|
cohort : Entity
|
|
RESULT SCHEMA TABLE
|
|
care_site : Entity
|
|
CARE_SITE
Table Description
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.).
ETL Conventions
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.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
care_site_id
|
|
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.
|
integer
|
Yes
|
Yes
|
No
|
|
|
care_site_name
|
The name of the care_site as it appears in the source data
|
|
varchar(255)
|
No
|
No
|
No
|
|
|
place_of_service_concept_id
|
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.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
location_id
|
The location_id from the LOCATION table representing the physical
location of the care_site.
|
|
integer
|
No
|
No
|
Yes
|
LOCATION
|
|
care_site_source_value
|
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.
|
|
varchar(50)
|
No
|
No
|
No
|
|
|
place_of_service_source_value
|
|
Put the place of service of the care_site as it appears in the
source data.
|
varchar(50)
|
No
|
No
|
No
|
|
|
|
|
cdm_source : Entity
|
|
|
|
cohort_definition : Entity
|
|
RESULT SCHEMA TABLE
|
|
concept : Entity
|
|
CONCEPT
Table Description
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.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
concept_id
|
A unique identifier for each Concept across all domains.
|
|
integer
|
Yes
|
Yes
|
No
|
|
|
concept_name
|
An unambiguous, meaningful and descriptive name for the Concept.
|
|
varchar(255)
|
Yes
|
No
|
No
|
|
|
domain_id
|
A foreign key to the DOMAIN table
the Concept belongs to.
|
|
varchar(20)
|
Yes
|
No
|
Yes
|
DOMAIN
|
|
vocabulary_id
|
A foreign key to the VOCABULARY table
indicating from which source the Concept has been adapted.
|
|
varchar(20)
|
Yes
|
No
|
Yes
|
VOCABULARY
|
|
concept_class_id
|
The attribute or concept class of the Concept. Examples are
‘Clinical Drug’, ‘Ingredient’, ‘Clinical Finding’ etc.
|
|
varchar(20)
|
Yes
|
No
|
Yes
|
CONCEPT_CLASS
|
|
standard_concept
|
This flag determines where a Concept is a Standard Concept,
i.e. is used in the data, a Classification Concept, or a
non-standard Source Concept. The allowable values are ‘S’
(Standard Concept) and ‘C’ (Classification Concept), otherwise the
content is NULL.
|
|
varchar(1)
|
No
|
No
|
No
|
|
|
concept_code
|
The concept code represents the identifier of the Concept in the
source vocabulary, such as SNOMED-CT concept IDs, RxNorm RXCUIs
etc. Note that concept codes are not unique across vocabularies.
|
|
varchar(50)
|
Yes
|
No
|
No
|
|
|
valid_start_date
|
The date when the Concept was first recorded. The default value is
1-Jan-1970, meaning, the Concept has no (known) date of inception.
|
|
date
|
Yes
|
No
|
No
|
|
|
valid_end_date
|
The date when the Concept became invalid because it was deleted or
superseded (updated) by a new concept. The default value is
31-Dec-2099, meaning, the Concept is valid until it becomes
deprecated.
|
|
date
|
Yes
|
No
|
No
|
|
|
invalid_reason
|
Reason the Concept was invalidated. Possible values are D
(deleted), U (replaced with an update) or NULL when valid_end_date
has the default value.
|
|
varchar(1)
|
No
|
No
|
No
|
|
|
|
|
concept_ancestor : Entity
|
|
CONCEPT_ANCESTOR
Table Description
The CONCEPT_ANCESTOR table is designed to simplify observational
analysis by providing the complete hierarchical relationships between
Concepts. Only direct parent-child relationships between Concepts are
stored in the CONCEPT_RELATIONSHIP table. To determine higher level
ancestry connections, all individual direct relationships would have
to be navigated at analysis time. The CONCEPT_ANCESTOR table includes
records for all parent-child relationships, as well as
grandparent-grandchild relationships and those of any other level of
lineage. Using the CONCEPT_ANCESTOR table allows for querying for all
descendants of a hierarchical concept. For example, drug ingredients
and drug products are all descendants of a drug class ancestor.
This table is entirely derived from the CONCEPT, CONCEPT_RELATIONSHIP
and RELATIONSHIP tables.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
ancestor_concept_id
|
The Concept Id for the higher-level concept that forms the
ancestor in the relationship.
|
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
|
descendant_concept_id
|
The Concept Id for the lower-level concept that forms the
descendant in the relationship.
|
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
|
min_levels_of_separation
|
The minimum separation in number of levels of hierarchy between
ancestor and descendant concepts. This is an attribute that is
used to simplify hierarchic analysis.
|
|
integer
|
Yes
|
No
|
No
|
|
|
max_levels_of_separation
|
The maximum separation in number of levels of hierarchy between
ancestor and descendant concepts. This is an attribute that is
used to simplify hierarchic analysis.
|
|
integer
|
Yes
|
No
|
No
|
|
|
|
|
concept_class : Entity
|
|
CONCEPT_CLASS
Table Description
The CONCEPT_CLASS table is a reference table, which includes a list of
the classifications used to differentiate Concepts within a given
Vocabulary. This reference table is populated with a single record for
each Concept Class.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
concept_class_id
|
A unique key for each class.
|
|
varchar(20)
|
Yes
|
Yes
|
No
|
|
|
concept_class_name
|
The name describing the Concept Class, e.g. Clinical Finding,
Ingredient, etc.
|
|
varchar(255)
|
Yes
|
No
|
No
|
|
|
concept_class_concept_id
|
A Concept that represents the Concept Class.
|
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
|
|
|
concept_relationship : Entity
|
|
CONCEPT_RELATIONSHIP
Table Description
The CONCEPT_RELATIONSHIP table contains records that define direct
relationships between any two Concepts and the nature or type of the
relationship. Each type of a relationship is defined in the
RELATIONSHIP table.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
concept_id_1
|
|
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
|
concept_id_2
|
|
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
|
relationship_id
|
The relationship between CONCEPT_ID_1 and CONCEPT_ID_2. Please see
the Vocabulary
Conventions. for more information.
|
|
varchar(20)
|
Yes
|
No
|
Yes
|
RELATIONSHIP
|
|
valid_start_date
|
The date when the relationship is first recorded.
|
|
date
|
Yes
|
No
|
No
|
|
|
valid_end_date
|
The date when the relationship is invalidated.
|
|
date
|
Yes
|
No
|
No
|
|
|
invalid_reason
|
Reason the relationship was invalidated. Possible values are ‘D’
(deleted), ‘U’ (updated) or NULL.
|
|
varchar(1)
|
No
|
No
|
No
|
|
|
|
|
concept_synonym : Entity
|
|
CONCEPT_SYNONYM
Table Description
The CONCEPT_SYNONYM table is used to store alternate names and
descriptions for Concepts.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
concept_id
|
|
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
|
concept_synonym_name
|
|
|
varchar(1000)
|
Yes
|
No
|
No
|
|
|
language_concept_id
|
|
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
|
|
|
condition_era : Entity
|
|
CONDITION_ERA
Table Description
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. 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.
ETL Conventions
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 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.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
condition_era_id
|
|
|
integer
|
Yes
|
Yes
|
No
|
|
|
person_id
|
|
|
integer
|
Yes
|
No
|
Yes
|
PERSON
|
|
condition_concept_id
|
The Concept Id representing the Condition.
|
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
Condition
|
condition_era_start_date
|
The start date for the Condition Era constructed from the
individual instances of Condition Occurrences. It is the start
date of the very first chronologically recorded instance of the
condition with at least 31 days since any prior record of the same
Condition.
|
|
date
|
Yes
|
No
|
No
|
|
|
condition_era_end_date
|
The end date for the Condition Era constructed from the individual
instances of Condition Occurrences. It is the end date of the
final continuously recorded instance of the Condition.
|
|
date
|
Yes
|
No
|
No
|
|
|
condition_occurrence_count
|
The number of individual Condition Occurrences used to construct
the condition era.
|
|
integer
|
No
|
No
|
No
|
|
|
|
|
condition_occurrence : Entity
|
|
CONDITION_OCCURRENCE
Table Description
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.
User Guide
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 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 table
addresses this issue. Family history and past diagnoses (‘history of’)
are not recorded in this table. Instead, they are listed in the 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 table,
if they are used for analyses. However, this information is not always
available.
ETL Conventions
Source codes and source text fields mapped to Standard Concepts of the
Condition Domain have to be recorded here.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
condition_occurrence_id
|
The unique key given to a condition record for a person. Refer to
the ETL for how duplicate conditions during the same visit were
handled.
|
Each instance of a condition present in the source data should be
assigned this unique key. In some cases, a person can have
multiple records of the same condition within the same visit. It
is valid to keep these duplicates and assign them individual,
unique, CONDITION_OCCURRENCE_IDs, though it is up to the ETL how
they should be handled.
|
integer
|
Yes
|
Yes
|
No
|
|
|
person_id
|
The PERSON_ID of the PERSON for whom the condition is recorded.
|
|
integer
|
Yes
|
No
|
Yes
|
PERSON
|
|
condition_concept_id
|
The CONDITION_CONCEPT_ID field is recommended for primary use in
analyses, and must be used for network studies. This is the
standard concept mapped from the source value which represents a
condition
|
The CONCEPT_ID that the CONDITION_SOURCE_VALUE maps to. Only
records whose source values map to concepts with a domain of
“Condition” should go in this table. Accepted
Concepts.
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
Condition
|
condition_start_date
|
Use this date to determine the start date of the condition
|
Most often data sources do not have the idea of a start date for a
condition. Rather, if a source only has one date associated with a
condition record it is acceptable to use that date for both the
CONDITION_START_DATE and the CONDITION_END_DATE.
|
date
|
Yes
|
No
|
No
|
|
|
condition_start_datetime
|
|
If a source does not specify datetime the convention is to set the
time to midnight (00:00:0000)
|
datetime
|
No
|
No
|
No
|
|
|
condition_end_date
|
Use this date to determine the end date of the condition
|
Most often data sources do not have the idea of a start date for a
condition. Rather, if a source only has one date associated with a
condition record it is acceptable to use that date for both the
CONDITION_START_DATE and the CONDITION_END_DATE.
|
date
|
No
|
No
|
No
|
|
|
condition_end_datetime
|
|
If a source does not specify datetime the convention is to set the
time to midnight (00:00:0000)
|
datetime
|
No
|
No
|
No
|
|
|
condition_type_concept_id
|
This field can be used to determine the provenance of the
Condition record, as in whether the condition was from an EHR
system, insurance claim, registry, or other sources.
|
Choose the CONDITION_TYPE_CONCEPT_ID that best represents the
provenance of the record. Accepted
Concepts. A more detailed explanation of each Type
Concept can be found on the vocabulary
wiki.
