Beyond Gender Identity Disorder Diagnoses Codes: An Examination of Additional Methods to Identify Transgender Individuals in Administrative Databases - Jasuja, Guneet K; de Groot, Alexander; Quinn, Emily K; Ameli, Omid; Hughto, Jaclyn M W; Dunbar, Michael; Deutsch, Madeline; Streed, Jr, Carl G; Paasche-Orlow, Michael K; Wolfe, Hill L; Rose, Adam J (Medical care, 2020)
Large administrative databases often do not capture gender identity data, limiting researchers' ability to identify transgender people and complicating the study of this population. The objective of this study was to develop methods for identifying transgender people in a large, national dataset for insured adults. This was a retrospective analysis of administrative claims data. After using gender identity disorder (GID) diagnoses codes, the current method for identifying transgender people in administrative data, we used the following 2 strategies to improve the accuracy of identifying transgender people that involved: (1) Endocrine Disorder Not Otherwise Specified (Endo NOS) codes and a transgender-related procedure code; or (2) Receipt of sex hormones not associated with the sex recorded in the patient's chart (sex-discordant hormone therapy) and an Endo NOS code or transgender-related procedure code. Seventy-four million adults 18 years and above enrolled at some point in commercial or Medicare Advantage plans from 2006 through 2017. We identified 27,227 unique transgender people overall; 18,785 (69%) were identified using GID codes alone. Using Endo NOS with a transgender-related procedure code, and sex-discordant hormone therapy with either Endo NOS or transgender-related procedure code, we added 4391 (16%) and 4051 (15%) transgender people, respectively. Of the 27,227 transgender people in our cohort, 8694 (32%) were transmasculine, 3959 (15%) were transfeminine, and 14,574 (54%) could not be classified. In the absence of gender identity data, additional data elements beyond GID codes improves the identification of transgender people in large, administrative claims databases.