Medicine and heuristics: cognitive biases and medical decision-making



Clinical decision-making is a daily practice conducted by medical practitioners, yet the processes surrounding it are poorly understood. The influence of ‘shortcuts’ in clinical decision-making, known as heuristics, remains unknown. This paper explores heuristics and the valuable role they play in medical practice, as well as offering potential solutions to minimize the risk of incorrect decision-making.


The quasi-systematic review was conducted according to modified PRISMA guidelines utilizing the electronic databases Medline, Embase and Cinahl. All English language papers including bias and the medical profession were included. Papers with evidence from other healthcare professions were included if medical practitioners were in the study sample.


The most common decisional shortcuts used in medicine are the Availability, Anchoring and Confirmatory heuristics. The Representativeness, Overconfidence and Bandwagon effects are also prevalent in medical practice. Heuristics are mostly positive but can also result in negative consequences if not utilized appropriately. Factors such as personality and level of experience may influence a doctor’s use of heuristics. Heuristics are influenced by the context and conditions in which they are performed. Mitigating strategies such as reflective practice and technology may reduce the likelihood of inappropriate use.


It remains unknown if heuristics are primarily positive or negative for clinical decision-making. Future efforts should assess heuristics in real-time and controlled trials should be applied to assess the potential impact of mitigating factors in reducing the negative impact of heuristics and optimizing their efficiency for positive outcomes.

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Fig. 1


  1. 1.

    Tversky A, Kahneman D (1974) Judgment under uncertainty: heuristics and biases. Science 185(4157):1124–1131

    CAS  PubMed  Google Scholar 

  2. 2.

    Kohn LT, Corrigan J, Donaldson MS (2000) To err is human: building a safer health system, vol 6. National academy press, Washington, DC

    Google Scholar 

  3. 3.

    Andel C, Davidow SL, Hollander M, Moreno DA (2012) The economics of health care quality and medical errors. J Health Care Finance 39(1):39

    PubMed  Google Scholar 

  4. 4.

    Shreve J, Van Den Bos J, Gray T, Halford M, Rustagi K, Ziemkiewicz E, 2010 The economic measurement of medical errors sponsored by society of actuaries’ health section. Milliman Inc. Link available at: Accessed 25 Apr 2020

  5. 5.

    Goel V, Dolan RJ (2003) Explaining modulation of reasoning by belief. Cognition 87(1):B11–B22

    PubMed  Google Scholar 

  6. 6.

    Bell DE, Raiffa H, Tversky A (1988) Descriptive, normative, and prescriptive interactions in decision making. Decis Mak 1:9–32

    Google Scholar 

  7. 7.

    Simon HA (1990) Bounded rationality. In: Utility and probability. Palgrave Macmillan, London, pp 15–18

    Google Scholar 

  8. 8.

    Rieskamp J, Otto PE (2006) SSL: a theory of how people learn to select strategies. J Exp Psychol Gen 135(2):207

    PubMed  Google Scholar 

  9. 9.

    Keys DJ, Schwartz B (2007) “Leaky” rationality: how research on behavioral decision making challenges normative standards of rationality. Perspect Psychol Sci 2(2):162–180

    PubMed  Google Scholar 

  10. 10.

    Gigerenzer G (2007) Gut feelings: the intelligence of the unconscious, Penguin Books, New York

  11. 11.

    Wegwarth O, Schwartz LM, Woloshin S, Gaissmaier W, Gigerenzer G (2012) Do physicians understand cancer screening statistics? A national survey of primary care physicians in the United States. Ann Intern Med 156(5):340–349

    PubMed  Google Scholar 

  12. 12.

    Blumenthal-Barby JS, Krieger H (2015) Cognitive biases and heuristics in medical decision making: a critical review using a systematic search strategy. Med Decis Mak 35(4):539–557

    CAS  Google Scholar 

  13. 13.

    Stiegler MP, Tung A (2014) Cognitive processes in anesthesiology decision making. Anesthesiology 120(1):204–217

    PubMed  Google Scholar 

  14. 14.

    Croskerry P (2002) Achieving quality in clinical decision making: cognitive strategies and detection of bias. Acad Emerg Med 9(11):1184–1204

    PubMed  Google Scholar 

  15. 15.

    Mamede S, Van Gog T, Van Den Berge K, Van Saase JL, Schmidt HG (2014) Why do doctors make mistakes? A study of the role of salient distracting clinical features. Acad Med 89(1):114–120

    PubMed  Google Scholar 

  16. 16.

    Marewski JN, Gigerenzer G (2012) Heuristic decision making in medicine. Dialogues Clin Neurosci 14(1):77

    PubMed  PubMed Central  Google Scholar 

  17. 17.

