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Licensed Unlicensed Requires Authentication Published by De Gruyter July 22, 2020

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

Ashwin Gupta, Martha Quinn, Sanjay Saint, Richard Lewis, Karen E. Fowler, Suzanne Winter and Vineet Chopra
From the journal Diagnosis



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.


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.


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.


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.

Corresponding author: Ashwin Gupta, MD, VA Ann Arbor Healthcare System Medicine Service, 2215 Fuller Road, Ann Arbor, MI, USA; Division of Hospital Medicine, Department of Medicine, University of Michigan, Ann Arbor, MI, USA; E-mail:

Funding source: Agency for Healthcare Research and Quality

Award Identifier / Grant number: P30HS024385

Funding source: Moore Foundation

Funding source: Agency for Healthcare Research and Quality

Award Identifier / Grant number: 1 R18 HS025891-01

Funding source: Centers for Disease Control and Prevention

Funding source: National Institutes of Health

Funding source: Department of Veterans Affairs

  1. Research funding: This project was supported by grant number P30HS024385 from the Agency for Healthcare Research and Quality. The funding source played no role in study design, data acquisition, analysis or decision to report these data. Dr. Gupta is supported by funding from the Moore Foundation. Dr. Chopra is supported by funding from the Moore Foundation and the Agency for Healthcare Research and Quality (1 R18 HS025891-01). Dr. Saint receives funding support from the Moore Foundation, the Agency for Healthcare Research and Quality, the Centers for Disease Control and Prevention, the National Institutes of Health, and the Department of Veterans Affairs.

  2. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  3. Competing interests: Authors state no conflict of interest.

  4. Informed consent: Informed consent was obtained from all individuals included in this study.

  5. Ethical approval: Generally ethical approval is captured within the IRB approval for human subjects. This study was reviewed and approved by the Institutional Review Board at the University of Michigan Health System (HUM-00106657).


1. Institute of Medicine. Improving diagnosis in health care. Washington, DC: National Academies Press; 2015.Search in Google Scholar

2. Saber Tehrani, AS, Lee, H, Mathews, SC, Shore, A, Makary, M, Pronovost, P, et al. 25-Year summary of US malpractice claims for diagnostic errors 1986-2010: an analysis from the National Practitioner Data Bank. BMJ Qual Saf 2013;22:672–80. in Google Scholar

3. Graber, ML, Kissam, S, Payne, VL, Meyer, AN, Sorensen, A, Lenfestey, N, et al. Cognitive interventions to reduce diagnostic error: a narrative review. BMJ Qual Saf 2012;21:535–57. in Google Scholar

4. Singh, H, Graber, ML, Kissam, SM, Sorensen, AV, Lenfestey, NF, Tant, EM, et al. System-related interventions to reduce diagnostic errors: a narrative review. BMJ Qual Saf 2012;21:160–70. in Google Scholar

5. Gupta, A, Harrod, M, Quinn, M, Manojlovich, M, Fowler, KE, Singh, H, et al. Mind the overlap: how system problems contribute to cognitive failure and diagnostic errors. Diagnosis (Berl.) 2018;5:151–6. in Google Scholar

6. Abimanyi-Ochom, J, Bohingamu Mudiyanselage, S, Catchpool, M, Finpis, M, Wanni Arachchiage Dona, S, Watts, JJ. Strategies to reduce diagnostic errors: a systematic review. BMC Med Inf Decis Making 2019;19:174. in Google Scholar

7. Hilliard, AA, Weinberger, SE, Tierney, LMJr, Midthun, DE, Saint, S. Clinical problem-solving. Occam’s razor versus Saint’s triad. N Engl J Med 2004;350:599–603. in Google Scholar

8. Fonteyn, ME, Kuipers, B, Grobe, SJ. A description of think aloud method and protocol analysis. Qual Health Res 1993;3:430–41. in Google Scholar

9. Forman, J, Damschroder, L. Qualitative content analysis. Empirical methods for bioethics: a primer. Bingley: Emerald Group Publishing Limited; 2007.10.1016/S1479-3709(07)11003-7Search in Google Scholar

10. Graber, ML, Franklin, N, Gordon, R. Diagnostic error in internal medicine. Arch Intern Med 2005;165:1493–9. in Google Scholar PubMed

11. Zwaan, L, Thijs, A, Wagner, C, Timmermans, DR. Does inappropriate selectivity in information use relate to diagnostic errors and patient harm? The diagnosis of patients with dyspnea. Soc Sci Med 2013;91:32–8. in Google Scholar PubMed

12. Patel, K. Is clinical examination dead?. BMJ 2013;346:f3442. in Google Scholar PubMed

13. Forbes, C, Weissman, C. Mnemonics: overused in medical education?. In: Training: the agora of the medical student community. Available from: [Accessed December 31, 2019].Search in Google Scholar

14. Riches, R, Panagiota, M, Rahul, A, Cheragh-Sohi, S, Campbell, S, Esmail, A, et al. The effectiveness of electronic differential diagnosis (DDX) generators: a systematic review and meta-analysis. PloS One 2016;11:e0148991. in Google Scholar PubMed PubMed Central

15. Huang, GC, Kriegel, G, Wheaton, C, Sternberg, S, Sands, K, Richards, J, et al. Implementation of diagnostic pauses in the ambulatory setting. BMJ Qual Saf 2018;27:492–7. in Google Scholar PubMed

Received: 2020-01-15
Accepted: 2020-05-28
Published Online: 2020-07-22
Published in Print: 2021-05-26

© 2020 Walter de Gruyter GmbH, Berlin/Boston

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