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Strengths and Weakness of the Atherosclerotic Cardiovascular Risk Calculation: A Qualitative Study
Ebiere Okah1, Oluwamuyiwa Adeniran2, Paul Mihas2
1From the University of Minnesota School of Medicine, Minneapolis, MN (EO); University of North Carolina at Chapel Hill Gillings School of Global Public Health, Chapel Hill, NC (OA); University of North Carolina at Chapel Hill Odum Institute for Research in Social Science, Chapel Hill, NC (PM); University of North Carolina School of Medicine, Chapel Hill, NC (PDS). Ebiere@umn.edu.
Background:
Patients at risk of atherosclerotic cardiovascular disease (ASCVD) have low statin use. Clinician perceptions of the ASCVD risk estimates that guide statin prescribing may contribute to poor uptake. At the time of the study, the only equations used to predict ASCVD risk (the Pooled Cohort Equations; PCE) provided race-specific estimates, a controversial practice and a potential reason why clinicians may scrutinize these estimates. We sought to examine how clinicians perceived ASCVD estimates, in relation to their perceptions of race and, also, more broadly.
Methods:
We conducted an interpretive description study using ten 45-minute semistructured interviews with primary care physicians in North Carolina between March and April 2022. Interviews focused on the PCE ASCVD risk calculator and perspectives of race as it relates to ASCVD. Responses were analyzed using both deductive and inductive approaches to identify primary topics.
Results:
5 men and 5 women participated. Of these, 6 identified as White, 2 as Black, and 2 as Asian. Three main topics emerged. First, participants felt conflicted about the role of race in ASCVD risk. Second, they had several concerns with the calculator that went beyond race, including its emphasis on statin use and lack of social determinants of health. Finally, participants universally valued the PCE ASCVD calculator as a tool to educate patients and inspire statin initiation and behavioral change.
Conclusions:
The PCE ASCVD risk calculator was seen as most useful in facilitating discussions regarding behavior and lifestyle changes, suggesting the potential benefit of incorporating variables related to patients' health behaviors in a revised model. The new PREVENT equations provide a helpful first step by removing race and including social determinants. The next step may be to add health behaviors and visual images to facilitate patient counseling and comprehension.
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