Abstract 10145: Cardiovascular Disease Risk and Outcomes Among Veterans by Sexual Orientation

Abstract

Introduction: Lesbian, gay, and bisexual (LGB) adults have CVD risk and outcome inequities compared to heterosexual peers. With upwards of 7 million sexual minority adults aged >50 by 2030, assessing and addressing their cardiovascular health is critical for clinicians and public health practitioners. However, few electronic health record (EHR) cohorts have been used to study this association. Methods and Results: In this analysis, we used the Veterans Healthcare Administration Lesbian, Gay, Bisexual, Transgender EHR cohort, excluding transgender individuals to avoid conflating sexual orientation with gender identity. The baseline date was the first primary care appointment on or after October 1, 2009. Sexual orientation of 1,108,990 veterans was identified via a natural language processing tool with 88.2% sensitivity, 91.5% specificity, and 85.9% PPV; 185,788 veterans were classified as LGB. Prevalent CVD (history of AMI, ischemic stroke, or revascularization in the year preceding the baseline date) was present among 19,887 veterans (4,684 LGB). We calculated sample statistics stratified by sex and sexual minority status; results are displayed in the Table . We used logistic regression analyses to assess the association between sexual minority status and prevalent CVD. Adjusting for age, sex, race, and Hispanic ethnicity, LGB veterans had 1.12 [1.16, 1.24] times the odds of prevalent CVD compared to non-sexual minority veterans. Upon additional adjustment for BMI, diabetes, hypertension, lipids, substance use, anxiety, and depression, this association remained significant (OR [95% CI]: 1.08 [1.04, 1.12]). Conclusion: This is one of the first studies to examine cardiovascular health within a veteran population stratified by sexual orientation. Addressing the cardiovascular health of marginalized populations requires further exploring the mechanisms by which stress results in CVD risk and outcomes and the inequitable distribution of both.

Emphasizing Sexual Orientation and Gender Identity Data Capture for Improved Cardiovascular Care of the LGBTQ+ Population

“…Not only does the EHR help us capture SOGIE data prospectively, it also enables collecting these data retrospectively from clinical notes. Retrospective collection can be achieved by natural language processing of clinical notes, which is the ability of a program/computer to understand human language as it is written (in our case) and spoken 45,46 in order to gather and interpret data. The integration of SOGIE data within the EHR comes with definite utility: (1) use in clinical decision support tools, eg, suggesting screening tests based on the anatomic inventory of the organs that a person has and not by their sex assigned at birth, which is what EHR systems currently do; (2) creation of dashboards which enable us to understand SGM population-level metrics of health 44 ; (3) understand differences in cardiovascular outcomes in LGBTQ+ individuals for higher quality personalization of care; and (4) improved concordance between patients and their providers (Figure 2).…”