• Diagnosis (Berl) · Jun 2019

    Use of clinical reasoning tasks by medical students.

    • Elexis McBee, Christina Blum, Temple Ratcliffe, Lambert Schuwirth, Elizabeth Polston, Anthony R Artino, and Steven J Durning.
    • Department of Medicine, F. Edward Hébert School of Medicine, Uniformed Services University, Naval Medical Center San Diego, 34800 Bob Wilson Drive, San Diego, CA 92134, USA.
    • Diagnosis (Berl). 2019 Jun 26; 6 (2): 127-135.

    AbstractBackground A framework of clinical reasoning tasks used by physicians during clinical encounters was previously developed proposing that clinical reasoning is a complex process composed of 26 possible tasks. The aim of this paper was to analyze the verbalized clinical reasoning processes of medical students utilizing commonly encountered internal medicine cases. Methods In this mixed-methods study, participants viewed three video recorded clinical encounters. After each encounter, participants completed a think-aloud protocol. The qualitative data from the transcribed think-aloud transcripts were analyzed by two investigators using a constant comparative approach. The type, frequency, and pattern of codes used were analyzed. Results Seventeen third and fourth year medical students participated. They used 15 reasoning tasks across all cases. The average number of tasks used in cases 1, 2, and 3 was (respectively) 5.6 (range 3-8), 5.9 (range 4-8), and 5.3 (range 3-10). The order in which medical students verbalized reasoning tasks varied and appeared purposeful but non-sequential. Conclusions Consistent with prior research in residents, participants progressed through the encounter in a purposeful but non-sequential fashion. Reasoning tasks related to framing the encounter and diagnosis were not used in succession but interchangeably. This suggests that teaching successful clinical reasoning may involve encouraging or demonstrating multiple pathways through a problem. Further research exploring the association between use of clinical reasoning tasks and clinical reasoning accuracy could enhance the medical community's understanding of variance in clinical reasoning.

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