Do physicians know when their diagnoses are correct?
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OBJECTIVE: This study explores the alignment between physicians’ confidence in their diagnoses and the “correctness” of these diagnoses, as a function of clinical experience, and whether subjects were prone to over-or underconfidence.
DESIGN: Prospective, counterbalanced experimental design.
SETTING: Laboratory study conducted under controlled conditions at three academic medical centers.
PARTICIPANTS: Seventy-two senior medical students, 72 senior medical residents, and 72 faculty internists.
INTERVENTION: We created highly detailed, 2-to 4-page synopses of 36 diagnostically challenging medical cases, each with a definitive correct diagnosis. Subjects generated a differential diagnosis for each of 9 assigned cases, and indicated their level of confidence in each diagnosis.
MEASUREMENTS AND MAIN RESULTS: A differential was considered “correct” if the clinically true diagnosis was listed in that subject’s hypothesis list. To assess confidence, subjects rated the likelihood that they would, at the time they generated the differential, seek assistance in reaching a diagnosis. Subjects’ confidence and correctness were “mildly” aligned (k=.314 for all subjects, .285 for faculty, .227 for residents, and .349 for students). Residents were overconfident in 41% of cases where their confidence and correctness were not aligned, whereas faculty were overconfident in 36% of such cases and students in 25%.
CONCLUSIONS: Even experienced clinicians may be unaware of the correctness of their diagnoses at the time they make them. Medical decision support systems, and other interventions designed to reduce medical errors, cannot rely exclusively on clinicians’ perceptions of their needs for such support.
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- Do physicians know when their diagnoses are correct?
Journal of General Internal Medicine
Volume 20, Issue 4 , pp 334-339
- Cover Date
- Print ISSN
- Online ISSN
- Additional Links
- diagnostic reasoning
- clinical decision support
- medical errors
- clinical judgment
- Industry Sectors
- Author Affiliations
- 1. Center for Biomedical Informatics, University of Pittsburgh, 8084 Forbes Tower, 15213, Pittsburgh, PA
- 3. Department of Psychology, St. John Fisher College, Rochester, NY, USA
- 4. Division of Community Health, Duke University, Durham, NC, USA
- 5. Department of Medical Education and Informatics, University of Washington, Seattle, WA, USA
- 6. Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA
- 7. Department of Medicine, University of Michigan, Ann Arbor, MI, USA
- 8. Department of Medicine, University of North Carolina, Chapel Hill, NC, USA
- 9. Department of Medical Education, University of Illinois at Chicago, Chicago, IL, USA