Cited by 49Clinical Reasoning and Diagnostic SkillsPatient Safety and Medication ErrorsDecision-Making and Behavioral Economics

Cognitive biases encountered by physicians in the emergency room

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Kunitomo, Kotaro, Harada, Taku, Watari, Takashi·2022·BMC Emergency Medicine

Abstract

Background: Diagnostic errors constitute an important medical safety problem that needs improvement, and their frequency and severity are high in emergency room settings. Previous studies have suggested that diagnostic errors occur in 0.6-12% of first-time patients in the emergency room and that one or more cognitive factors are involved in 96% of these cases. This study aimed to identify the types of cognitive biases experienced by physicians in emergency rooms in Japan. Methods: We conducted a questionnaire survey using Nikkei Medical Online (Internet) from January 21 to January 31, 2019. Of the 159,519 physicians registered with Nikkei Medical Online when the survey was administered, those who volunteered their most memorable diagnostic error cases in the emergency room participated in the study. EZR was used for the statistical analyses. Results: A total of 387 physicians were included. The most common cognitive biases were overconfidence (22.5%), confirmation (21.2%), availability (12.4%), and anchoring (11.4%). Of the error cases, the top five most common initial diagnoses were upper gastrointestinal disease (22.7%), trauma (14.7%), cardiovascular disease (10.9%), respiratory disease (7.5%), and primary headache (6.5%). The corresponding final diagnoses for these errors were intestinal obstruction or peritonitis (27.3%), overlooked traumas (47.4%), other cardiovascular diseases (66.7%), cardiovascular disease (41.4%), and stroke (80%), respectively. Conclusions: A comparison of the initial and final diagnoses of cases with diagnostic errors shows that there were more cases with diagnostic errors caused by overlooking another disease in the same organ or a disease in a closely related organ.

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  • Overconfidence is one of the most common biases in the clinical setting, as clinicians sometimes trust their own judgment more than engaging in thorough investigations.

    “Overconfidence is one of the most common biases in the clinical setting [103], as clinicians sometimes trust their own judgment more than engaging in thorough investigations.”

    From Toward Safer Diagnoses: A SEIPS-Based Narrative Review of Diagnostic Errors (2026) · cites this paper as [103]

    The Results report that overconfidence was the most common bias identified (22.5%), and the Conclusions list it among the most common biases in the emergency room. The claim extends that finding to clinical settings generally, whereas this study examined emergency-room diagnostic errors. (LLM, conf=0.84)