    Van den Berge K, Mamede S (2013) Cognitive diagnostic error in internal medicine. Eur J Int Med 24(6):525–529

    Google Scholar 

  18. 18.

    Ely JW, Graber ML, Croskerry P (2011) Checklists to reduce diagnostic errors. Acad Med 86(3):307–313

    PubMed  Google Scholar 

  19. 19.

    Elstein AS (1999) Heuristics and biases: selected errors in clinical reasoning. Acad Med 74(7):791–794

    CAS  PubMed  Google Scholar 

  20. 20.

    Dawson NV (1993) Physician judgment in clinical settings: methodological influences and cognitive performance. Clin Chem 39(7):1468–1478

    CAS  PubMed  Google Scholar 

  21. 21.

    Dawson NV, Arkes HR (1987) Systematic errors in medical decision making. J Gen Intern Med 2(3):183–187

    CAS  PubMed  Google Scholar 

  22. 22.

    Sweller J, Chandler P (1991) Evidence for cognitive load theory. Cogn Instr 8(4):351–362

    Google Scholar 

  23. 23.

    Saposnik G, Redelmeier D, Ruff CC, Tobler PN (2016) Cognitive biases associated with medical decisions: a systematic review. BMC Med Inform Decis Making 16(1):138

    Google Scholar 

  24. 24.

    Croskerry P (2003) The importance of cognitive errors in diagnosis and strategies to minimize them. Acad Med 78(8):776

    Google Scholar 

  25. 25.

    Mamede S, van Gog T, van den Berge K, Rikers RM, van Saase JL, van Guldener C, Schmidt HG (2010) Effect of availability bias and reflective reasoning on diagnostic accuracy among internal medicine residents. JAMA 304(11):1198–1203

    CAS  PubMed  Google Scholar 

  26. 26.

    Ogdie AR, Reilly JB, Pang MWG, Keddem MS, Barg FK, Von Feldt JM, Myers JS (2012) Seen through their eyes: residents’ reflections on the cognitive and contextual components of diagnostic errors in medicine. Acad Med 87(10):1361

    PubMed  PubMed Central  Google Scholar 

  27. 27.

    Crowley RS, Legowski E, Medvedeva O, Reitmeyer K, Tseytlin E, Castine M, Jukic D, Mello-Thoms C (2013) Automated detection of heuristics and biases among pathologists in a computer-based system. Adv Health Sci Educ 18(3):343–363

    Google Scholar 

  28. 28.

    Perneger TV, Agoritsas T (2011) Doctors and patients’ susceptibility to framing bias: a randomized trial. J Gen Intern Med 26(12):1411–1417

    PubMed  PubMed Central  Google Scholar 

  29. 29.

    Yee LM, Liu LY, Grobman WA (2014) The relationship between obstetricians’ cognitive and affective traits and their patients’ delivery outcomes. Am J Obstetr Gynaecol 211(6):692–6e1

    Google Scholar 

  30. 30.

    Sorum PC, Shim J, Chasseigne G, Bonnin-Scaon S, Cogneau J, Mullet E (2003) Why do primary care physicians in the United States and France order prostate-specific antigen tests for asymptomatic patients? Med Decis Mak 23(4):301–313

    Google Scholar 

  31. 31.

    Seda MC, U.S.N (2008) Look out doctor, you may be getting framed: heuristics in medical decision-making. Mil Med 173(9):2

    Google Scholar 

  32. 32.

    Colman A, Group think: bandwagon effect. 2003. In: Oxford Dictionary of Psychology. Oxford University Press, New York, p. 77

  33. 33.

    Kahneman D, Tversky A (2013) Choices, values, and frames. In: Handbook of the Fundamentals of Financial Decision Making: Part I, pp 269–278

    Google Scholar 

  34. 34.

    Malterud K (2002) Reflexivity and metapositions: strategies for appraisal of clinical evidence. J Eval Clin Pract 8(2):121–126

    PubMed  Google Scholar 

  35. 35.

    Kalf AJ, Spruijt-Metz D (1996) Variation in diagnoses: influence of specialists’ training on selecting and ranking relevant information in geriatric case vignettes. Soc Sci Med 42(5):705–712

    CAS  PubMed  Google Scholar 

  36. 36.

    Sugarman DB (1986) Active versus passive euthanasia: an attributional analysis 1. J Appl Soc Psychol 16(1):60–76

    Google Scholar 

  37. 37.

    Kempainen RR, Migeon MB, Wolf FM (2003) Understanding our mistakes: a primer on errors in clinical reasoning. Med Teach 25(2):177

    PubMed  Google Scholar 

  38. 38.

