria. Also, OBSERVATION_PERIOD records can be as short as a single day, greatly disturbing the denominator of any rate calculation as part of cohort characterizations. To avoid that, apply minimal observation time as a requirement for any cohort definition.","Each Person needs to have at least one OBSERVATION_PERIOD record, which should represent time intervals with a high capture rate of Clinical Events. Some source data have very similar concepts, such as enrollment periods in insurance claims data. In other source data such as most EHR systems these time spans need to be inferred under a set of assumptions. It is the discretion of the ETL developer to define these assumptions. In many ETL solutions the start date of the first occurrence or the first high quality occurrence of a Clinical Event (Condition, Drug, Procedure, Device, Measurement, Visit) is defined as the start of the OBSERVATION_PERIOD record, and the end date of the last occurrence of last high quality occurrence of a Clinical Event, or the end of the database period becomes the end of the OBSERVATOIN_PERIOD for each Person. If a Person only has a single Clinical Event the OBSERVATION_PERIOD record can be as short as one day. Depending on these definitions it is possible that Clinical Events fall outside the time spans defined by OBSERVATION_PERIOD records. Family history or history of Clinical Events generally are not used to generate OBSERVATION_PERIOD records around the time they are referring to. Any two overlapping or adjacent OBSERVATION_PERIOD records have to be merged into one."
observation_period,CDM,Yes,NA,Yes,0,NA,"This table contains records which define spans of time during which two conditions are expected to hold: (i) Clinical Events that happened to the Person are recorded in the Event tables, and (ii) absence of records indicate such Events did not occur during this span of time.","For each Person, one or more OBSERVATION_PERIOD records may be present, but they will not overlap or be back to back to each other. Events may exist outside all of the time spans of the OBSERVATION_PERIOD records for a patient, however, absence of an Event outside these time spans cannot be construed as evidence of absence of an Event. Incidence or prevalence rates should only be calculated for the time of active OBSERVATION_PERIOD records. When constructing cohorts, outside Events can be used for inclusion criteria definition, but without any guarantee for the performance of these criteria. Also, OBSERVATION_PERIOD records can be as short as a single day, greatly disturbing the denominator of any rate calculation as part of cohort characterizations. To avoid that, apply minimal observation time as a requirement for any cohort definition.","Each Person needs to have at least one OBSERVATION_PERIOD record, which should represent time intervals with a high capture rate of Clinical Events. Some source data have very similar concepts, such as enrollment periods in insurance claims data. In other source data such as most EHR systems these time spans need to be inferred under a set of assumptions. It is the discretion of the ETL developer to define these assumptions. In many ETL solutions the start date of the first occurrence or the first high quality occurrence of a Clinical Event (Condition, Drug, Procedure, Device, Measurement, Visit) is defined as the start of the OBSERVATION_PERIOD record, and the end date of the last occurrence of last high quality occurrence of a Clinical Event, or the end of the database period becomes the end of the OBSERVATOIN_PERIOD for each Person. If a Person only has a single Clinical Event the OBSERVATION_PERIOD record can be as short as one day. Depending on these definitions it is possible that Clinical Events fall outside the time spans defined by OBSERVATION_PERIOD records. Family history or history of Clinical Events generally are not used to generate OBSERVATION_PERIOD records around the time they are referring to. Any two overlapping or adjacent OBSERVATION_PERIOD records have to be merged into one."
