Overlooked: Implicit Bias in Health Care
In health care, the impact of implicit bias in clinical decision-making is a persistent problem. Although implicit biases are ubiquitous among the general human population, healthcare professionals may be more susceptible, because the healthcare setting—often fast-paced, high-stress, and high-uncertainty—can accentuate cognitive biases.
The clinical setting is fast-paced because clinicians need to juggle numerous patients, administrative tasks, and other responsibilities while staying on a tight schedule. Clinical decision-making can also often be synonymous with uncertainty. Arriving at a diagnosis is like a puzzle; sometimes, a patient’s symptomatology or lab results will not point to a clear diagnosis, requiring the provider to rely on prior experience to make a decision.
This, in conjunction with intense work demands, long hours, and occasionally uncooperative patients, can contribute to the emotional toll and stress that healthcare professionals endure on the job. This is the perfect storm for prejudice to rear its head, as it promotes a shift towards System 1 thinking and increases our reliance on heuristics—mental shortcuts that we take during the decision-making process for the sake of cognitive ease.1
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About the Author
Sanketh Andhavarapu
Sanketh is an undergraduate student at the University of Maryland: College Park studying Health Decision Sciences (individual studies degree) and Biology. He is the co-Founder and co-CEO of Vitalize, a digital wellness platform for healthcare workers, and has published research on topics related to clinical decision-making, neurology, and emergency medicine and critical care. He is also currently leading business development for a new AI innovation at PediaMetrix, a pediatric health startup, and previously founded STEPS, an education nonprofit. Sanketh is interested in the applications of behavioral and decision sciences to improve medical decision-making, and how digital health and health policy serve as a scalable channel to do so.
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