The variability in how physicians think: a casebased diagnostic simulation exercise.

Gupta A, Quinn M, Saint S, Lewis R, Fowler KE, Winter S, Chopra V. The variability in how physicians think: a casebased diagnostic simulation exercise. Diagnosis (Berlin, Germany). 2021 May 26; 8(2):167-175.

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Abstract:

OBJECTIVES: Little is known about how physician diagnostic thinking unfolds over time when evaluating patients. We designed a case-based simulation to understand how physicians reason, create differential diagnoses, and employ strategies to achieve a correct diagnosis. METHODS: Between June 2017 and August 2018, hospital medicine physicians at two academic medical centers were presented a standardized case of a patient presenting with chest pain who was ultimately diagnosed with herpes zoster using an interview format. Case information was presented in predetermined aliquots where participants were then asked to think-aloud, describing their thoughts and differential diagnoses given the data available. At the conclusion of the interview, participants were asked questions about their diagnostic process. Interviews were recorded, transcribed, and content analysis was conducted to identify key themes related to the diagnostic thinking process. RESULTS: Sixteen hospital medicine physicians (nine men, seven women) participated in interviews and four obtained the correct final diagnosis (one man, three women). Participants had an average of nine years of experience. Overall, substantial heterogeneity in both the differential diagnoses and clinical reasoning among participants was observed. Those achieving the correct diagnosis utilized systems-based or anatomic approaches when forming their initial differential diagnoses, rather than focusing on life-threatening diagnoses alone. Evidence of cognitive bias was common; those with the correct diagnosis more often applied debiasing strategies than those with the incorrect final diagnosis. CONCLUSIONS: Heterogeneity in diagnostic evaluation appears to be common and may indicate faulty data processing. Structured approaches and debiasing strategies appear helpful in promoting diagnostic accuracy.