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
Type Concept
|
condition_status_concept_id
|
This concept represents the point during the visit the diagnosis
was given (admitting diagnosis, final diagnosis), whether the
diagnosis was determined due to laboratory findings, if the
diagnosis was exclusionary, or if it was a preliminary diagnosis,
among others.
|
Choose the Concept in the Condition Status domain that best
represents the point during the visit when the diagnosis was
given. These can include admitting diagnosis, principal diagnosis,
and secondary diagnosis. Accepted
Concepts.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
Condition Status
|
stop_reason
|
The Stop Reason indicates why a Condition is no longer valid with
respect to the purpose within the source data. Note that a Stop
Reason does not necessarily imply that the condition is no longer
occurring.
|
This information is often not populated in source data and it is a
valid etl choice to leave it blank if the information does not
exist.
|
varchar(20)
|
No
|
No
|
No
|
|
|
provider_id
|
The provider associated with condition record, e.g. the provider
who made the diagnosis or the provider who recorded the symptom.
|
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.
|
integer
|
No
|
No
|
Yes
|
PROVIDER
|
|
visit_occurrence_id
|
The visit during which the condition occurred.
|
Depending on the structure of the source data, this may have to be
determined based on dates. If a CONDITION_START_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
CONDITION_OCCURRENCE record.
|
integer
|
No
|
No
|
Yes
|
VISIT_OCCURRENCE
|
|
visit_detail_id
|
The VISIT_DETAIL record during which the condition occurred. For
example, if the person was in the ICU at the time of the diagnosis
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.
|
integer
|
No
|
No
|
Yes
|
VISIT_DETAIL
|
|
condition_source_value
|
This field houses the verbatim value from the source data
representing the condition that occurred. For example, this could
be an ICD10 or Read code.
|
This code is mapped to a Standard Condition Concept in the
Standardized Vocabularies and the original code is stored here for
reference.
|
varchar(50)
|
No
|
No
|
No
|
|
|
condition_source_concept_id
|
This is the concept representing the condition 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 Condition necessary for a given analytic use
case. Consider using CONDITION_CONCEPT_ID instead to enable
standardized analytics that can be consistent across the network.
|
If the CONDITION_SOURCE_VALUE is coded in the source data using an
OMOP supported vocabulary put the concept id representing the
source value here.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
condition_status_source_value
|
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.
|
varchar(50)
|
No
|
No
|
No
|
|
|
|
|
cost : Entity
|
|
COST
Table Description
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.
User Guide
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.
ETL Conventions
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).
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
cost_id
|
|
|
integer
|
Yes
|
Yes
|
No
|
|
|
cost_event_id
|
|
|
integer
|
Yes
|
No
|
No
|
|
|
cost_domain_id
|
|
|
varchar(20)
|
Yes
|
No
|
Yes
|
DOMAIN
|
|
cost_type_concept_id
|
|
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
|
currency_concept_id
|
|
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
total_charge
|
|
|
float
|
No
|
No
|
No
|
|
|
total_cost
|
|
|
float
|
No
|
No
|
No
|
|
|
total_paid
|
|
|
float
|
No
|
No
|
No
|
|
|
paid_by_payer
|
|
|
float
|
No
|
No
|
No
|
|
|
paid_by_patient
|
|
|
float
|
No
|
No
|
No
|
|
|
paid_patient_copay
|
|
|
float
|
No
|
No
|
No
|
|
|
paid_patient_coinsurance
|
|
|
float
|
No
|
No
|
No
|
|
|
paid_patient_deductible
|
|
|
float
|
No
|
No
|
No
|
|
|
paid_by_primary
|
|
|
float
|
No
|
No
|
No
|
|
|
paid_ingredient_cost
|
|
|
float
|
No
|
No
|
No
|
|
|
paid_dispensing_fee
|
|
|
float
|
No
|
No
|
No
|
|
|
payer_plan_period_id
|
|
|
integer
|
No
|
No
|
No
|
|
|
amount_allowed
|
|
|
float
|
No
|
No
|
No
|
|
|
revenue_code_concept_id
|
|
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
revenue_code_source_value
|
Revenue codes are a method to charge for a class of procedures
and conditions in the U.S. hospital system.
|
|
varchar(50)
|
No
|
No
|
No
|
|
|
drg_concept_id
|
|
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
drg_source_value
|
Diagnosis Related Groups are US codes used to classify hospital
cases into one of approximately 500 groups.
|
|
varchar(3)
|
No
|
No
|
No
|
|
|
|
|
death : Entity
|
|
DEATH
Table Description
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.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
person_id
|
|
|
integer
|
Yes
|
No
|
Yes
|
PERSON
|
|
death_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.
|
date
|
Yes
|
No
|
No
|
|
|
death_datetime
|
|
If not available set time to midnight (00:00:00)
|
datetime
|
No
|
No
|
No
|
|
|
death_type_concept_id
|
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. A more detailed explanation of each Type
Concept can be found on the vocabulary
wiki.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
Type Concept
|
cause_concept_id
|
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.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
cause_source_value
|
|
If available, put the source code representing the cause of death
here.
|
varchar(50)
|
No
|
No
|
No
|
|
|
cause_source_concept_id
|
|
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.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
|
|
device_exposure : Entity
|
|
DEVICE_EXPOSURE
Table Description
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).
User Guide
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.
ETL Conventions
Source codes and source text fields mapped to Standard Concepts of the
Device Domain have to be recorded here.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
device_exposure_id
|
The unique key given to records a person’s exposure to a foreign
physical object or instrument.
|
Each instance of an exposure to a foreign object or device present
in the source data should be assigned this unique key.
|
integer
|
Yes
|
Yes
|
No
|
|
|
person_id
|
|
|
integer
|
Yes
|
No
|
Yes
|
PERSON
|
|
device_concept_id
|
The DEVICE_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 foreign object or instrument the person was exposed
to.
|
The CONCEPT_ID that the DEVICE_SOURCE_VALUE maps to.
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
Device
|
device_exposure_start_date
|
Use this date to determine the start date of the device record.
|
Valid entries include a start date of a procedure to implant a
device, the date of a prescription for a device, or the date of
device administration.
|
date
|
Yes
|
No
|
No
|
|
|
device_exposure_start_datetime
|
|
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)
|
datetime
|
No
|
No
|
No
|
|
|
device_exposure_end_date
|
The DEVICE_EXPOSURE_END_DATE denotes the day the device exposure
ended for the patient, if given.
|
Put the end date or discontinuation date as it appears from the
source data or leave blank if unavailable.
|
date
|
No
|
No
|
No
|
|
|
device_exposure_end_datetime
|
|
If a source does not specify datetime the convention is to set the
time to midnight (00:00:0000)
|
datetime
|
No
|
No
|
No
|
|
|
device_type_concept_id
|
You can use the TYPE_CONCEPT_ID to denote the provenance of the
record, as in whether the record is from administrative claims or
EHR.
|
Choose the drug_type_concept_id that best represents the
provenance of the record, for example whether it came from a
record of a prescription written or physician administered drug. Accepted
Concepts. A more detailed explanation of each Type
Concept can be found on the vocabulary
wiki.
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
Type Concept
|
unique_device_id
|
This is the Unique Device Identification (UDI-DI) number for
devices regulated by the FDA, if given.
|
For medical devices that are regulated by the FDA, a Unique Device
Identification (UDI) is provided if available in the data source
and is recorded in the UNIQUE_DEVICE_ID field.
|
varchar(255)
|
No
|
No
|
No
|
|
|
production_id
|
This is the Production Identifier (UDI-PI) portion of the Unique
Device Identification.
|
|
varchar(255)
|
No
|
No
|
No
|
|
|
quantity
|
|
|
integer
|
No
|
No
|
No
|
|
|
provider_id
|
The Provider associated with device record, e.g. the provider who
wrote the prescription or the provider who implanted the device.
|
The ETL may need to make a choice as to which PROVIDER_ID to put
here. Based on what is available this may or may not be different
than the provider associated with the overall VISIT_OCCURRENCE
record.
|
integer
|
No
|
No
|
Yes
|
PROVIDER
|
|
visit_occurrence_id
|
The Visit during which the device was prescribed or given.
|
To populate this field device exposures must be explicitly
initiated in the visit.
|
integer
|
No
|
No
|
Yes
|
VISIT_OCCURRENCE
|
|
visit_detail_id
|
The Visit Detail during which the device was prescribed or given.
|
To populate this field device exposures must be explicitly
initiated in the visit detail record.
|
integer
|
No
|
No
|
Yes
|
VISIT_DETAIL
|
|
device_source_value
|
This field houses the verbatim value from the source data
representing the device exposure that occurred. For example, this
could be an NDC or Gemscript code.
|
This code is mapped to a Standard Device Concept in the
Standardized Vocabularies and the original code is stored here for
reference.
|
varchar(50)
|
No
|
No
|
No
|
|
|
device_source_concept_id
|
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.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
unit_concept_id
|
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
DEVICE_CONCEPT_IDs, however, it is the responsibility of the ETL
to choose the most plausible unit. If there is no unit associated
with a Device record, set to NULL.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
Unit
|
unit_source_value
|
This field houses the verbatim value from the source data
representing the unit of the Device. For example, blood
transfusions are considered devices and can be given in mL
quantities.
|
This code is mapped to a Standard Condition Concept in the
Standardized Vocabularies and the original code is stored here for
reference. Using the blood transfusion example, blood transfusion
is represented by the DEVICE_CONCEPT_ID and the unit (mL) would be
housed in the UNIT_SOURCE_VALUE and mapped to a standard concept
in the unit domain.
|
varchar(50)
|
No
|
No
|
No
|
|
|
unit_source_concept_id
|
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.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
|
|
domain : Entity
|
|
DOMAIN
Table Description
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.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
domain_id
|
A unique key for each domain.
|
|
varchar(20)
|
Yes
|
Yes
|
No
|
|
|
domain_name
|
The name describing the Domain, e.g. Condition, Procedure,
Measurement etc.
|
|
varchar(255)
|
Yes
|
No
|
No
|
|
|
domain_concept_id
|
A Concept representing the Domain Concept the DOMAIN record
belongs to.
|
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
|
|
|
dose_era : Entity
|
|
DOSE_ERA
Table Description
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.
