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While a growing body of evidence suggests that healthcare workers in low and middle-income countries often provide poor quality of care, the reasons behind such low performance remain unclear. The literature on medical decision-making suggests that cognitive biases, or failures related to the way healthcare providers think, explain many diagnostic errors. This study investigates whether one cognitive bias, overconfidence, defined as the tendency to overestimate one's performance relative to others, is associated with the low quality of care provided in Senegal. It links survey data on the overconfidence of health workers to objective measures of the quality of care they provide to standardised patients – enumerators who pose as real patients and record details of the consultation. We find that about a third of providers are overconfident – meaning that they overestimate their own abilities relative to their peers. It shows that overconfident providers are 26% less likely to manage patients correctly and exert less effort in clinical practice. These results suggest that the low levels of quality of care observed in some settings could be partly explained by the cognitive biases of providers, such as overconfidence. Policies that encourage adequate supervision and feedback to healthcare workers might reduce such failures in clinical decision-making.

The great majority of medical diagnoses are made using automatic, efficient cognitive processes, and these diagnoses are correct most of the time. This analytic review from Berner and Graber in The American Journal of Medicine concerns the exceptions: the times when these cognitive processes fail and the final diagnosis is missed or wrong. The authors argue that physicians in general underappreciate the likelihood that their diagnoses are wrong and that this tendency to overconfidence is related to both intrinsic and systemically reinforced factors. They present a comprehensive review of the available literature and current thinking related to these issues. The review covers the incidence and impact of diagnostic error, data on physician overconfidence as a contributing cause of errors, strategies to improve the accuracy of diagnostic decision making, and recommendations for future research.

To improve their diagnosis and management skills, doctors need consistent, timely and accurate feedback, as it helps them become better calibrated, leading to more appropriate clinical decisions. Despite its benefits, clinicians do not consistently receive information on the subsequent clinical outcomes of patients they have diagnosed and treated, known as patient outcome feedback. This paper discusses challenges faced in developing systems for effective patient outcome feedback. The authors propose applying a sociotechnical approach using health IT to support these systems. The concepts they discuss are applicable not only to fragmented systems of care, but also to integrated health systems that plan to harness the benefits of integration for providing effective clinician feedback.

This article by The Decision Lab explains the Dunning-Kruger Effect, which occurs when a person’s lack of knowledge and skills in a certain area causes them to overestimate their own competence. By contrast, this effect also causes those who excel in a given area to think the task is simple for everyone, and underestimate their relative abilities as well. The article covers the following topics: Where this bias occurs Individual effects Systemic effects Why it happens Why it is important How to avoid it How it all started It also includes two real-world examples of the Dunning-Kruger Effect.