Algorithm to identify transgender and gender nonbinary individuals among people living with HIV performs differently by age and ethnicity
Autor: | Viraj V. Patel, David B. Hanna, Mindy Ginsberg, Jules Chyten-Brennan |
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Rok vydání: | 2021 |
Předmět: |
Adult
Male Epidemiology Human immunodeficiency virus (HIV) Ethnic group Patient characteristics HIV Infections medicine.disease_cause Transgender Persons 01 natural sciences Article 03 medical and health sciences Age Distribution 0302 clinical medicine Chart review Transgender Ethnicity medicine Electronic Health Records Humans Prospective Studies 030212 general & internal medicine 0101 mathematics Retrospective Studies Data collection business.industry 010102 general mathematics Gender Identity Reproducibility of Results Middle Aged Female Diagnosis code business Algorithm Algorithms Urban health |
Zdroj: | Ann Epidemiol |
ISSN: | 1047-2797 |
Popis: | PURPOSE: HIV research among transgender and gender nonbinary (TGNB) people is limited by lack of gender identity data collection. We designed an EHR-based algorithm to identify TGNB people among patients living with HIV (PLWH) when gender identity was not systematically collected. METHODS: We applied EHR-based search criteria to all PLWH receiving care at a large urban health system between 1997–2017, then confirmed gender identity by chart review. We compared patient characteristics by gender identity and screening criteria, then calculated positive predictive values (PPVs) for each criterion. RESULTS: Among 18,086 PLWH, 213 (1.2%) met criteria as potential TGNB patients and 178/213 were confirmed. PPVs were highest for free-text keywords (91.7%) and diagnosis codes (77.4%). Verified TGNB patients were younger (median 32.5 vs. 42.5 years, p |
Databáze: | OpenAIRE |
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