Comparing Electronic Health Record Domains' Utility to Identify Transgender Patients

Overview

Journal Transgend Health

Date 2023 Jan 16

PMID 36644028

Authors

Samuel Dubin

Tiffany Cook

Alison Liss

Glenn Doty

Kevin Moore

Richard Greene

Asa Radix

Aron Janssen

Affiliations

Soon will be listed here.

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 (ICD-10) diagnostic codes and demographic data specific to transgender patients from January 2011 to April 2019.

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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