Cognitive biases, such as the availability heuristic or availability bias, can inadvertently affect patient outcomes. These biases may be magnified during times of heightened awareness of a particular disease. Failure to identify cognitive biases when managing patients during the coronavirus disease 2019 (COVID-19) pandemic can delay the institution of the right treatment option and result in poor health outcomes. We present a case of delayed diagnosis of Legionella pneumonia due to COVID-19-related availability bias. We discuss some methods to mitigate the effects of this bias and the importance of challenging trainees to recognize these pitfalls in medical training.

Objective Empirical evidence on the availability bias associated with diagnostic errors is still insufficient. We investigated whether or not recent experience with clinical problems can lead physicians to make diagnostic errors due to availability bias and whether or not reflection counteracts this bias. Methods Forty-six internal medicine residents were randomly divided into a control group (CG) and experimental group (EG). Among the eight clinical cases used in this study, three experimental cases were similar to the disease of dengue fever (DF) but exhibited different diagnoses, one was actually DF, and the other four filler cases were not associated with DF. First, only the EG received information on DF, while the CG knew nothing about this study. Then, six hours later, all participants were asked to diagnose eight clinical cases via nonanalytic reasoning. Finally, four cases were diagnosed again via reflective reasoning. Results In stage 2, the average score of the CG in the diagnosis of experimental cases was significantly higher than that of the filler cases (0.80 vs. 0.59, p<0.01), but the EG\'s average score in the two types of cases was not significantly different (0.66 vs. 0.64, p=0.756). The EG and CG had significantly different scores for each experimental case, while no difference was observed in the filler cases. The proportion of diseases incorrectly diagnosed as DF among experimental cases ranged from 71% to 100% in the EG. There were no significant differences between the mean diagnostic accuracy scores obtained by nonanalytic reasoning and those obtained by the reflective reasoning in any cases. Conclusion Availability bias led to diagnostic errors. Misdiagnoses cannot always be repaired solely by adopting a reflective approach.