visit_occurrence,CDM,No,VISIT_,Yes,0,NA,"This table contains Events where Persons engage with the healthcare system for a duration of time. They are often also called ""Encounters"". Visits are defined by a configuration of circumstances under which they occur, such as (i) whether the patient comes to a healthcare institution, the other way around, or the interaction is remote, (ii) whether and what kind of trained medical staff is delivering the service during the Visit, and (iii) whether the Visit is transient or for a longer period involving a stay in bed.","The configuration defining the Visit are described by Concepts in the Visit Domain, which form a hierarchical structure, but rolling up to generally familiar Visits adopted in most healthcare systems worldwide:
- [Inpatient Visit](https://athena.ohdsi.org/search-terms/terms/9201): Person visiting hospital, at a Care Site, in bed, for duration of more than one day, with physicians and other Providers permanently available to deliver service around the clock

1 cdmTableName schema isRequired conceptPrefix measurePersonCompleteness measurePersonCompletenessThreshold validation tableDescription userGuidance etlConventions
2 person CDM Yes NA No NA NA This table serves as the central identity management for all Persons in the database. It contains records that uniquely identify each person or patient, and some demographic information. All records in this table are independent Persons. All Persons in a database needs one record in this table, unless they fail data quality requirements specified in the ETL. Persons with no Events should have a record nonetheless. If more than one data source contributes Events to the database, Persons must be reconciled, if possible, across the sources to create one single record per Person. The BIRTH_DATETIME must be equivalent to the content of BIRTH_DAY, BIRTH_MONTH and BIRTH_YEAR. There is a helpful rule listed in table below for how to derive BIRTH_DATETIME if it is not available in the source. **New to CDM v6.0** The person's death date is now stored in this table instead of the separate DEATH table. In the case that multiple dates of death are given in the source data the ETL should make a choice as to which death date to put in the PERSON table. Any additional dates can be stored in the OBSERVATION table using the concept [4265167](https://athena.ohdsi.org/search-terms/terms/4265167) which stands for 'Date of death' . Similarly, the cause of death is stored in the CONDITION_OCCURRENCE table using the CONDITION_STATUS_CONCEPT_ID [32891](https://athena.ohdsi.org/search-terms/terms/32891) for 'Cause of death'.
3 observation_period CDM Yes NA Yes 0 NA This table contains records which define spans of time during which two conditions are expected to hold: (i) Clinical Events that happened to the Person are recorded in the Event tables, and (ii) absense of records indicate such Events did not occur during this span of time. This table contains records which define spans of time during which two conditions are expected to hold: (i) Clinical Events that happened to the Person are recorded in the Event tables, and (ii) absence of records indicate such Events did not occur during this span of time. For each Person, one or more OBSERVATION_PERIOD records may be present, but they will not overlap or be back to back to each other. Events may exist outside all of the time spans of the OBSERVATION_PERIOD records for a patient, however, absence of an Event outside these time spans cannot be construed as evidence of absence of an Event. Incidence or prevalence rates should only be calculated for the time of active OBSERVATION_PERIOD records. When constructing cohorts, outside Events can be used for inclusion criteria definition, but without any guarantee for the performance of these criteria. Also, OBSERVATION_PERIOD records can be as short as a single day, greatly disturbing the denominator of any rate calculation as part of cohort characterizations. To avoid that, apply minimal observation time as a requirement for any cohort definition. Each Person needs to have at least one OBSERVATION_PERIOD record, which should represent time intervals with a high capture rate of Clinical Events. Some source data have very similar concepts, such as enrollment periods in insurance claims data. In other source data such as most EHR systems these time spans need to be inferred under a set of assumptions. It is the discretion of the ETL developer to define these assumptions. In many ETL solutions the start date of the first occurrence or the first high quality occurrence of a Clinical Event (Condition, Drug, Procedure, Device, Measurement, Visit) is defined as the start of the OBSERVATION_PERIOD record, and the end date of the last occurrence of last high quality occurrence of a Clinical Event, or the end of the database period becomes the end of the OBSERVATOIN_PERIOD for each Person. If a Person only has a single Clinical Event the OBSERVATION_PERIOD record can be as short as one day. Depending on these definitions it is possible that Clinical Events fall outside the time spans defined by OBSERVATION_PERIOD records. Family history or history of Clinical Events generally are not used to generate OBSERVATION_PERIOD records around the time they are referring to. Any two overlapping or adjacent OBSERVATION_PERIOD records have to be merged into one.
