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Factors Associated with Completeness of Sex and Gender Fields in Electronic Health Records.
McDowell, Alex; Fung, Vicki; Bates, David W; Foer, Dinah.
Afiliação
  • McDowell A; Health Policy Research Center, Mongan Institute, Massachusetts General Hospital, Boston, Massachusetts, USA.
  • Fung V; Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA.
  • Bates DW; Health Policy Research Center, Mongan Institute, Massachusetts General Hospital, Boston, Massachusetts, USA.
  • Foer D; Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA.
LGBT Health ; 2024 Aug 16.
Article em En | MEDLINE | ID: mdl-39149787
ABSTRACT

Purpose:

Our purpose was to understand the completeness of sex and gender fields in electronic health record (EHR) data and patient-level factors associated with completeness of those fields. In doing so, we aimed to inform approaches to EHR sex and gender data collection.

Methods:

This was a retrospective observational study using 2016-2021 deidentified EHR data from a large health care system. Our sample included adults who had an encounter at any of three hospitals within the health care system or were enrolled in the health care system's Accountable Care Organization. The sex and gender fields of interest were gender identity, sex assigned at birth (SAB), and legal sex. Patient characteristics included demographics, clinical features, and health care utilization.

Results:

In the final study sample (N = 3,473,123), gender identity, SAB, and legal sex (required for system registration) were missing for 75.4%, 75.8%, and 0.1% of individuals, respectively. Several demographic and clinical factors were associated with having complete gender identity and SAB. Notably, the odds of having complete gender identity and SAB were greater among individuals with an activated patient portal (odds ratio [OR] = 2.68; 95% confidence interval [CI] = 2.66-2.70) and with more outpatient visits (OR = 4.34; 95% CI = 4.29-4.38 for 5+ visits); odds of completeness were lower among those with any urgent care visits (OR = 0.80; 95% CI = 0.78-0.82).

Conclusions:

Missingness of sex and gender data in the EHR was high and associated with a range of patient factors. Key features associated with completeness highlight multiple opportunities for intervention with a focus on patient portal use, primary care provider reporting, and urgent care settings.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article