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References 40 · Cited by 49

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  1. [1]Pelaccia T Messman AM Kline JA Misdiagnosis and failure to diagnose in emergency care: causes and empathy as a solution Patient Educ Couns 2020 103 1650 1656 10.1016/j.pec.2020.02.039 32169322 · DOI
  2. [2]Westbrook JI Raban MZ Walter SR Douglas H Task errors by emergency physicians are associated with interruptions, multitasking, fatigue and working memory capacity: a prospective, direct observation study BMJ Qual Saf 2018 27 655 663 10.1136/bmjqs-2017-007333 PMC6204927 29317463 · DOI
  3. [3]Chisholm CD Dornfeld AM Nelson DR Cordell WH Work interrupted: a comparison of workplace interruptions in emergency departments and primary care offices Ann Emerg Med 2001 38 146 151 10.1067/mem.2001.115440 11468609 · DOI
  4. [4]Ratwani RM Fong A Puthumana JS Hettinger AZ Emergency physician use of cognitive strategies to manage interruptions Ann Emerg Med 2017 70 683 687 10.1016/j.annemergmed.2017.04.036 28601266 · DOI
  5. [5]Hansen K Schultz T Crock C Deakin A Runciman W Gosbell A The emergency medicine events register: an analysis of the first 150 incidents entered into a novel, online incident reporting registry Emerg Med Australas 2016 28 544 550 10.1111/1742-6723.12620 27476648 · DOI
  6. [6]Berg LM Källberg AS Göransson KE Östergren J Florin J Ehrenberg A Interruptions in emergency department work: an observational and interview study BMJ Qual Saf 2013 22 656 663 10.1136/bmjqs-2013-001967 23584208 · DOI
  7. [8]Balogh EP Miller BT Ball JR Improving diagnosis in health care 2015 Washington (DC) National Academies Press. US 26803862
  8. [9]Hansen K Cognitive bias in emergency medicine Emerg Med Australas 2020 32 852 855 10.1111/1742-6723.13622 32902161 · DOI
  9. [10]Pelaccia T Tardif J Triby E Ammirati C Bertrand C Dory V How and when do expert emergency physicians generate and evaluate diagnostic hypotheses? A qualitative study using head-mounted video cued-recall interviews Ann Emerg Med 2014 64 575 585 10.1016/j.annemergmed.2014.05.003 24882662 · DOI
  10. [11]O'Connor PM Dowey KE Bell PM Irwin ST Dearden CH Unnecessary delays in accident and emergency departments: do medical and surgical senior house officers need to vet admissions? J Accid Emerg Med 1995 12 251 254 10.1136/emj.12.4.251 8775950 PMC1342573 · DOI
  11. [12]Chellis M Olson J Augustine J Hamilton G Evaluation of missed diagnoses for patients admitted from the emergency department Acad Emerg Med 2001 8 125 130 10.1111/j.1553-2712.2001.tb01276.x 11157287 · DOI
  12. [13]Kachalia A Gandhi TK Puopolo AL Yoon C Thomas EJ Griffey R Missed and delayed diagnoses in the emergency department: a study of closed malpractice claims from 4 liability insurers Ann Emerg Med 2007 49 196 205 10.1016/j.annemergmed.2006.06.035 16997424 · DOI
  13. [14]Harada T, Miyagami T, Watari T, Kawahigashi T, Harada Y, Shikino K, et al. Barriers to diagnostic error reduction in Japan. Diagnosis (Berl). 2021. 10.1515/dx-2021-0055. 34187115 · DOI
  14. [15]Harada T Miyagami T Watari T Hiyoshi T Kunitomo K Tsuji T Analysis of diagnostic error cases among Japanese residents using diagnosis error evaluation and research taxonomy J Gen Fam Med 2021 22 96 99 10.1002/jgf2.388 33717785 PMC7921344 · DOI
  15. [16]Schnapp BH Sun JE Kim JL Strayer RJ Shah KH Cognitive error in an academic emergency department Diagnosis (Berl) 2018 5 135 142 10.1515/dx-2018-0011 30016277 · DOI
  16. [18]Campbell SG Croskerry P Bond WF Profiles in patient safety: a "perfect storm" in the emergency department Acad Emerg Med 2007 14 743 749 17538077
  17. [19]Croskerry P Achieving quality in clinical decision making: cognitive strategies and detection of bias Acad Emerg Med 2002 9 1184 1204 10.1197/aemj.9.11.1184 12414468 · DOI · Paper page
  18. [20]Watari T Tokuda Y Amano Y Onigata K Kanda H Cognitive bias and diagnostic errors among physicians in Japan: a self-reflection survey Int J Environ Res Public Health 2022 19 8 4645 10.3390/ijerph19084645 35457511 PMC9032995 · DOI
  19. [21]Halsey T Johnson MI Jones G Epiphyseal stress fractures of the fingers in an adolescent climber: a potential “Maslow’s hammer” in terms of clinical reasoning Curr Sports Med Rep 2019 18 431 433 10.1249/JSR.0000000000000658 31834172 · DOI
  20. [22]Lee R The law of the instrument J Thorac Cardiovasc Surg 2015 150 167 168 10.1016/j.jtcvs.2015.05.019 26126464 · DOI
  21. [23]Kanda Y Investigation of the freely available easy-to-use software ‘EZR’ for medical statistics Bone Marrow Transplant 2013 48 452 458 10.1038/bmt.2012.244 23208313 PMC3590441 · DOI
  22. [24]Watari T Tokuda Y Mitsuhashi S Otuki K Kono K Nagai N Factors and impact of physicians' diagnostic errors in malpractice claims in Japan PLoS One 2020 15 e0237145 10.1371/journal.pone.0237145 32745150 PMC7398551 · DOI
  23. [25]Pines JM Profiles in patient safety: confirmation bias in emergency medicine Acad Emerg Med 2006 13 90 94 10.1111/j.1553-2712.2006.tb00990.x 16365325 · DOI
  24. [26]Berner ES Graber ML Overconfidence as a cause of diagnostic error in medicine Am J Med 2008 121 5 S2 23 10.1016/j.amjmed.2008.01.001 18440350 · DOI · Paper page
  25. [28]Daniel M Khandelwal S Santen SA Malone M Croskerry P Cognitive debiasing strategies for the emergency department AEM Educ Train 2017 1 41 42 10.1002/aet2.10010 30051007 PMC6001502 · DOI
  26. [29]Pines JM Strong A Cognitive biases in emergency physicians: a pilot study J Emerg Med 2019 57 168 172 10.1016/j.jemermed.2019.03.048 31126674 · DOI
  27. [30]O'Sullivan ED Schofield SJ Cognitive bias in clinical medicine J R Coll Physicians Edinb 2018 48 225 232 10.4997/jrcpe.2018.306 30191910 · DOI · Paper page
  28. [31]Croskerry P Singhal G Mamede S Cognitive debiasing 1: origins of bias and theory of debiasing BMJ Qual Saf 2013 22 Suppl 2:ii58–64 PMC3786658 23882089
  29. [32]Hartigan S Brooks M Hartley S Miller RE Santen SA Hemphill RR Review of the basics of cognitive error in emergency medicine: still no easy answers West J Emerg Med 2020 21 125 131 10.5811/westjem.2020.7.47832 33207157 PMC7673867 · DOI
  30. [34]Newman-Toker DE Wang Z Zhu Y Nassery N Saber Tehrani AS Schaffer AC Rate of diagnostic errors and serious misdiagnosis-related harms for major vascular events, infections, and cancers: toward a national incidence estimate using the “big three” Diagnosis (Berl) 2021 8 67 84 10.1515/dx-2019-0104 32412440 · DOI
  31. [35]Edlow JA Caplan LR Avoiding pitfalls in the diagnosis of subarachnoid hemorrhage N Engl J Med 2000 342 29 36 10.1056/NEJM200001063420106 10620647 · DOI
  32. [36]Oh SY Lim YC Shim YS Song J Park SK Sim SY Initial misdiagnosis of aneurysmal subarachnoid hemorrhage: associating factors and its prognosis Acta Neurochir 2018 160 1105 1113 10.1007/s00701-018-3552-6 29675720 · DOI
  33. [37]Hautz WE Kämmer JE Hautz SC Sauter TC Zwaan L Exadaktylos AK Diagnostic error increases mortality and length of hospital stay in patients presenting through the emergency room Scand J Trauma Resusc Emerg Med 2019 27 54 10.1186/s13049-019-0629-z 31068188 PMC6505221 · DOI · Paper page
  34. [38]Daniel M Carney M Khandelwal S Merritt C Cole M Malone M Cognitive debiasing strategies: a faculty development workshop for clinical teachers in emergency medicine MedEdPORTAL 2017 13 10646 10.15766/mep_2374-8265.10646 30800847 PMC6338148 · DOI