ETL Conventions
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.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
dose_era_id
|
|
|
integer
|
Yes
|
Yes
|
No
|
|
|
person_id
|
|
|
integer
|
Yes
|
No
|
Yes
|
PERSON
|
|
drug_concept_id
|
The Concept Id representing the specific drug ingredient.
|
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
Drug
|
unit_concept_id
|
The Concept Id representing the unit of the specific drug
ingredient.
|
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
Unit
|
dose_value
|
The numeric value of the dosage of the drug_ingredient.
|
|
float
|
Yes
|
No
|
No
|
|
|
dose_era_start_date
|
The date the Person started on the specific dosage, with at least
31 days since any prior exposure.
|
|
date
|
Yes
|
No
|
No
|
|
|
dose_era_end_date
|
|
The date the Person was no longer exposed to the dosage of the
specific drug ingredient. An era is ended if there are 31 days or
more between dosage records.
|
date
|
Yes
|
No
|
No
|
|
|
|
|
drug_era : Entity
|
|
DRUG_ERA
Table Description
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.
ETL Conventions
The SQL script for generating DRUG_ERA records can be found here.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
drug_era_id
|
|
|
integer
|
Yes
|
Yes
|
No
|
|
|
person_id
|
|
|
integer
|
Yes
|
No
|
Yes
|
PERSON
|
|
drug_concept_id
|
The Concept Id representing the specific drug ingredient.
|
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
Drug
|
drug_era_start_date
|
|
The Drug Era Start Date is the start date of the first Drug
Exposure for a given ingredient, with at least 31 days since the
previous exposure.
|
date
|
Yes
|
No
|
No
|
|
|
drug_era_end_date
|
|
The Drug Era End Date is the end date of the last Drug Exposure.
The End Date of each Drug Exposure is either taken from the field
drug_exposure_end_date or, as it is typically not available,
inferred using the following rules: For pharmacy prescription
data, the date when the drug was dispensed plus the number of days
of supply are used to extrapolate the End Date for the Drug
Exposure. Depending on the country-specific healthcare system,
this supply information is either explicitly provided in the
day_supply field or inferred from package size or similar
information. For Procedure Drugs, usually the drug is administered
on a single date (i.e., the administration date). A standard
Persistence Window of 30 days (gap, slack) is permitted between
two subsequent such extrapolated DRUG_EXPOSURE records to be
considered to be merged into a single Drug Era.
|
date
|
Yes
|
No
|
No
|
|
|
drug_exposure_count
|
|
|
integer
|
No
|
No
|
No
|
|
|
gap_days
|
|
The Gap Days determine how many total drug-free days are observed
between all Drug Exposure events that contribute to a DRUG_ERA
record. It is assumed that the drugs are “not stockpiled” by the
patient, i.e. that if a new drug prescription or refill is
observed (a new DRUG_EXPOSURE record is written), the remaining
supply from the previous events is abandoned. The difference
between Persistence Window and Gap Days is that the former is the
maximum drug-free time allowed between two subsequent
DRUG_EXPOSURE records, while the latter is the sum of actual
drug-free days for the given Drug Era under the above assumption
of non-stockpiling.
|
integer
|
No
|
No
|
No
|
|
|
|
|
drug_exposure : Entity
|
|
DRUG_EXPOSURE
Table Description
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.
User Guide
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.
ETL Conventions
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.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
drug_exposure_id
|
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.
|
integer
|
Yes
|
Yes
|
No
|
|
|
person_id
|
The PERSON_ID of the PERSON for whom the drug dispensing or
administration is recorded. This may be a system generated code.
|
|
integer
|
Yes
|
No
|
Yes
|
PERSON
|
|
drug_concept_id
|
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.
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
Drug
|
drug_exposure_start_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.
|
date
|
Yes
|
No
|
No
|
|
|
drug_exposure_start_datetime
|
|
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)
|
datetime
|
No
|
No
|
No
|
|
|
drug_exposure_end_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:
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
|
date
|
Yes
|
No
|
No
|
|
|
drug_exposure_end_datetime
|
|
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)
|
datetime
|
No
|
No
|
No
|
|
|
verbatim_end_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.
|
date
|
No
|
No
|
No
|
|
|
drug_type_concept_id
|
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. A more detailed explanation of each Type
Concept can be found on the vocabulary
wiki.
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
Type Concept
|
stop_reason
|
The reason a person stopped a medication as it is represented in
the source. Reasons include regimen completed, changed, removed,
etc. This field will be retired in v6.0.
|
This information is often not populated in source data and it is a
valid etl choice to leave it blank if the information does not
exist.
|
varchar(20)
|
No
|
No
|
No
|
|
|
refills
|
This is only filled in when the record is coming from a
prescription written this field is meant to represent intended
refills at time of the prescription.
|
|
integer
|
No
|
No
|
No
|
|
|
quantity
|
|
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 for more
information.
|
float
|
No
|
No
|
No
|
|
|
days_supply
|
|
Days supply of the drug. This should be the verbatim days_supply
as given on the prescription. If the drug is physician
administered use duration end date if given or set to 1 as default
if duration is not available.
|
integer
|
No
|
No
|
No
|
|
|
sig
|
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.
|
varchar(MAX)
|
No
|
No
|
No
|
|
|
route_concept_id
|
|
The standard CONCEPT_ID that the ROUTE_SOURCE_VALUE maps to in the
route domain.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
Route
|
lot_number
|
|
|
varchar(50)
|
No
|
No
|
No
|
|
|
provider_id
|
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.
|
integer
|
No
|
No
|
Yes
|
PROVIDER
|
|
visit_occurrence_id
|
The Visit during which the drug was prescribed, administered or
dispensed.
|
To populate this field drug exposures must be explicitly initiated
in the visit.
|
integer
|
No
|
No
|
Yes
|
VISIT_OCCURRENCE
|
|
visit_detail_id
|
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.
|
integer
|
No
|
No
|
Yes
|
VISIT_DETAIL
|
|
drug_source_value
|
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.
|
varchar(50)
|
No
|
No
|
No
|
|
|
drug_source_concept_id
|
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.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
route_source_value
|
This field houses the verbatim value from the source data
representing the drug route.
|
This information may be called something different in the source
data but the field is meant to contain a value indicating when and
how a drug was given to a patient. This source value is mapped to
a standard concept which is stored in the ROUTE_CONCEPT_ID field.
|
varchar(50)
|
No
|
No
|
No
|
|
|
dose_unit_source_value
|
This field houses the verbatim value from the source data
representing the dose unit of the drug given.
|
This information may be called something different in the source
data but the field is meant to contain a value indicating the unit
of dosage of drug given to the patient. This
is an older column and will be deprecated in an upcoming version.
|
varchar(50)
|
No
|
No
|
No
|
|
|
|
|
drug_strength : Entity
|
|
DRUG_STRENGTH
Table Description
The DRUG_STRENGTH table contains structured content about the amount
or concentration and associated units of a specific ingredient
contained within a particular drug product. This table is supplemental
information to support standardized analysis of drug utilization.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
drug_concept_id
|
The Concept representing the Branded Drug or Clinical Drug Product.
|
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
|
ingredient_concept_id
|
The Concept representing the active ingredient contained within
the drug product.
|
Combination Drugs will have more than one record in this table,
one for each active Ingredient.
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
|
amount_value
|
The numeric value or the amount of active ingredient contained
within the drug product.
|
|
float
|
No
|
No
|
No
|
|
|
amount_unit_concept_id
|
The Concept representing the Unit of measure for the amount of
active ingredient contained within the drug product.
|
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
numerator_value
|
The concentration of the active ingredient contained within the
drug product.
|
|
float
|
No
|
No
|
No
|
|
|
numerator_unit_concept_id
|
The Concept representing the Unit of measure for the concentration
of active ingredient.
|
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
denominator_value
|
The amount of total liquid (or other divisible product, such as
ointment, gel, spray, etc.).
|
|
float
|
No
|
No
|
No
|
|
|
denominator_unit_concept_id
|
The Concept representing the denominator unit for the
concentration of active ingredient.
|
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
box_size
|
The number of units of Clinical Branded Drug or Quantified
Clinical or Branded Drug contained in a box as dispensed to the
patient.
|
|
integer
|
No
|
No
|
No
|
|
|
valid_start_date
|
The date when the Concept was first recorded. The default value is
1-Jan-1970.
|
|
date
|
Yes
|
No
|
No
|
|
|
valid_end_date
|
The date when then Concept became invalid.
|
|
date
|
Yes
|
No
|
No
|
|
|
invalid_reason
|
Reason the concept was invalidated. Possible values are D
(deleted), U (replaced with an update) or NULL when valid_end_date
has the default value.
|
|
varchar(1)
|
No
|
No
|
No
|
|
|
|
|
episode : Entity
|
|
EPISODE
Table Description
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.
User Guide
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.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
episode_id
|
A unique identifier for each Episode.
|
|
integer
|
Yes
|
Yes
|
No
|
|
|
person_id
|
The PERSON_ID of the PERSON for whom the episode is recorded.
|
|
integer
|
Yes
|
No
|
Yes
|
PERSON
|
|
episode_concept_id
|
The EPISODE_CONCEPT_ID represents the kind abstraction related to
the disease phase, outcome or treatment.
|
Choose a concept in the Episode domain that best represents the
ongoing disease phase, outcome, or treatment. Please see [article]
for cancers and [article] for non-cancers describing how these are
defined. Accepted
Concepts
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
Episode
|
episode_start_date
|
The date when the Episode beings.
|
Please see [article] for how to define an Episode start date.
|
date
|
Yes
|
No
|
No
|
|
|
episode_start_datetime
|
The date and time when the Episode begins.
|
|
datetime
|
No
|
No
|
No
|
|
|
episode_end_date
|
The date when the instance of the Episode is considered to have
ended.
|
Please see [article] for how to define an Episode end date.
|
date
|
No
|
No
|
No
|
|
|
episode_end_datetime
|
The date when the instance of the Episode is considered to have
ended.
|
|
datetime
|
No
|
No
|
No
|
|
|
episode_parent_id
|
Use this field to find the Episode that subsumes the given Episode
record. This is used in the case that an Episode are nested into
each other.
|
If there are multiple nested levels to how Episodes are
represented, the EPISODE_PARENT_ID can be used to record this
relationship.
|
integer
|
No
|
No
|
No
|
|
|
episode_number
|
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.
|
integer
|
No
|
No
|
No
|
|
|
episode_object_concept_id
|
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 then the
EPISODE_OBJECT_CONCEPT_ID should contain the chemotherapy regimen
concept, like Afatinib
monotherapy.
|
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.