4 visit_occurrence CDM No VISIT_ Yes 0 NA This table contains Events where Persons engage with the healthcare system for a duration of time. They are often also called "Encounters". Visits are defined by a configuration of circumstances under which they occur, such as (i) whether the patient comes to a healthcare institution, the other way around, or the interaction is remote, (ii) whether and what kind of trained medical staff is delivering the service during the Visit, and (iii) whether the Visit is transient or for a longer period involving a stay in bed. The configuration defining the Visit are described by Concepts in the Visit Domain, which form a hierarchical structure, but rolling up to generally familiar Visits adopted in most healthcare systems worldwide: - [Inpatient Visit](https://athena.ohdsi.org/search-terms/terms/9201): Person visiting hospital, at a Care Site, in bed, for duration of more than one day, with physicians and other Providers permanently available to deliver service around the clock - [Emergency Room Visit](https://athena.ohdsi.org/search-terms/terms/9203): Person visiting dedicated healthcare institution for treating emergencies, at a Care Site, within one day, with physicians and Providers permanently available to deliver service around the clock - [Emergency Room and Inpatient Visit](https://athena.ohdsi.org/search-terms/terms/262): Person visiting ER followed by a subsequent Inpatient Visit, where Emergency department is part of hospital, and transition from the ER to other hospital departments is undefined - [Non-hospital institution Visit](https://athena.ohdsi.org/search-terms/terms/42898160): Person visiting dedicated institution for reasons of poor health, at a Care Site, long-term or permanently, with no physician but possibly other Providers permanently available to deliver service around the clock - [Outpatient Visit](https://athena.ohdsi.org/search-terms/terms/9202): Person visiting dedicated ambulatory healthcare institution, at a Care Site, within one day, without bed, with physicians or medical Providers delivering service during Visit - [Home Visit](https://athena.ohdsi.org/search-terms/terms/581476): Provider visiting Person, without a Care Site, within one day, delivering service - [Telehealth Visit](https://athena.ohdsi.org/search-terms/terms/5083): Patient engages with Provider through communication media - [Pharmacy Visit](https://athena.ohdsi.org/search-terms/terms/581458): Person visiting pharmacy for dispensing of Drug, at a Care Site, within one day - [Laboratory Visit](https://athena.ohdsi.org/search-terms/terms/32036): Patient visiting dedicated institution, at a Care Site, within one day, for the purpose of a Measurement. - [Ambulance Visit](https://athena.ohdsi.org/search-terms/terms/581478): Person using transportation service for the purpose of initiating one of the other Visits, without a Care Site, within one day, potentially with Providers accompanying the Visit and delivering service - [Case Management Visit](https://athena.ohdsi.org/search-terms/terms/38004193): Person interacting with healthcare system, without a Care Site, within a day, with no Providers involved, for administrative purposes The Visit duration, or 'length of stay', is defined as VISIT_END_DATE - VISIT_START_DATE. For all Visits this is <1 day, except Inpatient Visits and Non-hospital institution Visits. The CDM also contains the VISIT_DETAIL table where additional information about the Visit is stored, for example, transfers between units during an inpatient Visit. Visits can be derived easily if the source data contain coding systems for Place of Service or Procedures, like CPT codes for well visits. In those cases, the codes can be looked up and mapped to a Standard Visit Concept. Otherwise, Visit Concepts have to be identified in the ETL process. This table will contain concepts in the Visit domain. These concepts are arranged in a hierarchical structure to facilitate cohort definitions by rolling up to generally familiar Visits adopted in most healthcare systems worldwide. Visits can be adjacent to each other, i.e. the end date of one can be identical with the start date of the other. As a consequence, more than one-day Visits or their descendants can be recorded for the same day. Multi-day visits must not overlap, i.e. share days other than start and end days. It is often the case that some logic should be written for how to define visits and how to assign Visit_Concept_Id. For example, in US claims outpatient visits that appear to occur within the time period of an inpatient visit can be rolled into one with the same Visit_Occurrence_Id. In EHR data inpatient visits that are within one day of each other may be strung together to create one visit. It will all depend on the source data and how encounter records should be translated to visit occurrences. Providers can be associated with a Visit through the PROVIDER_ID field, or indirectly through PROCEDURE_OCCURRENCE records linked both to the VISIT and PROVIDER tables.
5 visit_detail CDM No VISIT_DETAIL_ Yes 0 NA The VISIT_DETAIL table is an optional table used to represents details of each record in the parent VISIT_OCCURRENCE table. A good example of this would be the movement between units in a hospital during an inpatient stay or claim lines associated with a one insurance claim. For every record in the VISIT_OCCURRENCE table there may be 0 or more records in the VISIT_DETAIL table with a 1:n relationship where n may be 0. The VISIT_DETAIL table is structurally very similar to VISIT_OCCURRENCE table and belongs to the visit domain. The configuration defining the Visit Detail is described by Concepts in the Visit Domain, which form a hierarchical structure. The Visit Detail record will have an associated to the Visit Occurrence record in two ways: <br> 1. The Visit Detail record will have the VISIT_OCCURRENCE_ID it is associated to 2. The VISIT_DETAIL_CONCEPT_ID will be a descendant of the VISIT_CONCEPT_ID for the Visit. It is not mandatory that the VISIT_DETAIL table be filled in, but if you find that the logic to create VISIT_OCCURRENCE records includes the roll-up of multiple smaller records to create one picture of a Visit then it is a good idea to use VISIT_DETAIL. In EHR data, for example, a Person may be in the hospital but instead of one over-arching Visit their encounters are recorded as times they interacted with a health care provider. A Person in the hospital interacts with multiple providers multiple times a day so the encounters must be strung together using some heuristic (defined by the ETL) to identify the entire Visit. In this case the encounters would be considered Visit Details and the entire Visit would be the Visit Occurrence. In this example it is also possible to use the Vocabulary to distinguish Visit Details from a Visit Occurrence by setting the VISIT_CONCEPT_ID to [9201](https://athena.ohdsi.org/search-terms/terms/9201) and the VISIT_DETAIL_CONCEPT_IDs either to 9201 or its children to indicate where the patient was in the hospital at the time of care.
