Cognitive biases associated with medical decisions: a systematic review

Gustavo Saposnik, Donald Redelmeier, Christian C Ruff, Philippe N Tobler, Gustavo Saposnik, Donald Redelmeier, Christian C Ruff, Philippe N Tobler

Abstract

Background: Cognitive biases and personality traits (aversion to risk or ambiguity) may lead to diagnostic inaccuracies and medical errors resulting in mismanagement or inadequate utilization of resources. We conducted a systematic review with four objectives: 1) to identify the most common cognitive biases, 2) to evaluate the influence of cognitive biases on diagnostic accuracy or management errors, 3) to determine their impact on patient outcomes, and 4) to identify literature gaps.

Methods: We searched MEDLINE and the Cochrane Library databases for relevant articles on cognitive biases from 1980 to May 2015. We included studies conducted in physicians that evaluated at least one cognitive factor using case-vignettes or real scenarios and reported an associated outcome written in English. Data quality was assessed by the Newcastle-Ottawa scale. Among 114 publications, 20 studies comprising 6810 physicians met the inclusion criteria. Nineteen cognitive biases were identified.

Results: All studies found at least one cognitive bias or personality trait to affect physicians. Overconfidence, lower tolerance to risk, the anchoring effect, and information and availability biases were associated with diagnostic inaccuracies in 36.5 to 77 % of case-scenarios. Five out of seven (71.4 %) studies showed an association between cognitive biases and therapeutic or management errors. Of two (10 %) studies evaluating the impact of cognitive biases or personality traits on patient outcomes, only one showed that higher tolerance to ambiguity was associated with increased medical complications (9.7 % vs 6.5 %; p = .004). Most studies (60 %) targeted cognitive biases in diagnostic tasks, fewer focused on treatment or management (35 %) and on prognosis (10 %). Literature gaps include potentially relevant biases (e.g. aggregate bias, feedback sanction, hindsight bias) not investigated in the included studies. Moreover, only five (25 %) studies used clinical guidelines as the framework to determine diagnostic or treatment errors. Most studies (n = 12, 60 %) were classified as low quality.

Conclusions: Overconfidence, the anchoring effect, information and availability bias, and tolerance to risk may be associated with diagnostic inaccuracies or suboptimal management. More comprehensive studies are needed to determine the prevalence of cognitive biases and personality traits and their potential impact on physicians' decisions, medical errors, and patient outcomes.

Keywords: Case-scenarios; Cognition; Cognitive bias; Decision making; Personality traits; Physicians; Systematic review.

Figures

Fig. 1
Fig. 1
A model for diagnostic reasoning based on dual-process theory (from Ely et al. with permission).[9] System 1 thinking can be influenced by multiple factors, many of them subconscious (emotional polarization toward the patient, recent experience with the diagnosis being considered, specific cognitive or affective biases), and is therefore represented with multiple channels, whereas system 2 processes are, in a given instance, single-channeled and linear. System 2 overrides system 1 (executive override) when physicians take a time-out to reflect on their thinking, possibly with the help of checklists. In contrast, system 1 may irrationally override system 2 when physicians insist on going their own way (e.g., ignoring evidence-based clinical decision rules that can usually outperform them). Notes: Dysrationalia denotes the inability to think rationally despite adequate intelligence. “Calibration” denotes the degree to which the perceived and actual diagnostic accuracy correspond
Fig. 2
Fig. 2
PRISMA flow diagram
Fig. 3
Fig. 3
Prevalence of most common cognitive biases as reported by different studies. Numbers represent percentages reflecting the frequency of the cognitive factor/bias. Panel a represent the prevalence of the framing effect. Panel b represent the prevalence of prevalence of tolerance to risk and ambiguity. Panel c represents the prevalence of overconfidence. Overall, overconfidence and low tolerance to risk or ambiguity were found in 50-70 % of participants, whereas a wide variation was found for the framing effect
Fig. 4
Fig. 4
Prevalence of cognitive biases in the top three most comprehensive studies [39, 50, 52] Numbers represent percentages reflecting the frequency of the cognitive bias. Note the wide variation in the prevalence of cognitive biases across studies
Fig. 5
Fig. 5
Outcome measures of studies evaluating cognitive biases. Numbers represent percentages. Total number of studies = 20. Note that 30 % of studies are descriptive and 35 % target diagnostic accuracy. Only few studies evaluated medical management, treatment, hospitalization or prognosis