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
Procedure, Regimen
|
episode_type_concept_id
|
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. A more detailed explanation of each Type
Concept can be found on the vocabulary
wiki.
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
Type Concept
|
episode_source_value
|
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.
|
|
varchar(50)
|
No
|
No
|
No
|
|
|
episode_source_concept_id
|
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.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
|
|
episode_event : Entity
|
|
EPISODE_EVENT
Table Description
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.
User Guide
This connecting table is used instead of the FACT_RELATIONSHIP table
for linking low-level events to abstracted Episodes.
ETL Conventions
Some episodes may not have links to any underlying clinical events.
For such episodes, the EPISODE_EVENT table is not populated.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
episode_id
|
Use this field to link the EPISODE_EVENT record to its EPISODE.
|
Put the EPISODE_ID that subsumes the EPISODE_EVENT record here.
|
integer
|
Yes
|
No
|
Yes
|
EPISODE
|
|
event_id
|
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.
|
integer
|
Yes
|
No
|
No
|
|
|
episode_event_field_concept_id
|
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
EVENT_ID came from. Accepted
Concepts
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
Metadata
|
|
|
fact_relationship : Entity
|
|
FACT_RELATIONSHIP
Table Description
The FACT_RELATIONSHIP table contains records about the relationships
between facts stored as records in any table of the CDM.
Relationships can be defined between facts from the same domain, or
different domains. Examples of Fact Relationships include: Person
relationships (parent-child), care site
relationships (hierarchical organizational structure of facilities
within a health system), indication relationship (between drug
exposures and associated conditions), usage relationships (of
devices during the course of an associated procedure), or facts
derived from one another (measurements derived from an associated
specimen).
ETL Conventions
All relationships are directional, and each relationship is
represented twice symmetrically within the FACT_RELATIONSHIP table.
For example, two persons if person_id = 1 is the mother of person_id
= 2 two records are in the FACT_RELATIONSHIP table (all strings in
fact concept_id records in the Concept table: - Person, 1, Person,
2, parent of - Person, 2, Person, 1, child of
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
domain_concept_id_1
|
|
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
|
fact_id_1
|
|
|
integer
|
Yes
|
No
|
No
|
|
|
domain_concept_id_2
|
|
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
|
fact_id_2
|
|
|
integer
|
Yes
|
No
|
No
|
|
|
relationship_concept_id
|
|
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
|
|
|
location : Entity
|
|
LOCATION
Table Description
The LOCATION table represents a generic way to capture physical
location or address information of Persons and Care Sites.
User Guide
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.
- STATE can also be used for
province or district - ZIP is also the postal code or postcode -
COUNTY can also be used to represent region
ETL Conventions
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.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
location_id
|
The unique key given to a unique Location.
|
Each instance of a Location in the source data should be assigned
this unique key.
|
integer
|
Yes
|
Yes
|
No
|
|
|
address_1
|
This is the first line of the address.
|
|
varchar(50)
|
No
|
No
|
No
|
|
|
address_2
|
This is the second line of the address
|
|
varchar(50)
|
No
|
No
|
No
|
|
|
city
|
|
|
varchar(50)
|
No
|
No
|
No
|
|
|
state
|
|
|
varchar(2)
|
No
|
No
|
No
|
|
|
zip
|
|
Zip codes are handled as strings of up to 9 characters length. For
US addresses, these represent either a 3-digit abbreviated Zip
code as provided by many sources for patient protection reasons,
the full 5-digit Zip or the 9-digit (ZIP + 4) codes. Unless for
specific reasons analytical methods should expect and utilize only
the first 3 digits. For international addresses, different rules
apply.
|
varchar(9)
|
No
|
No
|
No
|
|
|
county
|
|
|
varchar(20)
|
No
|
No
|
No
|
|
|
location_source_value
|
|
Put the verbatim value for the location here, as it shows up in
the source.
|
varchar(50)
|
No
|
No
|
No
|
|
|
country_concept_id
|
The Concept Id representing the country. Values should conform to
the Geography domain.
|
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
country_source_value
|
The name of the country.
|
|
varchar(80)
|
No
|
No
|
No
|
|
|
latitude
|
|
Must be between -90 and 90.
|
float
|
No
|
No
|
No
|
|
|
longitude
|
|
Must be between -180 and 180.
|
float
|
No
|
No
|
No
|
|
|
|
|
measurement : Entity
|
|
MEASUREMENT
Table Description
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.
User Guide
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.).
ETL Conventions
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 ‘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 ‘Enzyme
measurement’ as well as a ‘Maps to value’ record to 4135493 ‘Abnormal’.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
measurement_id
|
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.
|
integer
|
Yes
|
Yes
|
No
|
|
|
person_id
|
The PERSON_ID of the Person for whom the Measurement is recorded.
This may be a system generated code.
|
|
integer
|
Yes
|
No
|
Yes
|
PERSON
|
|
measurement_concept_id
|
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.
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
Measurement
|
measurement_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.
|
date
|
Yes
|
No
|
No
|
|
|
measurement_datetime
|
|
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)
|
datetime
|
No
|
No
|
No
|
|
|
measurement_time
|
|
This is present for backwards compatibility and will be deprecated
in an upcoming version.
|
varchar(10)
|
No
|
No
|
No
|
|
|
measurement_type_concept_id
|
This field can be used to determine the provenance of the
Measurement record, as in whether the measurement was from an EHR
system, insurance claim, registry, or other sources.
|
Choose the MEASUREMENT_TYPE_CONCEPT_ID that best represents the
provenance of the record, for example whether it came from an EHR
record or billing claim. Accepted
Concepts. A more detailed explanation of each Type
Concept can be found on the vocabulary
wiki.
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
Type Concept
|
operator_concept_id
|
The meaning of Concept 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.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
value_as_number
|
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): - 1925-7 Base
excess in Arterial blood by calculation - 1927-3 Base
excess in Venous blood by calculation - 8632-2 QRS-Axis
- 11555-0 Base
excess in Blood by calculation - 1926-5 Base
excess in Capillary blood by calculation - 28638-5 Base
excess in Arterial cord blood by calculation 28639-3 Base
excess in Venous cord blood by calculation
|
float
|
No
|
No
|
No
|
|
|
value_as_concept_id
|
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.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
unit_concept_id
|
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.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
Unit
|
range_low
|
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.
|
float
|
No
|
No
|
No
|
|
|
range_high
|
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.
|
float
|
No
|
No
|
No
|
|
|
provider_id
|
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.
|
integer
|
No
|
No
|
Yes
|
PROVIDER
|
|
visit_occurrence_id
|
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.
|
integer
|
No
|
No
|
Yes
|
VISIT_OCCURRENCE
|
|
visit_detail_id
|
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.
|
integer
|
No
|
No
|
Yes
|
VISIT_DETAIL
|
|
measurement_source_value
|
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.
|
varchar(50)
|
No
|
No
|
No
|
|
|
measurement_source_concept_id
|
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.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
unit_source_value
|
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.
|
varchar(50)
|
No
|
No
|
No
|
|
|
unit_source_concept_id
|
“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.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
value_source_value
|
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.
|
varchar(50)
|
No
|
No
|
No
|
|
|
measurement_event_id
|
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.
|
integer
|
No
|
No
|
No
|
|
|
meas_event_field_concept_id
|
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.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
|
|
metadata : Entity
|
|
|
|
note : Entity
|
|
NOTE
Table Description
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.
ETL Conventions
HL7/LOINC CDO is a standard for consistent naming of documents to
support a range of use cases: retrieval, organization, display, and
exchange. It guides the creation of LOINC codes for clinical notes.
CDO annotates each document with 5 dimensions:
-
Kind of Document:
Characterizes the general structure of the document at a macro level
(e.g. Anesthesia Consent)
-
Type of Service:
Characterizes the kind of service or activity (e.g. evaluations,
consultations, and summaries). The notion of time sequence, e.g., at
the beginning (admission) at the end (discharge) is subsumed in this
axis. Example: Discharge Teaching.
-
Setting: Setting
is an extension of CMS’s definitions (e.g. Inpatient, Outpatient)
-
Subject Matter Domain (SMD):
Characterizes the subject matter domain of a note
(e.g. Anesthesiology)
-
Role:
Characterizes the training or professional level of the author of
the document, but does not break down to specialty or subspecialty
(e.g. Physician) Each combination of these 5 dimensions rolls up to
a unique LOINC code.
According to CDO requirements, only 2 of the 5 dimensions are required
to properly annotate a document; Kind of Document and any one of the
other 4 dimensions. However, not all the permutations of the CDO
dimensions will necessarily yield an existing LOINC code. Each of
these dimensions are contained in the OMOP Vocabulary under the domain
of ‘Meas Value’ with each dimension represented as a Concept Class.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
note_id
|
A unique identifier for each note.
|
|
integer
|
Yes
|
Yes
|
No
|
|
|
person_id
|
|
|
integer
|
Yes
|
No
|
Yes
|
PERSON
|
|
note_date
|
The date the note was recorded.
|
|
date
|
Yes
|
No
|
No
|
|
|
note_datetime
|
|
If time is not given set the time to midnight.
|
datetime
|
No
|
No
|
No
|
|
|
note_type_concept_id
|
The provenance of the note. Most likely this will be EHR.
|
Put the source system of the note, as in EHR record. Accepted
Concepts. A more detailed explanation of each Type
Concept can be found on the vocabulary
wiki.
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
Type Concept
|
note_class_concept_id
|
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. This Concept can alternatively be
represented by concepts with the relationship ‘Kind of (LOINC)’ to 706391 (Note).
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
|
note_title
|
The title of the note.
|
|
varchar(250)
|
No
|
No
|
No
|
|
|
note_text
|
The content of the note.
|
|
varchar(MAX)
|
Yes
|
No
|
No
|
|
|
encoding_concept_id
|
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).
It the note is encoded in any other type, like ASCII then put 0.
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
|
language_concept_id
|
The language of the note.
|
Use Concepts that are descendants of the concept 4182347 (World
Languages).
