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

Abstract

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.