Teaching Diagnostic Reasoning to Medical Students: a four-step approach
Diagnosis is fundamental to clinical medicine, and diagnostic errors are a serious public health problem. However, there is little consensus regarding the best approach to teaching diagnostic reasoning in medical schools. One approach (“pattern recognition”) uses learned associations between patient...
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Published in | Perspectives in biology and medicine Vol. 64; no. 4; pp. 557 - 586 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Baltimore
Johns Hopkins University Press
01.09.2021
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Subjects | |
Online Access | Get full text |
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Summary: | Diagnosis is fundamental to clinical medicine, and diagnostic errors are a serious public health problem. However, there is little consensus regarding the best approach to teaching diagnostic reasoning in medical schools. One approach (“pattern recognition”) uses learned associations between patient symptoms and signs and human disorders to help experienced clinicians solve problems rapidly and efficiently. However, this approach may be ineffective when used by students with little clinical experience. Here we describe a four-step analytical approach to diagnosis that can be used by medical students before beginning clinical training. This approach complements the pattern recognition approach used by experts and can be used by students, residents in training, and attending physicians when confronting complex cases. The analytical approach also highlights critical basic science concept areas that support diagnostic reasoning and therefore warrant emphasis in medical school curricula. We propose introducing the analytical approach to medical students early in their training, coordinated with basic science instruction. Once students master relevant basic science concepts, they can use the analytical approach to diagnose disorders affecting one or more physiological systems, as a foundation for future clinical training. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0031-5982 1529-8795 1529-8795 |
DOI: | 10.1353/pbm.2021.0041 |