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
|
provider_id
|
The Provider who wrote the note.
|
The ETL may need to make a determination on which provider to put
here.
|
integer
|
No
|
No
|
Yes
|
PROVIDER
|
|
visit_occurrence_id
|
The Visit during which the note was written.
|
|
integer
|
No
|
No
|
Yes
|
VISIT_OCCURRENCE
|
|
visit_detail_id
|
The Visit Detail during which the note was written.
|
|
integer
|
No
|
No
|
Yes
|
VISIT_DETAIL
|
|
note_source_value
|
|
The source value mapped to the NOTE_CLASS_CONCEPT_ID.
|
varchar(50)
|
No
|
No
|
No
|
|
|
note_event_id
|
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.
|
integer
|
No
|
No
|
No
|
|
|
note_event_field_concept_id
|
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.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
|
|
note_nlp : Entity
|
|
NOTE_NLP
Table Description
The NOTE_NLP table encodes all output of NLP on clinical notes. Each
row represents a single extracted term from a note.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
note_nlp_id
|
A unique identifier for the NLP record.
|
|
integer
|
Yes
|
Yes
|
No
|
|
|
note_id
|
This is the NOTE_ID for the NOTE record the NLP record is
associated to.
|
|
integer
|
Yes
|
No
|
No
|
|
|
section_concept_id
|
|
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.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
snippet
|
A small window of text surrounding the term
|
|
varchar(250)
|
No
|
No
|
No
|
|
|
“offset”
|
Character offset of the extracted term in the input note
|
|
varchar(50)
|
No
|
No
|
No
|
|
|
lexical_variant
|
Raw text extracted from the NLP tool.
|
|
varchar(250)
|
Yes
|
No
|
No
|
|
|
note_nlp_concept_id
|
|
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
note_nlp_source_concept_id
|
|
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
nlp_system
|
|
Name and version of the NLP system that extracted the term. Useful
for data provenance.
|
varchar(250)
|
No
|
No
|
No
|
|
|
nlp_date
|
The date of the note processing.
|
|
date
|
Yes
|
No
|
No
|
|
|
nlp_datetime
|
The date and time of the note processing.
|
|
datetime
|
No
|
No
|
No
|
|
|
term_exists
|
|
Term_exists is defined as a flag that indicates if the patient
actually has or had the condition. Any of the following modifiers
would make Term_exists false: Negation = true Subject = [anything
other than the patient] Conditional = true/li> Rule_out = true
Uncertain = very low certainty or any lower certainties A complete
lack of modifiers would make Term_exists true.
|
varchar(1)
|
No
|
No
|
No
|
|
|
term_temporal
|
|
Term_temporal is to indicate if a condition is present or just in
the past. The following would be past:
- History = true -
Concept_date = anything before the time of the report
|
varchar(50)
|
No
|
No
|
No
|
|
|
term_modifiers
|
|
For the modifiers that are there, they would have to have these
values:
- Negation = false - Subject = patient -
Conditional = false - Rule_out = false - Uncertain = true or high
or moderate or even low (could argue about low). Term_modifiers
will concatenate all modifiers for different types of entities
(conditions, drugs, labs etc) into one string. Lab values will be
saved as one of the modifiers.
|
varchar(2000)
|
No
|
No
|
No
|
|
|
|
|
observation : Entity
|
|
OBSERVATION
Table Description
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.
User Guide
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.
ETL Conventions
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.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
observation_id
|
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.
|
integer
|
Yes
|
Yes
|
No
|
|
|
person_id
|
The PERSON_ID of the Person for whom the Observation is recorded.
This may be a system generated code.
|
|
integer
|
Yes
|
No
|
Yes
|
PERSON
|
|
observation_concept_id
|
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.
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
|
observation_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.
|
date
|
Yes
|
No
|
No
|
|
|
observation_datetime
|
|
If no time is given set to midnight (00:00:00).
|
datetime
|
No
|
No
|
No
|
|
|
observation_type_concept_id
|
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. A more detailed explanation of each Type
Concept can be found on the vocabulary
wiki.
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
Type Concept
|
value_as_number
|
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.
|
|
float
|
No
|
No
|
No
|
|
|
value_as_string
|
This is the categorical value of the Result of the Observation, if
applicable and available.
|
|
varchar(60)
|
No
|
No
|
No
|
|
|
value_as_concept_id
|
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 ‘Family
history of ischaemic heart disease and other diseases of the
circulatory system’ has a ‘Maps to’ relationship to 4167217 ‘Family
history of clinical finding’ as well as a ‘Maps to value’ record to 134057 ‘Disorder
of cardiovascular system’.
|
Integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
qualifier_concept_id
|
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.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
unit_concept_id
|
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.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
Unit
|
provider_id
|
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.
|
integer
|
No
|
No
|
Yes
|
PROVIDER
|
|
visit_occurrence_id
|
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.
|
integer
|
No
|
No
|
Yes
|
VISIT_OCCURRENCE
|
|
visit_detail_id
|
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.
|
integer
|
No
|
No
|
Yes
|
VISIT_DETAIL
|
|
observation_source_value
|
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.
|
varchar(50)
|
No
|
No
|
No
|
|
|
observation_source_concept_id
|
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.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
unit_source_value
|
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.
|
varchar(50)
|
No
|
No
|
No
|
|
|
qualifier_source_value
|
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.
|
varchar(50)
|
No
|
No
|
No
|
|
|
value_source_value
|
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.
|
varchar(50)
|
No
|
No
|
No
|
|
|
observation_event_id
|
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 table
for more details.
|
integer
|
No
|
No
|
No
|
|
|
obs_event_field_concept_id
|
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.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
|
|
observation_period : Entity
|
|
OBSERVATION_PERIOD
Table Description
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.
User Guide
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.
ETL Conventions
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.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
observation_period_id
|
A Person can have multiple discrete Observation Periods which are
identified by the Observation_Period_Id.
|
Assign a unique observation_period_id to each discrete Observation
Period for a Person.
|
integer
|
Yes
|
Yes
|
No
|
|
|
person_id
|
The Person ID of the PERSON record for which the Observation
Period is recorded.
|
|
integer
|
Yes
|
No
|
Yes
|
PERSON
|
|
observation_period_start_date
|
Use this date to determine the start date of the Observation
Period.
|
It is often the case that the idea of Observation Periods does not
exist in source data. In those cases, the
observation_period_start_date can be inferred as the earliest
Event date available for the Person. In insurance claim data, the
Observation Period can be considered as the time period the Person
is enrolled with a payer. If a Person switches plans but stays
with the same payer, and therefore capturing of data continues,
that change would be captured in PAYER_PLAN_PERIOD.
|
date
|
Yes
|
No
|
No
|
|
|
observation_period_end_date
|
Use this date to determine the end date of the period for which we
can assume that all events for a Person are recorded.
|
It is often the case that the idea of Observation Periods does not
exist in source data. In those cases, the
observation_period_end_date can be inferred as the last Event date
available for the Person. In insurance claim data, the Observation
Period can be considered as the time period the Person is enrolled
with a payer.
|
date
|
Yes
|
No
|
No
|
|
|
period_type_concept_id
|
This field can be used to determine the provenance of the
Observation Period as in whether the period was determined from an
insurance enrollment file, EHR healthcare encounters, or other
sources.
|
Choose the observation_period_type_concept_id that best represents
how the period was determined. Accepted
Concepts. A more detailed explanation of each Type
Concept can be found on the vocabulary
wiki.
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
Type Concept
|
|
|
payer_plan_period : Entity
|
|
PAYER_PLAN_PERIOD
Table Description
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.
User Guide
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.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
payer_plan_period_id
|
A unique identifier for each unique combination of a Person,
Payer, Plan, and Period of time.
|
|
integer
|
Yes
|
Yes
|
No
|
|
|
person_id
|
The Person covered by the Plan.
|
A single Person can have multiple, overlapping, PAYER_PLAN_PERIOD
records
|
integer
|
Yes
|
No
|
Yes
|
PERSON
|
|
payer_plan_period_start_date
|
Start date of Plan coverage.
|
|
date
|
Yes
|
No
|
No
|
|
|
payer_plan_period_end_date
|
End date of Plan coverage.
|
|
date
|
Yes
|
No
|
No
|
|
|
payer_concept_id
|
This field represents the organization who reimburses the provider
which administers care to the Person.
|
Map the Payer 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 payer, though the name of the Payer is not necessary. Accepted
Concepts.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
payer_source_value
|
This is the Payer as it appears in the source data.
|
|
varchar(50)
|
No
|
No
|
No
|
|
|
payer_source_concept_id
|
|
If the source data codes the Payer in an OMOP supported vocabulary
store the concept_id here.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
plan_concept_id
|
This field represents the specific health benefit Plan the Person
is enrolled in.
|
Map the Plan 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 health benefit Plan though the name of the Plan is not
necessary. Accepted
Concepts.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
plan_source_value
|
This is the health benefit Plan of the Person as it appears in the
source data.
|
|
varchar(50)
|
No
|
No
|
No
|
|
|
plan_source_concept_id
|
|
If the source data codes the Plan in an OMOP supported vocabulary
store the concept_id here.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
sponsor_concept_id
|
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.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
sponsor_source_value
|
The Plan sponsor as it appears in the source data.
|
|
varchar(50)
|
No
|
No
|
No
|
|
|
sponsor_source_concept_id
|
|
If the source data codes the sponsor in an OMOP supported
vocabulary store the concept_id here.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
family_source_value
|
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.
|
varchar(50)
|
No
|
No
|
No
|
|
|
stop_reason_concept_id
|
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.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
stop_reason_source_value
|
The Plan stop reason as it appears in the source data.
|
|
varchar(50)
|
No
|
No
|
No
|
|
|
stop_reason_source_concept_id
|
|
If the source data codes the stop reason in an OMOP supported
vocabulary store the concept_id here.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
|
|
person : Entity
|
|
PERSON
Table Description
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.
User Guide
All records in this table are independent Persons.
ETL Conventions
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.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
person_id
|
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.
|
integer
|
Yes
|
Yes
|
No
|
|
|
gender_concept_id
|
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 table. Accepted
gender concepts
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
Gender
|
year_of_birth
|
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.
|
integer
|
Yes
|
No
|
No
|
|
|
month_of_birth
|
|
For data sources that provide the precise date of birth, the month
should be extracted and stored in this field.
|
integer
|
No
|
No
|
No
|
|
|
day_of_birth
|
|
For data sources that provide the precise date of birth, the day
should be extracted and stored in this field.
|
integer
|
No
|
No
|
No
|
|
|
birth_datetime
|
|
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).
|
datetime
|
No
|
No
|
No
|
|
|
race_concept_id
|
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.
