Beyond Gender Identity Disorder Diagnoses Codes: An Examination of Additional Methods to Identify Transgender Individuals in Administrative Databases

Guneet K. Jasuja*, Alexander De Groot, Emily K. Quinn, Omid Ameli, Jaclyn M.W. Hughto, Michael Dunbar, Madeline Deutsch, Carl G. Streed, Michael K. Paasche-Orlow, Hill L. Wolfe, Adam J. Rose

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

26 Scopus citations


Background:Large administrative databases often do not capture gender identity data, limiting researchers' ability to identify transgender people and complicating the study of this population.Objective:The objective of this study was to develop methods for identifying transgender people in a large, national dataset for insured adults.Research Design: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.Subjects:Seventy-four million adults 18 years and above enrolled at some point in commercial or Medicare Advantage plans from 2006 through 2017.Results: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.Conclusion:In the absence of gender identity data, additional data elements beyond GID codes improves the identification of transgender people in large, administrative claims databases.

Original languageAmerican English
Pages (from-to)903-911
Number of pages9
JournalMedical Care
Issue number10
StatePublished - 1 Oct 2020
Externally publishedYes

Bibliographical note

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© 2020 Lippincott Williams and Wilkins. All rights reserved.


  • administrative data
  • gender dysphoria
  • gender identity disorder
  • identification methods
  • transgender


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