Reducing Diagnostic Error in the Intensive Care Unit. Engaging Uncertainty When Teaching Clinical Reasoning

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Abstract

As medicine continues to advance with improvements in technology, factual information has become more easily available at the bedside. Nevertheless, diagnostic error remains a salient concern for the medical community and public. To address this problem, two fundamental characteristics of the physician remain important: curiosity and the ability to apply critical reasoning to solve problems, often in the setting of imperfect knowledge and uncertainty. Historically, the teaching and recall of factual information, illness scripts, and pattern recognition are emphasized early in medical education. Students are often left with the impression that there is a single correct answer for every question; discussions of uncertainty are rare. Consequently, discomfort with uncertainty is common among doctors. As attention to explicit teaching of clinical reasoning increases, one must consider how to incorporate uncertainty into that teaching and to transform the clinical learning environment to embrace uncertainty. The authors propose the use of several simple methods easily employed in the critical care setting to make uncertainty explicit by changing the language used for expressing differential diagnosis, incorporating probabilities into daily sign-outs, and by implementing inductive reasoning when teaching critical thinking to offer learners a strategy for working through unknown problems; these approaches may normalize uncertainty, improve comfort with it, and reduce the impact of cognitive bias in decision-making. Comfort with uncertainty may result not only in improved clinical experiences for learning by transforming a once negative cognitive experience to a positive one but also in reduced susceptibility to thinking errors.

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Dunlop, M., & Schwartzstein, R. M. (2020). Reducing Diagnostic Error in the Intensive Care Unit. Engaging Uncertainty When Teaching Clinical Reasoning. ATS Scholar, 1(4), 364–371. https://doi.org/10.34197/ats-scholar.2020-0043PS

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