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
Race
|
ethnicity_concept_id
|
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
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
Ethnicity
|
location_id
|
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 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.
|
integer
|
No
|
No
|
Yes
|
LOCATION
|
|
provider_id
|
The Provider refers to the last known primary care provider
(General Practitioner).
|
Put the provider_id from the 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.
|
integer
|
No
|
No
|
Yes
|
PROVIDER
|
|
care_site_id
|
The Care Site refers to where the Provider typically provides the
primary care.
|
|
integer
|
No
|
No
|
Yes
|
CARE_SITE
|
|
person_source_value
|
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.
|
varchar(50)
|
No
|
No
|
No
|
|
|
gender_source_value
|
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.
|
varchar(50)
|
No
|
No
|
No
|
|
|
gender_source_concept_id
|
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.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
race_source_value
|
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.
|
varchar(50)
|
No
|
No
|
No
|
|
|
race_source_concept_id
|
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.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
ethnicity_source_value
|
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.
|
varchar(50)
|
No
|
No
|
No
|
|
|
ethnicity_source_concept_id
|
Due to the small number of options, this tends to be zero.
|
If the source data codes ethnicity in an OMOP supported
vocabulary, store the concept_id here.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
|
|
procedure_occurrence : Entity
|
|
PROCEDURE_OCCURRENCE
Table Description
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.
User Guide
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.
ETL Conventions
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.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
procedure_occurrence_id
|
The unique key given to a procedure record for a person. Refer to
the ETL for how duplicate procedures during the same visit were
handled.
|
Each instance of a procedure occurrence in the source data should
be assigned this unique key. In some cases, a person can have
multiple records of the same procedure within the same visit. It
is valid to keep these duplicates and assign them individual,
unique, PROCEDURE_OCCURRENCE_IDs, though it is up to the ETL how
they should be handled.
|
integer
|
Yes
|
Yes
|
No
|
|
|
person_id
|
The PERSON_ID of the PERSON for whom the procedure is recorded.
This may be a system generated code.
|
|
integer
|
Yes
|
No
|
Yes
|
PERSON
|
|
procedure_concept_id
|
The PROCEDURE_CONCEPT_ID field is recommended for primary use in
analyses, and must be used for network studies. This is the
standard concept mapped from the source value which represents a
procedure
|
The CONCEPT_ID that the PROCEDURE_SOURCE_VALUE maps to. Only
records whose source values map to standard concepts with a domain
of “Procedure” should go in this table. Accepted
Concepts.
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
Procedure
|
procedure_date
|
Use this date to determine the date the procedure started.
|
This is meant to be the start
date of the procedure. It will be
renamed in a future version to PROCEDURE_START_DATE.
|
date
|
Yes
|
No
|
No
|
|
|
procedure_datetime
|
|
If the procedure has a start time in the native date, use this
field to house that information. This will be renamed in a future
version to PROCEDURE_START_DATETIME.
|
datetime
|
No
|
No
|
No
|
|
|
procedure_end_date
|
Use this field to house the date that the procedure ended.
|
This is meant to be the end date of the procedure. It is not
required and for most cases will be the same as the
PROCEDURE_START_DATE.
|
date
|
No
|
No
|
No
|
|
|
procedure_end_datetime
|
Use this field to house the datetime that the procedure ended.
|
This is meant to house the end datetime of the procedure and will
most often be used in conjunction with the
procedure_start_datetime to determine the length of the procedure.
|
datetime
|
No
|
No
|
No
|
|
|
procedure_type_concept_id
|
This field can be used to determine the provenance of the
Procedure record, as in whether the procedure was from an EHR
system, insurance claim, registry, or other sources.
|
Choose the PROCEDURE_TYPE_CONCEPT_ID that best represents the
provenance of the record, for example whether it came from an EHR
record or billing claim. If a procedure is recorded as an EHR
encounter, the PROCEDURE_TYPE_CONCEPT would be ‘EHR encounter
record’. Accepted
Concepts. A more detailed explanation of each Type
Concept can be found on the vocabulary
wiki.
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
Type Concept
|
modifier_concept_id
|
The modifiers are intended to give additional information about
the procedure but as of now the vocabulary is under review.
|
It is up to the ETL to choose how to map modifiers if they exist
in source data. These concepts are typically distinguished by
‘Modifier’ concept classes (e.g., ‘CPT4 Modifier’ as part of the
‘CPT4’ vocabulary). If there is more than one modifier on a
record, one should be chosen that pertains to the procedure rather
than provider. Accepted
Concepts.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
quantity
|
If the quantity value is omitted, a single procedure is assumed.
|
If a Procedure has a quantity of ‘0’ in the source, this should
default to ‘1’ in the ETL. If there is a record in the source it
can be assumed the exposure occurred at least once
|
integer
|
No
|
No
|
No
|
|
|
provider_id
|
The provider associated with the procedure record, e.g. the
provider who performed the Procedure.
|
The ETL may need to make a choice as to which PROVIDER_ID to put
here. Based on what is available this may or may not be different
than the provider associated with the overall VISIT_OCCURRENCE
record, for example the admitting vs attending physician on an EHR
record.
|
integer
|
No
|
No
|
Yes
|
PROVIDER
|
|
visit_occurrence_id
|
The visit during which the procedure occurred.
|
Depending on the structure of the source data, this may have to be
determined based on dates. If a PROCEDURE_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
PROCEDURE_OCCURRENCE record.
|
integer
|
No
|
No
|
Yes
|
VISIT_OCCURRENCE
|
|
visit_detail_id
|
The VISIT_DETAIL record during which the Procedure occurred. For
example, if the Person was in the ICU at the time of the Procedure
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.
|
integer
|
No
|
No
|
Yes
|
VISIT_DETAIL
|
|
procedure_source_value
|
This field houses the verbatim value from the source data
representing the procedure that occurred. For example, this could
be an CPT4 or OPCS4 code.
|
Use this value to look up the source concept id and then map the
source concept id to a standard concept id.
|
varchar(50)
|
No
|
No
|
No
|
|
|
procedure_source_concept_id
|
This is the concept representing the procedure 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 Procedure necessary for a given analytic use
case. Consider using PROCEDURE_CONCEPT_ID instead to enable
standardized analytics that can be consistent across the network.
|
If the PROCEDURE_SOURCE_VALUE is coded in the source data using an
OMOP supported vocabulary put the concept id representing the
source value here.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
modifier_source_value
|
|
The original modifier code from the source is stored here for
reference.
|
varchar(50)
|
No
|
No
|
No
|
|
|
|
|
provider : Entity
|
|
PROVIDER
Table Description
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.
User Guide
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.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
provider_id
|
It is assumed that every provider with a different unique
identifier is in fact a different person and should be treated
independently.
|
This identifier can be the original id from the source data
provided it is an integer, otherwise it can be an autogenerated
number.
|
integer
|
Yes
|
Yes
|
No
|
|
|
provider_name
|
|
This field is not necessary as it is not necessary to have the
actual identity of the Provider. Rather, the idea is to uniquely
and anonymously identify providers of care across the database.
|
varchar(255)
|
No
|
No
|
No
|
|
|
npi
|
This is the National Provider Number issued to health care
providers in the US by the Centers for Medicare and Medicaid
Services (CMS).
|
|
varchar(20)
|
No
|
No
|
No
|
|
|
dea
|
This is the identifier issued by the DEA, a US federal agency,
that allows a provider to write prescriptions for controlled
substances.
|
|
varchar(20)
|
No
|
No
|
No
|
|
|
specialty_concept_id
|
This field either represents the most common specialty that
occurs in the data or the most specific concept that represents
all specialties listed, should the provider have more than one.
This includes physician specialties such as internal medicine,
emergency medicine, etc. and allied health professionals such as
nurses, midwives, and pharmacists.
|
If a Provider has more than one Specialty, there are two
options: 1. Choose a concept_id which is a common ancestor to
the multiple specialties, or, 2. Choose the specialty that
occurs most often for the provider. Concepts in this field
should be Standard with a domain of Provider. Accepted
Concepts.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
care_site_id
|
This is the CARE_SITE_ID for the location that the provider
primarily practices in.
|
If a Provider has more than one Care Site, the main or most
often exerted CARE_SITE_ID should be recorded.
|
integer
|
No
|
No
|
Yes
|
CARE_SITE
|
|
year_of_birth
|
|
|
integer
|
No
|
No
|
No
|
|
|
gender_concept_id
|
This field represents the recorded gender of the provider in the
source data.
|
If given, put a concept from the gender domain representing the
recorded gender of the provider. Accepted
Concepts.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
Gender
|
provider_source_value
|
Use this field to link back to providers in the source data.
This is typically used for error checking of ETL logic.
|
Some use cases require the ability to link back to providers in
the source data. This field allows for the storing of the
provider identifier as it appears in the source.
|
varchar(50)
|
No
|
No
|
No
|
|
|
specialty_source_value
|
This is the kind of provider or specialty as it appears in the
source data. This includes physician specialties such as
internal medicine, emergency medicine, etc. and allied health
professionals such as nurses, midwives, and pharmacists.
|
Put the kind of provider as it appears in the source data. This
field is up to the discretion of the ETL-er as to whether this
should be the coded value from the source or the text
description of the lookup value.
|
varchar(50)
|
No
|
No
|
No
|
|
|
specialty_source_concept_id
|
This is often zero as many sites use proprietary codes to store
physician speciality.
|
If the source data codes provider specialty in an OMOP supported
vocabulary store the concept_id here.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
gender_source_value
|
This is provider’s gender as it appears in the source data.
|
Put the provider’s gender as it appears in the source data. This
field is up to the discretion of the ETL-er as to whether this
should be the coded value from the source or the text
description of the lookup value.
|
varchar(50)
|
No
|
No
|
No
|
|
|
gender_source_concept_id
|
This is often zero as many sites use proprietary codes to store
provider gender.
|
If the source data codes provider gender in an OMOP supported
vocabulary store the concept_id here.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
|
|
relationship : Entity
|
|
RELATIONSHIP
Table Description
The RELATIONSHIP table provides a reference list of all types of
relationships that can be used to associate any two concepts in the
CONCEPT_RELATIONSHP table.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
relationship_id
|
The type of relationship captured by the relationship record.
|
|
varchar(20)
|
Yes
|
Yes
|
No
|
|
|
relationship_name
|
|
|
varchar(255)
|
Yes
|
No
|
No
|
|
|
is_hierarchical
|
Defines whether a relationship defines concepts into classes or
hierarchies. Values are 1 for hierarchical relationship or 0 if
not.
|
|
varchar(1)
|
Yes
|
No
|
No
|
|
|
defines_ancestry
|
Defines whether a hierarchical relationship contributes to the
concept_ancestor table. These are subsets of the hierarchical
relationships. Valid values are 1 or 0.
|
|
varchar(1)
|
Yes
|
No
|
No
|
|
|
reverse_relationship_id
|
The identifier for the relationship used to define the reverse
relationship between two concepts.
|
|
varchar(20)
|
Yes
|
No
|
No
|
|
|
relationship_concept_id
|
A foreign key that refers to an identifier in the CONCEPT table
for the unique relationship concept.
|
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
|
|
|
source_to_concept_map : Entity
|
|
SOURCE_TO_CONCEPT_MAP
Table Description
The source to concept map table is a legacy data structure within the
OMOP Common Data Model, recommended for use in ETL processes to
maintain local source codes which are not available as Concepts in the
Standardized Vocabularies, and to establish mappings for each source
code into a Standard Concept as target_concept_ids that can be used to
populate the Common Data Model tables. The SOURCE_TO_CONCEPT_MAP table
is no longer populated with content within the Standardized
Vocabularies published to the OMOP community.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
source_code
|
The source code being translated into a Standard Concept.
|
|
varchar(50)
|
Yes
|
No
|
No
|
|
|
source_concept_id
|
A foreign key to the Source Concept that is being translated into
a Standard Concept.
|
This is either 0 or should be a number above 2 billion, which are
the Concepts reserved for site-specific codes and mappings.
