Validating Data-Driven Methods for Identifying Transgender Individuals in the Veterans Health Administration of the US Department of Veterans Affairs. Issue 9 (12th April 2021)

• Record Type: Journal Article
• 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
• Is Part Of: American journal of epidemiology. Volume 190:Issue 9(2021)
• Page Start: 1928
• Page End: 1934
• Publication Date: 2021-04-12
• Subjects: administrative data -- gender identity -- gender identity disorder -- identification methods -- transgender individuals -- US Department of Veterans Affairs; Epidemiology -- Periodicals; Public health -- Periodicals; 614.4
• DOI: 10.1093/aje/kwab102
• Languages: English
• ISSNs: 0002-9262

Abstract

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.