Validation of an Administrative Algorithm for Transgender and Gender Diverse Persons Against Self-report Data in Electronic Health Records

Overview

Journal J Am Med Inform Assoc

Publisher Oxford University Press

Specialty Medical Informatics

Date 2023 Mar 15

PMID 36921287

Authors

Carl G Streed

Dana King

Chris Grasso

Sari L Reisner

Kenneth H Mayer

Guneet K Jasuja

Tonia Poteat

Monica Mukherjee

Ayelet Shapira-Daniels

Howard Cabral

Vin Tangpricha

Michael K Paasche-Orlow

Emelia J Benjamin

Affiliations

Soon will be listed here.

Abstract

Objective: To adapt and validate an algorithm to ascertain transgender and gender diverse (TGD) patients within electronic health record (EHR) data.

Methods: Using a previously unvalidated algorithm of identifying TGD persons within administrative claims data in a multistep, hierarchical process, we validated this algorithm in an EHR data set with self-reported gender identity.

Results: Within an EHR data set of 52 746 adults with self-reported gender identity (gold standard) a previously unvalidated algorithm to identify TGD persons via TGD-related diagnosis and procedure codes, and gender-affirming hormone therapy prescription data had a sensitivity of 87.3% (95% confidence interval [CI] 86.4-88.2), specificity of 98.7% (95% CI 98.6-98.8), positive predictive value (PPV) of 88.7% (95% CI 87.9-89.4), and negative predictive value (NPV) of 98.5% (95% CI 98.4-98.6). The area under the curve (AUC) was 0.930 (95% CI 0.925-0.935). Steps to further categorize patients as presumably TGD men versus women based on prescription data performed well: sensitivity of 97.6%, specificity of 92.7%, PPV of 93.2%, and NPV of 97.4%. The AUC was 0.95 (95% CI 0.94-0.96).

Conclusions: In the absence of self-reported gender identity data, an algorithm to identify TGD patients in administrative data using TGD-related diagnosis and procedure codes, and gender-affirming hormone prescriptions performs well.

Citing Articles

Impact of Gender Identity Field in the Veterans Health Administration Electronic Health Record, 2016‒2023.

Leder S, McConnell A, Lamba S, Sonnier C, Matza A, Meriwether W Am J Public Health. 2025; 115(3):403-413.

PMID: 39818998 PMC: 11845828. DOI: 10.2105/AJPH.2024.307920.

Validating a Case Definition for Transgender Adults Using Administrative Data.

Rytz C, King J, Saad N, Ronksley P, Somayaji R, Raj S JAMA Netw Open. 2025; 8(1):e2451700.

PMID: 39752161 PMC: 11699535. DOI: 10.1001/jamanetworkopen.2024.51700.

Chronic conditions among transgender Medicare beneficiaries: Variation by race, ethnicity, and Medicaid dual-enrollment.

Babbs G, Mulcahy A, Ellison J, Varma H, Pletta D, Yee K Disabil Health J. 2024; 18(2):101764.

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Assessing how frailty and healthcare delays mediate the association between sexual and gender minority status and healthcare utilization in the All of Us Research Program.

Wong C, Smith L, Cavanaugh R, Kim D, Streed Jr C, Kapadia F J Am Med Inform Assoc. 2024; 31(12):2916-2923.

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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.

Boskey E, Jolly D Transgend Health. 2024; 9(2):192-193.

PMID: 38585243 PMC: 10998010. DOI: 10.1089/trgh.2023.0083.

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