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
|
source_vocabulary_id
|
A foreign key to the VOCABULARY table defining the vocabulary of
the source code that is being translated to a Standard Concept.
|
|
varchar(20)
|
Yes
|
No
|
No
|
|
|
source_code_description
|
An optional description for the source code. This is included as a
convenience to compare the description of the source code to the
name of the concept.
|
|
varchar(255)
|
No
|
No
|
No
|
|
|
target_concept_id
|
The target Concept to which the source code is being mapped.
|
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
|
target_vocabulary_id
|
The Vocabulary of the target Concept.
|
|
varchar(20)
|
Yes
|
No
|
Yes
|
VOCABULARY
|
|
valid_start_date
|
The date when the mapping instance was first recorded.
|
|
date
|
Yes
|
No
|
No
|
|
|
valid_end_date
|
The date when the mapping instance became invalid because it was
deleted or superseded (updated) by a new relationship. Default
value is 31-Dec-2099.
|
|
date
|
Yes
|
No
|
No
|
|
|
invalid_reason
|
Reason the mapping instance was invalidated. Possible values are D
(deleted), U (replaced with an update) or NULL when valid_end_date
has the default value.
|
|
varchar(1)
|
No
|
No
|
No
|
|
|
|
|
specimen : Entity
|
|
SPECIMEN
Table Description
The specimen domain contains the records identifying biological
samples from a person.
ETL Conventions
Anatomic site is coded at the most specific level of granularity
possible, such that higher level classifications can be derived using
the Standardized Vocabularies.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
specimen_id
|
Unique identifier for each specimen.
|
|
integer
|
Yes
|
Yes
|
No
|
|
|
person_id
|
The person from whom the specimen is collected.
|
|
integer
|
Yes
|
No
|
Yes
|
PERSON
|
|
specimen_concept_id
|
|
The standard CONCEPT_ID that the SPECIMEN_SOURCE_VALUE maps to in
the specimen domain. Accepted
Concepts
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
|
specimen_type_concept_id
|
|
Put the source of the specimen record, as in an EHR system. Accepted
Concepts. A more detailed explanation of each Type
Concept can be found on the vocabulary
wiki.
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
Type Concept
|
specimen_date
|
The date the specimen was collected.
|
|
date
|
Yes
|
No
|
No
|
|
|
specimen_datetime
|
|
|
datetime
|
No
|
No
|
No
|
|
|
quantity
|
The amount of specimen collected from the person.
|
|
float
|
No
|
No
|
No
|
|
|
unit_concept_id
|
The unit for the quantity of the specimen.
|
Map the UNIT_SOURCE_VALUE to a Standard Concept in the Unit domain. Accepted
Concepts
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
anatomic_site_concept_id
|
This is the site on the body where the specimen is from.
|
Map the ANATOMIC_SITE_SOURCE_VALUE to a Standard Concept in the
Spec Anatomic Site domain. This should be coded at the lowest
level of granularity Accepted
Concepts
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
disease_status_concept_id
|
|
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
specimen_source_id
|
This is the identifier for the specimen from the source system.
|
|
varchar(50)
|
No
|
No
|
No
|
|
|
specimen_source_value
|
|
|
varchar(50)
|
No
|
No
|
No
|
|
|
unit_source_value
|
|
This unit for the quantity of the specimen, as represented in the
source.
|
varchar(50)
|
No
|
No
|
No
|
|
|
anatomic_site_source_value
|
|
This is the site on the body where the specimen was taken from, as
represented in the source.
|
varchar(50)
|
No
|
No
|
No
|
|
|
disease_status_source_value
|
|
|
varchar(50)
|
No
|
No
|
No
|
|
|
|
|
visit_detail : Entity
|
|
VISIT_DETAIL
Table Description
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.
User Guide
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: 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.
ETL Conventions
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 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.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
visit_detail_id
|
Use this to identify unique interactions between a person and the
health care system. This identifier links across the other CDM
event tables to associate events with a visit detail.
|
This should be populated by creating a unique identifier for each
unique interaction between a person and the healthcare system
where the person receives a medical good or service over a span of
time.
|
integer
|
Yes
|
Yes
|
No
|
|
|
person_id
|
|
|
integer
|
Yes
|
No
|
Yes
|
PERSON
|
|
visit_detail_concept_id
|
This field contains a concept id representing the kind of visit
detail, like inpatient or outpatient. All concepts in this field
should be standard and belong to the Visit domain.
|
Populate this field based on the kind of visit that took place for
the person. For example this could be “Inpatient Visit”,
“Outpatient Visit”, “Ambulatory Visit”, etc. This table will
contain standard concepts in the Visit domain. These concepts are
arranged in a hierarchical structure to facilitate cohort
definitions by rolling up to generally familiar Visits adopted in
most healthcare systems worldwide. Accepted
Concepts.
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
Visit
|
visit_detail_start_date
|
This is the date of the start of the encounter. This may or may
not be equal to the date of the Visit the Visit Detail is
associated with.
|
When populating VISIT_DETAIL_START_DATE, you should think about
the patient experience to make decisions on how to define visits.
Most likely this should be the date of the patient-provider
interaction.
|
date
|
Yes
|
No
|
No
|
|
|
visit_detail_start_datetime
|
|
If no time is given for the start date of a visit, set it to
midnight (00:00:0000).
|
datetime
|
No
|
No
|
No
|
|
|
visit_detail_end_date
|
This the end date of the patient-provider interaction. If a Person
is still an inpatient in the hospital at the time of the data
extract and does not have a visit_end_date, then set the
visit_end_date to the date of the data pull.
|
Visit Detail end dates are mandatory. If end dates are not
provided in the source there are three ways in which to derive
them: - Outpatient Visit Detail: visit_detail_end_datetime =
visit_detail_start_datetime - Emergency Room Visit Detail:
visit_detail_end_datetime = visit_detail_start_datetime -
Inpatient Visit Detail: Usually there is information about
discharge. If not, you should be able to derive the end date from
the sudden decline of activity or from the absence of inpatient
procedures/drugs. - Non-hospital institution Visit Details:
Particularly for claims data, if end dates are not provided assume
the visit is for the duration of month that it occurs. For
Inpatient Visit Details ongoing at the date of ETL, put date of
processing the data into visit_detai_end_datetime and
visit_detail_type_concept_id with 32220 “Still patient” to
identify the visit as incomplete. All other Visits Details:
visit_detail_end_datetime = visit_detail_start_datetime.
|
date
|
Yes
|
No
|
No
|
|
|
visit_detail_end_datetime
|
If a Person is still an inpatient in the hospital at the time of
the data extract and does not have a visit_end_datetime, then set
the visit_end_datetime to the datetime of the data pull.
|
If no time is given for the end date of a visit, set it to
midnight (00:00:0000).
|
datetime
|
No
|
No
|
No
|
|
|
visit_detail_type_concept_id
|
Use this field to understand the provenance of the visit detail
record, or where the record comes from.
|
Populate this field based on the provenance of the visit detail
record, as in whether it came from an EHR record or billing claim. Accepted
Concepts. A more detailed explanation of each Type
Concept can be found on the vocabulary
wiki.
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
Type Concept
|
provider_id
|
There will only be one provider per visit record
and the ETL document should clearly state how they were chosen
(attending, admitting, etc.). This is a typical reason for
leveraging the VISIT_DETAIL table as even though each VISIT_DETAIL
record can only have one provider, there is no limit to the number
of VISIT_DETAIL records that can be associated to a
VISIT_OCCURRENCE record.
|
The additional providers associated to a Visit can be stored in
this table where each VISIT_DETAIL record represents a different
provider.
|
integer
|
No
|
No
|
Yes
|
PROVIDER
|
|
care_site_id
|
This field provides information about the Care Site where the
Visit Detail took place.
|
There should only be one Care Site associated with a Visit Detail.
|
integer
|
No
|
No
|
Yes
|
CARE_SITE
|
|
visit_detail_source_value
|
This field houses the verbatim value from the source data
representing the kind of visit detail that took place (inpatient,
outpatient, emergency, etc.)
|
If there is information about the kind of visit detail in the
source data that value should be stored here. If a visit is an
amalgamation of visits from the source then use a hierarchy to
choose the VISIT_DETAIL_SOURCE_VALUE, such as IP -> ER-> OP. This
should line up with the logic chosen to determine how visits are
created.
|
varchar(50)
|
No
|
No
|
No
|
|
|
visit_detail_source_concept_id
|
|
If the VISIT_DETAIL_SOURCE_VALUE is coded in the source data using
an OMOP supported vocabulary put the concept id representing the
source value here.
|
Integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
admitted_from_concept_id
|
Use this field to determine where the patient was admitted from.