    McDonald CJ (1996) Medical heuristics: the silent adjudicators of clinical practice. Ann Intern Med 124(1_Part_1):56–62

    CAS  PubMed  Google Scholar 

  39. 39.

    Nakata Y, Okuno-Fujiwara M, Goto T, Morita S (2000) Risk attitudes of anesthesiologists and surgeons in clinical decision making with expected years of life. J Clin Anesth 12(2):146–150

    CAS  PubMed  Google Scholar 

  40. 40.

    Hall JC, Ellis C, Hamdorf J (2003) Surgeons and cognitive processes. Br J Surg 90(1):10–16

    CAS  PubMed  Google Scholar 

  41. 41.

    Murray DJ, Freeman BD, Boulet JR, Woodhouse J, Fehr JJ, Klingensmith ME (2015) Decision making in trauma settings: simulation to improve diagnostic skills. Simul Healthc 10(3):139–145

    PubMed  Google Scholar 

  42. 42.

    Collicott PE, Hughes I (1980) Training in advanced trauma life support. JAMA 243(11):1156–1159

    CAS  PubMed  Google Scholar 

  43. 43.

    Kern KB, Hilwig RW, Berg RA, Sanders AB, Ewy GA (2002) Importance of continuous chest compressions during cardiopulmonary resuscitation: improved outcome during a simulated single lay-rescuer scenario. Circulation 105(5):645–649

    PubMed  Google Scholar 

  44. 44.

    Reason J (1990) Human error. Cambridge university press

  45. 45.

    Custers EJ (2015) Thirty years of illness scripts: theoretical origins and practical applications. Med Teach 37(5):457–462

    PubMed  Google Scholar 

  46. 46.

    Mamede S, Schmidt HG (2004) The structure of reflective practice in medicine. Med Educ 38(12):1302–1308

    PubMed  Google Scholar 

  47. 47.

    Schön DA (2017) The reflective practitioner: How professionals think in action. Routledge

  48. 48.

    Engel GL (1977) The need for a new medical model: a challenge for biomedicine. Science 196(4286):129–136

    CAS  PubMed  Google Scholar 

  49. 49.

    Klein G (2008) Naturalistic decision making. Hum Factors 50(3):456–460

    PubMed  Google Scholar 

  50. 50. (n.d.) Clinical Decision Making. [online] Available at: Accessed 19 Mar 2019

  51. 51.

    Hyman DJ, Pavlik VN, Greisinger AJ, Chan W, Bayona J, Mansyur C, Simms V, Pool J (2012) Effect of a physician uncertainty reduction intervention on blood pressure in uncontrolled hypertensives—A cluster randomized trial. J Gen Intern Med 27(4):413–419

    PubMed  Google Scholar 

  52. 52.

    Epstein RM (1999) Mindful practice. JAMA 282(9):833–839

    CAS  PubMed  Google Scholar 

  53. 53.

    Graber ML (2013) The incidence of diagnostic error in medicine. BMJ Qual Saf.

  54. 54.

    Newman-Toker DE, Pronovost PJ (2009) Diagnostic errors—the next frontier for patient safety. JAMA 301(10):1060–1062

    CAS  PubMed  Google Scholar 

  55. 55.

    Lynch TG, Woelfl NN, Steele DJ, Hanssen CS (1998) Learning style influences student examination performance. Am J Surg 176(1):62–66

    CAS  PubMed  Google Scholar 

  56. 56.

    Birkmeyer JD, Birkmeyer NOC (1996) Decision analysis in surgery. Surgery 120(1):7–15

    CAS  PubMed  Google Scholar 

  57. 57.

    Bhatt NR, Doherty EM, Mansour E, Traynor O, Ridgway PF (2016) Impact of a clinical decision making module on the attitudes and perceptions of surgical trainees. ANZ J Surg 86(9):660–664

    PubMed  Google Scholar 

  58. 58.

    Woo JK, Ghorayeb SH, Lee CK, Sangha H, Richter S (2004) Effect of patient socioeconomic status on perceptions of first-and second-year medical students. Can Med Assoc J 170(13):1915–1919

    Google Scholar 

  59. 59.

    Ehteshami A, Rezaei P, Tavakoli N, Kasaei M (2013) The role of health information technology in reducing preventable medical errors and improving patient safety. Int J Health Syst Disaster Manag 1(4):195

    Google Scholar 

  60. 60.

    Boss EF, Mehta N, Nagarajan N, Links A, Benke JR, Berger Z, Espinel A, Meier J, Lipstein EA (2016) Shared decision making and choice for elective surgical care: a systematic review. Otolaryngol Head Neck Surg 154(3):405–420

    PubMed  Google Scholar 

  61. 61.

