Validating Data-Driven Methods for Identifying Transgender Individuals in the Veterans Health Administration of the US Department of Veterans Affairs

We sought to operationalize and validate data-driven approaches for identifying transgender individuals in the Veterans Health Administration (VHA) of the US Department of Veterans Affairs (VA) through a retrospective analysis using VA administrative data from 2006–2018. Besides diagnoses of gender...

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Bibliographic Details
Published in:American journal of epidemiology 2021-09, Vol.190 (9), p.1928-1934
Main Authors: Wolfe, Hill L, Reisman, Joel I, Yoon, Samuel S, Blosnich, John R, Shipherd, Jillian C, Vimalananda, Varsha G, Rao, Sowmya R, Hashemi, Leila, Berlowitz, Dan, Goodman, Michael, Livingston, Nicholas A, Reece, Scott G, Jasuja, Guneet K
Format: Article
Language:English
Subjects:
Confidence intervals
Diagnosis
Federal agencies
Gender
Gender aspects
Gender identity
Hormones
Sex hormones
Transgender persons
Veterans
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Summary:We sought to operationalize and validate data-driven approaches for identifying transgender individuals in the Veterans Health Administration (VHA) of the US Department of Veterans Affairs (VA) through a retrospective analysis using VA administrative data from 2006–2018. Besides diagnoses of gender identity disorder (GID), a combination of non-GID data elements was used to identify potentially transgender veterans, including 1) an International Classification of Diseases (Ninth or Tenth Revision) code of endocrine disorder, unspecified or not otherwise specified; 2) receipt of sex hormones not associated with the sex documented in the veteran’s records (gender-affirming hormone therapy); and 3) a change in the veteran’s administratively recorded sex. Both GID and non-GID data elements were applied to a sample of 13,233,529 veterans utilizing the VHA of the VA between January 2006 and December 2018. We identified 10,769 potentially transgender veterans. Based on a high positive predictive value for GID-coded veterans (83%, 95% confidence interval: 77, 89) versus non–GID-coded veterans (2%, 95% confidence interval: 1, 11) from chart review validation, the final analytical sample comprised 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 is the most reliable approach for identifying transgender individuals in the VHA of the VA.
ISSN:0002-9262
1476-6256
DOI:10.1093/aje/kwab102