6 condition_occurrence CDM No CONDITION_ Yes 0 NA This table contains records of Events of a Person suggesting the presence of a disease or medical condition stated as a diagnosis, a sign, or a symptom, which is either observed by a Provider or reported by the patient. Conditions are defined by Concepts from the Condition domain, which form a complex hierarchy. As a result, the same Person with the same disease may have multiple Condition records, which belong to the same hierarchical family. Most Condition records are mapped from diagnostic codes, but recorded signs, symptoms and summary descriptions also contribute to this table. Rule out diagnoses should not be recorded in this table, but in reality their negating nature is not always captured in the source data, and other precautions must be taken when when identifying Persons who should suffer from the recorded Condition. Record all conditions as they exist in the source data. Any decisions about diagnosis/phenotype definitions would be done through cohort specifications. These cohorts can be housed in the [COHORT](https://ohdsi.github.io/CommonDataModel/cdm531.html#payer_plan_period) table. Conditions span a time interval from start to end, but are typically recorded as single snapshot records with no end date. The reason is twofold: (i) At the time of the recording the duration is not known and later not recorded, and (ii) the Persons typically cease interacting with the healthcare system when they feel better, which leads to incomplete capture of resolved Conditions. The [CONDITION_ERA](https://ohdsi.github.io/CommonDataModel/cdm531.html#condition_era) table addresses this issue. Family history and past diagnoses ('history of') are not recorded in this table. Instead, they are listed in the [OBSERVATION](https://ohdsi.github.io/CommonDataModel/cdm531.html#observation) table. Codes written in the process of establishing the diagnosis, such as 'question of' of and 'rule out', should not represented here. Instead, they should be recorded in the [OBSERVATION](https://ohdsi.github.io/CommonDataModel/cdm531.html#observation) table, if they are used for analyses. However, this information is not always available. Source codes and source text fields mapped to Standard Concepts of the Condition Domain have to be recorded here.

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@ -22,9 +22,9 @@ Subfolders will be created for each cdmVersion and targetDialect.}
}
\value{
Writes DDL, ForeignKey, PrimaryKey and index SQL files for given cdmVersion
and targetDialect to the 'ddl' folder in specifed output folder.
and targetDialect to the 'ddl' folder in specified output folder.
}
\description{
Writes DDL, ForeignKey, PrimaryKey and index SQL files for given cdmVersion
and targetDialect to the 'ddl' folder in specifed output folder.
and targetDialect to the 'ddl' folder in specified output folder.
}

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@ -12,7 +12,7 @@ The goal is to inform ETL developers, tooling developers and CDM extensions.
- For ETL developers it helps to have guidance on which fields to prioritise in the mapping. Most value will be gained from populating fields support across the OHDSI tooling.
- For OHDSI tooling developers, this page provides insight in the gaps of support and can drive future development efforts.
- For CDM extenstions, it helps to known what it means for an OMOP CDM table/field to be part of the standard. In other words: what OHDSI tooling do we at least expect to support the new extensions?
- For CDM extensions, it helps to known what it means for an OMOP CDM table/field to be part of the standard. In other words: what OHDSI tooling do we at least expect to support the new extensions?
Currently four OHDSI tools have been evaluated: DataQualityDashboard, Achilles, Atlas (Data Sources and Cohort creation) and Feature Extraction.
@ -30,7 +30,7 @@ General criteria:
- `r emoji::emoji("exclamation")` if field is used by the tool, but not in a meaningful way. e.g. `provider_id` in Achilles only checked for a valid foreign key to the provider table.
# Tooling Support for OMOP fields
**Abbrevations** | &nbsp;
**Abbreviations** | &nbsp;
--- | ---
**PK** | Primary Key
**SV** | Source Value (for data quality / etl validation)