    Légaré F, Stacey D, Turcotte S, Cossi MJ, Kryworuchko J, Graham ID, Lyddiatt A, Politi MC, Thomson R, Elwyn G, Donner‐Banzhoff N (2014) Interventions for improving the adoption of shared decision making by healthcare professionals. Cochrane Database Syst Rev 9

  62. 62.

    Stiggelbout AM, Van der Weijden T, Wit MPTD, Frosch D, Légaré F, Montori VM, Trevena L, Elwyn G (2012) Shared decision making: really putting patients at the centre of healthcare. BMJ 344:e256

    CAS  PubMed  Google Scholar 

  63. 63.

    Mamede S, Schmidt HG, Rikers R (2007) Diagnostic errors and reflective practice in medicine. J Eval Clin Pract 13(1):138–145

    PubMed  Google Scholar 

  64. 64.

    Stiegler MP, Gaba DM (2015) Decision-making and cognitive strategies. Simul Healthc 10(3):133–138

    PubMed  Google Scholar 

  65. 65.

    Smith TR, Habib A, Rosenow JM, Nahed BV, Babu MA, Cybulski G, Fessler R, Batjer HH, Heary RF (2014) Defensive medicine in neurosurgery: does state-level liability risk matter? Neurosurgery 76(2):105–114

    Google Scholar 

  66. 66.

    Kachalia A, Mello MM (2013) Defensive medicine—legally necessary but ethically wrong?: Inpatient stress testing for chest pain in low-risk patients. JAMA

  67. 67.

    Amirian I (2014) The impact of sleep deprivation on surgeons’ performance during night shifts. Dan Med J 61(9):4912

    Google Scholar 

  68. 68.

    Philibert I (2005) Sleep loss and performance in residents and nonphysicians: a metaanalytic examination. Sleep 28(11):1392–1402

    PubMed  Google Scholar 

  69. 69.

    Wesnes KA, Walker MB, Walker LG, Heys SD, White L, Warren R, Eremin O (1997) Cognitive performance and mood after a weekend on call in a surgical unit. Br J Surg 84(4):493–495

    CAS  PubMed  Google Scholar 

  70. 70.

    Hall WJ, Chapman MV, Lee KM, Merino YM, Thomas TW, Payne BK, Eng E, Day SH, Coyne-Beasley T (2015) Implicit racial/ethnic bias among health care professionals and its influence on heal

  71. 71.

    Merrill JM, Camacho Z, Laux LF, Lorimor R, Thornby JI, Vallbona C (1994) Uncertainties and ambiguities: measuring how medical students cope. Med Educ 28(4):316–322

    CAS  PubMed  Google Scholar 

  72. 72.

    Hozo I, Djulbegovic B (2008) When is diagnostic testing inappropriate or irrational? Acceptable regret approach. Med Decis Mak 28(4):540–553

    Google Scholar 

  73. 73.

    Mandelblatt JS, Hadley J, Kerner JF, Schulman KA, Gold K, Dunmore‐Griffith J, Edge S, Guadagnoli E, Lynch JJ, Meropol NJ, Weeks JC (2000) Patterns of breast carcinoma treatment in older women: patient preference and clinical and physician influences. Cancer 89(3):561–573

    CAS  PubMed  Google Scholar 

  74. 74.

    Hall KH (2002) Reviewing intuitive decision‐making and uncertainty: the implications for medical education. Med Educ 36(3):216–224

    PubMed  Google Scholar 

  75. 75.

    Patel VL, Kaufman DR, Arocha JF (2002) Emerging paradigms of cognition in medical decision-making. J Biomed Inform 35(1):52–75 Internal Medicine, 173(12), pp.1056-1057

    PubMed  Google Scholar 

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Author information




DFW conceived and designed the analysis, collected the data, contributed to data analysis and wrote the paper.

KCC contributed to data analysis and tools, assisted in editing the paper and contributed to clinical vignettes.

PFR assisted in conceiving and designing the analysis, assisted in editing the paper and contributed to clinical vignettes.

Corresponding author

Correspondence to Dale F. Whelehan.

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What this paper adds

This paper provides the reader with an overview of some of the most commonly used heuristics in medical practice. It discusses how best to use them in order to maximize positive patient outcomes. It also highlights some potential interventions to mitigate the risk of negative impacts when using them. This ‘toolkit’ will assist in increasing awareness of clinical decision-making models utilized by medical practitioners.

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Whelehan, D.F., Conlon, K.C. & Ridgway, P.F. Medicine and heuristics: cognitive biases and medical decision-making. Ir J Med Sci 189, 1477–1484 (2020).

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  • Cognitive biases
  • Decision-making
  • Diagnostics
  • Medical error