Abstract 36: Clinical Guidelines May Help Mitigate the Impact of Physician Implicit Bias on Patient Care and Treatment

Introduction: We previously found that physician pro-White implicit bias was associated with the performance of low-value revascularization procedures for Black patients with claudication. These treatments are commonly considered risk greater than benefit but are not expressly discouraged by guidelines. We sought to investigate whether implicit bias is less likely to impact care in settings with well-defined Class Ia-supported guidelines. Hypothesis: We hypothesized that a physician’s implicit bias would not be associated with the performance of clinical practices as outlined in the 2016 AHA/ACC Guidelines on the Management of Patients with Lower Extremity Peripheral Artery Disease. Methods: We measured implicit bias via the race Implicit Association Test (IAT) using a sample of physicians from the Society for Vascular Surgery’s Vascular Quality Initiative (VQI). The IAT asks participants to classify sequential images of Black and White faces to positive and negative attributes. Based on reaction times and responses on the IAT, physicians were categorized as having no bias, pro-Black bias, or pro-White bias. IAT results were then weighted to reflect the overall VQI demographics and linked to peripheral revascularization data. We used mixed effects logistic regression models to assess the association of physician implicit bias category with pre-operative prescriptions of antiplatelets (ASA, P2Y12) and statins, as well as current smoking status (reported as aORs). All models included a random intercept for the physician and were adjusted for year, physician race/ethnicity, and patient factors of race/ethnicity, diabetes, and hypertension. We examined effect modification by patient race/ethnicity through the inclusion of an interaction term with physician implicit bias category. Finally, we calculated a summary index across the four primary clinical practices and assessed the association with physician implicit bias category via a mixed effects Poisson model (reported as IRRs). Results: A total of 218 physicians successfully completed the IAT and were linked to 6,588 peripheral revascularizations they completed for claudication. We found no significant associations between the physician’s implicit bias category and the performance of any of the assessed guideline metrics for their Black or White patients (Summary Index - IRR: 1.02, 95% CI: 0.98-1.06). Additionally, we found no evidence of effect modification by patient race/ethnicity (ASA - aOR: 0.91, 95% CI: 0.61-1.34; P2Y12 - aOR: 1.22, 95% CI: 0.88-1.69; Statin - aOR: 1.12, 95% CI: 0.76-1.67). Conclusions: The performance of guideline-driven practices were not associated with a physician’s measured racial implicit bias. We provide preliminary evidence that appropriately designed guidelines could be successful in combatting Black-White health inequities stemming from the implicit bias of physicians.