Authors
Kunitomo, K., Harada, T., & Watari, T.
Affiliations
  • Kumamoto Medical Center (JP)
  • Koto Hospital (JP)
  • Shimane University (JP)
Corresponding author
Watari, Takashi
Venue
BMC Emergency Medicine
Published
2022-08-26
Volume
22
Issue
1
Pages
148-148
ISSN
1471-227X (ISSN-L)
OpenAlex
W4293230553
Cited by
49
References
40
Citations by year
2026: 21 · 2025: 15 · 2024: 7 · 2023: 6
FWCI
8.30
Type
journal article
Language
en
Open access
Locations
  • BMC Emergency Medicine (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Institutional Repositories DataBase (IRDB) (submittedVersion, cc-by)
Funders
Japan Society for the Promotion of Science (20H03913)
Topics
  • Health Sciences › Medicine › Family Practice › Clinical Reasoning and Diagnostic Skills
  • Health Sciences › Health Professions › Emergency Medical Services › Patient Safety and Medication Errors
  • Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
Keywords
diagnostic errors, cognitive biases, emergency physicians, overconfidence, confirmation bias, anchoring effect, availability bias, missed diagnosis, trauma (physical injury), cardiovascular disease, stroke, upper gastrointestinal diseases, primary headache, medical safety
MeSH terms
Cardiovascular Diseases, Cognition, Diagnostic Errors, Emergency Service, Hospital, Humans, Physicians, Bias

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