Implicit Bias And Unintentional Harm In Vascular Care: The Case For Intervention

Implicit-association test
DOI: 10.1101/2024.02.13.24302798 Publication Date: 2024-02-14T17:30:12Z
ABSTRACT
ABSTRACT Introduction Implicit (or unconscious) bias may influence physician treatment decisions and contribute to Black-White health disparities. While implicit has been linked with low quality care via clinical vignettes, some worry that these studies are not representative of the ‘real world.’ There is limited data attempted link actual delivery outcomes. We sought understand if associated potentially harmful surgical selection in a cohort patients peripheral artery disease (PAD)-related claudication undergoing below-knee lower extremity revascularization as captured world’ procedural registry. Methods invited vascular specialists from Vascular Quality Initiative (VQI) take race Association Test (IAT). The IAT asks participants associate images Black White Americans either positive or negative attributes. Based on reaction time differences across sequential tests, were grouped into race-based categories: pro-White bias, no pro-Black bias. Our provider-level results patient-level registry procedures performed for claudication. measured adjusted odds performance below knee by specialist patient mixed effects logistic regression models. assessed moderator association 1-yr amputation. Results 218 United States completed 157 (72%) had treated 74% increase receiving procedure compared total sample (aOR: 1.74, 95% CI: 1.33-2.15). When 3 times amputation – regardless anatomic location 3.04, 1.68-5.51). Conversely, similar 0.99, 0.67-1.30) 1-year 1.31, 0.35-4.96) full sample. Conclusions contributes outcome disparities States. These suggest need system-level interventions transparently identify warn aligned best practices reduce effect Clinical Perspective What new? Pro-White low-value patients. physicians preferences also worse rates. found little variation among IAT. implications? Physicians who treat diseases consider their own where they be falling short standards, particularly Health leaders must begin evaluate how why systems make it possible practitioners’ unconscious biases negatively impact care. Policy changes enhance payment evidence-based should considered.
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