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The Gender domain captures all concepts about the sex of a person, denoting the biological and physiological characteristics. In fact, the Domain (and field in the PERSON table) should probably should be called “sex” rather than “gender”, as gender refers to behaviors, roles, expectations, and activities in society.
The domain contains only two standard concepts: FEMALE (concept_id=8532) and MALE (concept_id=8507). Many data sources contain other codes, such as “Unknown”, “Refused to tell”, “Hermaphrodite”, as well as transgender constellations (“male to female”, etc.). For the current purposes of the OMOP CDM, the gender concepts are used to stratify patients by their biological make-up or to adjust analytical results for the influence of the biological sex. Therefore, all those other genders are denoted as concept_id=0 (unknown information).
The race field contains races and ethnic backgrounds, while for Ethnicity there are only two categories for data on ethnicity: “Hispanic or Latino” (concept_id=38003563) and “Not Hispanic or Latino” (concept_id=38003564). This means, the two categories are orthogonal to each other, and both Latinos and non-Latinos can have any racial or ethnic background.
This is a very US-centric solution, and hence the terminology might be confusing to non-US data owners. If belong to the latter group, you can probably ignore this field entirely.
There are no relationships defined for Ethnicity.
Relevant data fields:
:ETHNICITY_CONCEPT_ID
"Hispanic or Latino": 38003563
"Not Hispanic or Latino": 38003564
:GENDER_CONCEPT_SOURCE
Female: 8532
Male: 8507
Other or Unknown: 0
:YEAR_OF_BIRTH
:DRUG_CONCEPT_ID
Johnson & Johnson: 739906
Pfizer: 37003436
Moderna: 37003518
Identifying COVID-positive individuals requires a concept set. How should concept sets be handled in general?
Input: a concept group
c
Output:
c
, individuals outsidec
, unmatched, and total (number and percentage)The text was updated successfully, but these errors were encountered: