Patterns of gender identity data within electronic health record databases can be used as a tool for identifying and estimating the prevalence of gender-expansive people

Author:

Hines Nicole G1,Greene Dina N23ORCID,Imborek Katherine L4,Krasowski Matthew D5ORCID

Affiliation:

1. Carver College of Medicine, University of Iowa , Iowa City, Iowa, USA

2. Department of Laboratory Medicine, University of Washington , Seattle, Washington, USA

3. LetsGetChecked Laboratories , Monrovia, California, USA

4. Department of Family Medicine, University of Iowa , Iowa City, Iowa, USA

5. Department of Pathology, University of Iowa Hospitals and Clinics , Iowa City, Iowa, USA

Abstract

Abstract Objective Electronic health records (EHRs) within the United States increasingly include sexual orientation and gender identity (SOGI) fields. We assess how well SOGI fields, along with International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10) codes and medication records, identify gender-expansive patients. Materials and Methods The study used a data set of all patients that had in-person inpatient or outpatient encounters at an academic medical center in a rural state between December 1, 2018 and February 17, 2022. Chart review was performed for all patients meeting at least one of the following criteria: differences between legal sex, sex assigned at birth, and gender identity (excluding blank fields) in the EHR SOGI fields; ICD-10 codes related to gender dysphoria or unspecified endocrine disorder; prescription for estradiol or testosterone suggesting use of gender-affirming hormones. Results Out of 123 441 total unique patients with in-person encounters, we identified a total of 2236 patients identifying as gender-expansive, with 1506 taking gender-affirming hormones. SOGI field differences or ICD-10 codes related to gender dysphoria or both were found in 2219 of 2236 (99.2%) patients who identify as gender-expansive, and 1500 of 1506 (99.6%) taking gender-affirming hormones. For the gender-expansive population, assigned female at birth was more common in the 12–29 year age range, while assigned male at birth was more common for those 40 years and older. Conclusions SOGI fields and ICD-10 codes identify a high percentage of gender-expansive patients at an academic medical center.

Publisher

Oxford University Press (OUP)

Subject

Health Informatics

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