This concept is part of the visit domain and can indicate if a
patient was admitted to the hospital from a long-term care
facility, for example.
|
If available, map the admitted_from_source_value to a standard
concept in the visit domain. Accepted
Concepts. If the person was admitted from home, set
this to 0.
|
Integer
|
No
|
No
|
Yes
|
CONCEPT
|
Visit
|
admitted_from_source_value
|
|
This information may be called something different in the source
data but the field is meant to contain a value indicating where a
person was admitted from. Typically this applies only to visits
that have a length of stay, like inpatient visits or long-term
care visits.
|
varchar(50)
|
No
|
No
|
No
|
|
|
discharged_to_source_value
|
|
This information may be called something different in the source
data but the field is meant to contain a value indicating where a
person was discharged to after a visit, as in they went home or
were moved to long-term care. Typically this applies only to
visits that have a length of stay of a day or more.
|
varchar(50)
|
No
|
No
|
No
|
|
|
discharged_to_concept_id
|
Use this field to determine where the patient was discharged to
after a visit. This concept is part of the visit domain and can
indicate if a patient was transferred to another hospital or sent
to a long-term care facility, for example. It is assumed that a
person is discharged to home therefore there is not a standard
concept id for “home”. Use concept id = 0 when a person is
discharged to home.
|
If available, map the DISCHARGE_TO_SOURCE_VALUE to a Standard
Concept in the Visit domain. Accepted
Concepts.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
Visit
|
preceding_visit_detail_id
|
Use this field to find the visit detail that occurred for the
person prior to the given visit detail record. There could be a
few days or a few years in between.
|
The PRECEDING_VISIT_DETAIL_ID can be used to link a visit
immediately preceding the current Visit Detail. Note this is not
symmetrical, and there is no such thing as a “following_visit_id”.
|
integer
|
No
|
No
|
Yes
|
VISIT_DETAIL
|
|
parent_visit_detail_id
|
Use this field to find the visit detail that subsumes the given
visit detail record. This is used in the case that a visit detail
record needs to be nested beyond the VISIT_OCCURRENCE/VISIT_DETAIL
relationship.
|
If there are multiple nested levels to how Visits are represented
in the source, the VISIT_DETAIL_PARENT_ID can be used to record
this relationship.
|
integer
|
No
|
No
|
Yes
|
VISIT_DETAIL
|
|
visit_occurrence_id
|
Use this field to link the VISIT_DETAIL record to its
VISIT_OCCURRENCE.
|
Put the VISIT_OCCURRENCE_ID that subsumes the VISIT_DETAIL record
here.
|
integer
|
Yes
|
No
|
Yes
|
VISIT_OCCURRENCE
|
|
|
|
visit_occurrence : Entity
|
|
VISIT_OCCURRENCE
Table Description
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.
User Guide
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: 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: 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: 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: 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: 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: Provider visiting Person, without a Care Site,
within one day, delivering service
-
Telehealth
Visit: Patient engages with Provider through
communication media
-
Pharmacy
Visit: Person visiting pharmacy for dispensing of Drug,
at a Care Site, within one day
-
Laboratory
Visit: Patient visiting dedicated institution, at a Care
Site, within one day, for the purpose of a Measurement.
-
Ambulance
Visit: 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: 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.
ETL Conventions
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.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
visit_occurrence_id
|
Use this to identify unique interactions between a person and the
health care system. This identifier links across the other CDM
event tables to associate events with a visit.
|
This should be populated by creating a unique identifier for each
unique interaction between a person and the healthcare system
where the person receives a medical good or service over a span of
time.
|
integer
|
Yes
|
Yes
|
No
|
|
|
person_id
|
|
|
integer
|
Yes
|
No
|
Yes
|
PERSON
|
|
visit_concept_id
|
This field contains a concept id representing the kind of visit,
like inpatient or outpatient. All concepts in this field should be
standard and belong to the Visit domain.
|
Populate this field based on the kind of visit that took place for
the person. For example this could be “Inpatient Visit”,
“Outpatient Visit”, “Ambulatory Visit”, etc. This table will
contain standard concepts in the Visit domain. These concepts are
arranged in a hierarchical structure to facilitate cohort
definitions by rolling up to generally familiar Visits adopted in
most healthcare systems worldwide. Accepted
Concepts.
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
Visit
|
visit_start_date
|
For inpatient visits, the start date is typically the admission
date. For outpatient visits the start date and end date will be
the same.
|
When populating VISIT_START_DATE, you should think about the
patient experience to make decisions on how to define visits. In
the case of an inpatient visit this should be the date the patient
was admitted to the hospital or institution. In all other cases
this should be the date of the patient-provider interaction.
|
date
|
Yes
|
No
|
No
|
|
|
visit_start_datetime
|
|
If no time is given for the start date of a visit, set it to
midnight (00:00:0000).
|
datetime
|
No
|
No
|
No
|
|
|
visit_end_date
|
For inpatient visits the end date is typically the discharge date.
If a Person is still an inpatient in the hospital at the time of
the data extract and does not have a visit_end_date, then set the
visit_end_date to the date of the data pull.
|
Visit end dates are mandatory. If end dates are not provided in
the source there are three ways in which to derive them: -
Outpatient Visit: visit_end_datetime = visit_start_datetime -
Emergency Room Visit: visit_end_datetime = visit_start_datetime -
Inpatient Visit: Usually there is information about discharge. If
not, you should be able to derive the end date from the sudden
decline of activity or from the absence of inpatient
procedures/drugs. - Non-hospital institution Visits: Particularly
for claims data, if end dates are not provided assume the visit is
for the duration of month that it occurs. For Inpatient Visits
ongoing at the date of ETL, put date of processing the data into
visit_end_datetime and visit_type_concept_id with 32220 “Still
patient” to identify the visit as incomplete. - All other Visits:
visit_end_datetime = visit_start_datetime. If this is a one-day
visit the end date should match the start date.
|
date
|
Yes
|
No
|
No
|
|
|
visit_end_datetime
|
If a Person is still an inpatient in the hospital at the time of
the data extract and does not have a visit_end_datetime, then set
the visit_end_datetime to the datetime of the data pull.
|
If no time is given for the end date of a visit, set it to
midnight (00:00:0000).
|
datetime
|
No
|
No
|
No
|
|
|
visit_type_concept_id
|
Use this field to understand the provenance of the visit record,
or where the record comes from.
|
Populate this field based on the provenance of the visit record,
as in whether it came from an EHR record or billing claim. Accepted
Concepts. A more detailed explanation of each Type
Concept can be found on the vocabulary
wiki.
|
Integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
Type Concept
|
provider_id
|
There will only be one provider per visit record and the ETL
document should clearly state how they were chosen (attending,
admitting, etc.). If there are multiple providers associated with
a visit in the source, this can be reflected in the event tables
(CONDITION_OCCURRENCE, PROCEDURE_OCCURRENCE, etc.) or in the
VISIT_DETAIL table.
|
If there are multiple providers associated with a visit, you will
need to choose which one to put here. The additional providers can
be stored in the VISIT_DETAIL table.
|
integer
|
No
|
No
|
Yes
|
PROVIDER
|
|
care_site_id
|
This field provides information about the Care Site where the
Visit took place.
|
There should only be one Care Site associated with a Visit.
|
integer
|
No
|
No
|
Yes
|
CARE_SITE
|
|
visit_source_value
|
This field houses the verbatim value from the source data
representing the kind of visit that took place (inpatient,
outpatient, emergency, etc.)
|
If there is information about the kind of visit in the source data
that value should be stored here. If a visit is an amalgamation of
visits from the source then use a hierarchy to choose the visit
source value, such as IP -> ER-> OP. This should line up with the
logic chosen to determine how visits are created.
|
varchar(50)
|
No
|
No
|
No
|
|
|
visit_source_concept_id
|
|
If the visit source value is coded in the source data using an
OMOP supported vocabulary put the concept id representing the
source value here.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
|
admitted_from_concept_id
|
Use this field to determine where the patient was admitted from.
This concept is part of the visit domain and can indicate if a
patient was admitted to the hospital from a long-term care
facility, for example.
|
If available, map the admitted_from_source_value to a standard
concept in the visit domain. Accepted
Concepts. If a person was admitted from home, set
this to 0.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
Visit
|
admitted_from_source_value
|
|
This information may be called something different in the source
data but the field is meant to contain a value indicating where a
person was admitted from. Typically this applies only to visits
that have a length of stay, like inpatient visits or long-term
care visits.
|
varchar(50)
|
No
|
No
|
No
|
|
|
discharged_to_concept_id
|
Use this field to determine where the patient was discharged to
after a visit. This concept is part of the visit domain and can
indicate if a patient was transferred to another hospital or sent
to a long-term care facility, for example. It is assumed that a
person is discharged to home therefore there is not a standard
concept id for “home”. Use concept id = 0 when a person is
discharged to home.
|
If available, map the discharged_to_source_value to a standard
concept in the visit domain. Accepted
Concepts.
|
integer
|
No
|
No
|
Yes
|
CONCEPT
|
Visit
|
discharged_to_source_value
|
|
This information may be called something different in the source
data but the field is meant to contain a value indicating where a
person was discharged to after a visit, as in they went home or
were moved to long-term care. Typically this applies only to
visits that have a length of stay of a day or more.
|
varchar(50)
|
No
|
No
|
No
|
|
|
preceding_visit_occurrence_id
|
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.
|
This field 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”.
|
integer
|
No
|
No
|
Yes
|
VISIT_OCCURRENCE
|
|
|
|
vocabulary : Entity
|
|
VOCABULARY
Table Description
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.
CDM Field
|
User Guide
|
ETL Conventions
|
Datatype
|
Required
|
Primary Key
|
Foreign Key
|
FK Table
|
FK Domain
|
vocabulary_id
|
A unique identifier for each Vocabulary, such as ICD9CM, SNOMED,
Visit.
|
|
varchar(20)
|
Yes
|
Yes
|
No
|
|
|
vocabulary_name
|
The name describing the vocabulary, for example, International
Classification of Diseases, Ninth Revision, Clinical Modification,
Volume 1 and 2 (NCHS) etc.
|
|
varchar(255)
|
Yes
|
No
|
No
|
|
|
vocabulary_reference
|
External reference to documentation or available download of the
about the vocabulary.
|
|
varchar(255)
|
No
|
No
|
No
|
|
|
vocabulary_version
|
Version of the Vocabulary as indicated in the source.
|
|
varchar(255)
|
No
|
No
|
No
|
|
|
vocabulary_concept_id
|
A Concept that represents the Vocabulary the VOCABULARY record
belongs to.
|
|
integer
|
Yes
|
No
|
Yes
|
CONCEPT
|
|
|
|
Entity : Entity
|
|
|
|
: Rectangle
|
|
|
|
VOC BOUNDARY : Rectangle
|
|
|
|
WHERE : Rectangle
|
|
|
|
: Rectangle
|
|
|
|
: Rectangle
|
|
|
|
Vocabulary Tables : Diagram Overview
|
|
|
|
Standardized_Tables : Diagram Overview
|
|
|