Diagnostic Decision Making in the Face of Uncertainty: COVID-19 and Its Sequalae

The introduction of an unfamiliar disease has added uncertainty to many aspects of the practice of medicine. Evidence-based-guidelines on the recognition, investigation, and treatment of COVID-19 and its sequelae are in early stages. Clinicians are often left making critical diagnostic and treatment decisions in the absence of clear evidence. Operating in the face of uncertainty has brought to light fallibilities in clinical decision-making processes in healthcare systems around the world. A growing body of literature on COVID-19 and its associated Multisystem Inflammatory Syndrome has revealed self-perpetuating cycles of cognitive biases with far-reaching implications on patients, populations, and healthcare systems. We describe the implications of cognitive biases on decision making processes in the context of the COVID-19 pandemic. In an era when even the most experienced of clinicians find themselves navigating unchartered territory, we must rely on tried-and-true diagnostic decision-making processes to mitigate cognitive biases. To address a challenge of such complexity, we incorporate a problem spaces perspective to clinical decision making, encompasses the broader context in which decisions are made, including workplace environment, team dynamics, patient wishes, practitioner perspectives, framing of the problem, and sociocultural factors. By applying evidence from relevant disciplines, we highlight strategies to mitigate cognitive biases during emerging infectious disease pandemics, including optimizing multidisciplinary decision-making, building redundancies, and strengthening decision making processes. Continuous feedback, recalibration, and reflection will provide a better understanding of the art of diagnostic decision making and improve healthcare quality.