ArticleTransgender health2022
Comparing Electronic Health Record Domains' Utility to Identify Transgender Patients.
Article in Transgender health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- When algorithms infer gender: revisiting computational phenotyping with electronic health records data.Biology of sex differences · 2025Review
- A multidisciplinary look into transgender and gender diverse people with epilepsy: An at-risk and underreported population.Epilepsia · 2025Article
- Unveiling health disparities: Diagnostic prevalences in a transgender cohort versus matched controls.PloS one · 2025Article
- Impact of sex used for assignment of reference intervals in a population of patients taking gender-affirming hormones.Journal of clinical & translational endocrinology · 2024Article
- Re: "Determining the Sex Assigned at Birth of Transgender and Nonbinary Populations in Administrative Claims Databases Utilizing Diagnostic and Procedure Codes" by Haley et al.Transgender health · 2024Article
- Health-Outcomes and Epidemiologic Research of Transgender Patients Requires Simple, Meaningful Diagnostic Codes: A Retrospective Review of California Emergency Department Visits.Journal of surgery and research · 2024Article
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- Change in Gender on Record and Transgender Adults' Mental or Behavioral Health.American journal of preventive medicine · 2022Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Earlier literature has reported on the utility of diagnostic codes and demographic information for identifying transgender patients. We aim to assess which method identifies the most transgender patients utilizing readily available tools from within the electronic health record (EHR). Methods: A de-identified patient database from a single EHR that allows for searching any discrete data point in the EHR was used to query Results: Demographic data and ICD-10 codes yielded 1494 individual EHRs with transgender-specific data domains. ICD-10 diagnostic codes alone identified 942 (63.05%) unique EHRs. Demographics alone identified 218 (14.59%) unique EHRs. A total of 334 (22.36%) unique EHRs had both ICD-10 and demographic identifiers. Of those identified by transgender-specific demographic data (552), 294 (53.26%) were trans masculine, 215 (38.95%) were trans feminine, and 43 (7.79%) were nonbinary. Of the 552 demographic-identified transgender patients, 141 (25.86%) were identified by a two-part gender identity demographic question. Conclusions: ICD-10 diagnostic codes, not demographic data, identified the most transgender patient records, but neither diagnostic codes alone nor demographic data captured the full population. Only 26.36% of the charts identified as transgender patients had both ICD-10 codes and demographic data. We recommend that when identifying transgender populations through EHR domains, a combination of diagnostic codes and demographic data be used. Furthermore, research is needed to optimize disclosure and collection of demographic information for gender minority populations.
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