Title

Validating data-driven methods to identify transgender individuals in the Veterans Affairs

Affiliations

Division of Endocrinology, Diabetes & Metabolism, Advocate Aurora Health

Abstract

We sought to operationalize and validate data-driven approaches to identify transgender individuals in the U.S. Department of Veteran Affairs (VA) health care system through a retrospective analysis using VA administrative data from 2006 to 2018. Besides gender identity disorder (GID) diagnoses, a combination of non-GID data elements were used to identify potential transgender veterans, including: 1) endocrine disorder, unspecified or not otherwise specified codes, 2) receipt of sex hormones not associated with the sex documented in the veteran's records (gender-affirming hormone therapy), and 3) change in the administratively recorded sex. Both GID and non-GID data elements were applied to a sample of 13,233,529 veterans utilizing the VA healthcare system between January 2006 and December 2018. We identified 10,769 potential transgender veterans. Based on a high positive predictive value of GID (83%, 95% Confidence Interval (CI)=77-89%) versus non-GID-coded veterans (2%, 95% CI=1-11%) from chart review validation, the final analytical sample comprised of only veterans with a GID diagnosis code (n=9,608). In the absence of self-identified gender identity, findings suggest that relying entirely on GID diagnosis codes are the most reliable approach to identify transgender individuals in the VA.

Document Type

Article

PubMed ID

33843970

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