References

    1. Classen DC, Pestotnik SL, Evans RS, Burke JP. Computerized surveillance of adverse drug events in hospital patients. JAMA. 1991;266(20):2847–51. doi: 10.1001/jama.1991.03470200059035.
    1. Bates DW, Cullen DJ, Laird N, Petersen LA, Small SD, Servi D, Laffel G, Sweitzer BJ, Shea BF, Hallisey R, et al. Incidence of adverse drug events and potential adverse drug events. Implications for prevention. ADE Prevention Study Group. JAMA. 1995;274(1):29–34. doi: 10.1001/jama.1995.03530010043033.
    1. Andel C, Davidow SL, Hollander M, Moreno DA. The economics of health care quality and medical errors. J Health Care Finance. 2012;39(1):39–50.
    1. OECD. Health at a Glance 2013: OECD Indicators, OECD Publishing. 2013..
    1. Ioannidis JP, Lau J. Evidence on interventions to reduce medical errors: an overview and recommendations for future research. J Gen Intern Med. 2001;16(5):325–34. doi: 10.1046/j.1525-1497.2001.00714.x.
    1. Tversky A, Kahneman D. Judgment under Uncertainty: Heuristics and Biases. Science. 1974;185(4157):1124–31. doi: 10.1126/science.185.4157.1124.
    1. Mamede S, van Gog T, van den Berge K, van Saase JL, Schmidt HG. Why do doctors make mistakes? A study of the role of salient distracting clinical features. Acad Med. 2014;89(1):114–20. doi: 10.1097/ACM.0000000000000077.
    1. van den Berge K, Mamede S. Cognitive diagnostic error in internal medicine. Eur J Intern Med. 2013;24(6):525–9. doi: 10.1016/j.ejim.2013.03.006.
    1. Ely JW, Graber ML, Croskerry P. Checklists to reduce diagnostic errors. Acad Med. 2011;86(3):307–13. doi: 10.1097/ACM.0b013e31820824cd.
    1. Dhillon BS. Human errors: a review. Microelectron Reliab. 1989;29(3):299–304. doi: 10.1016/0026-2714(89)90612-4.
    1. Stripe SC, Best LG, Cole-Harding S, Fifield B, Talebdoost F. Aviation model cognitive risk factors applied to medical malpractice cases. J Am Board Fam Med. 2006;19(6):627–32. doi: 10.3122/jabfm.19.6.627.
    1. Chassin MR. Is health care ready for Six Sigma quality? Milbank Q. 1998;76(4):565–91. doi: 10.1111/1468-0009.00106.
    1. Corn JB. Six sigma in health care. Radiol Technol. 2009;81(1):92–5.
    1. Zeltser MV, Nash DB. Approaching the evidence basis for aviation-derived teamwork training in medicine. Am J Med Qual. 2010;25(1):13–23. doi: 10.1177/1062860609345664.
    1. Ballard S-B. The U.S. commercial air tour industry: a review of aviation safety concerns. Aviat Space Environ Med. 2014;85(2):160–6. doi: 10.3357/ASEM.3814.2014.
    1. Kern KB, Hilwig RW, Berg RA, Sanders AB, Ewy GA. Importance of continuous chest compressions during cardiopulmonary resuscitation: improved outcome during a simulated single lay-rescuer scenario. Circulation. 2002;105(5):645–9. doi: 10.1161/hc0502.102963.
    1. Collicott PE, Hughes I. Training in advanced trauma life support. JAMA. 1980;243(11):1156–9. doi: 10.1001/jama.1980.03300370030022.
    1. Michaels AD, Spinler SA, Leeper B, Ohman EM, Alexander KP, Newby LK, Ay H, Gibler WB, American Heart Association Acute Cardiac Care Committee of the Council on Clinical Cardiology, Outcomes Research et al. Medication errors in acute cardiovascular and stroke patients: a scientific statement from the American Heart Association. Circulation. 2010;121(14):1664–82. doi: 10.1161/CIR.0b013e3181d4b43e.
    1. Khoo EM, Lee WK, Sararaks S, Abdul Samad A, Liew SM, Cheong AT, Ibrahim MY, Su SH, Mohd Hanafiah AN, Maskon K, et al. Medical errors in primary care clinics--a cross sectional study. BMC Fam Pract. 2012;13:127. doi: 10.1186/1471-2296-13-127.
    1. Jenkins RH, Vaida AJ. Simple strategies to avoid medication errors. Fam Pract Manag. 2007;14(2):41–7.
    1. Marewski JN, Gigerenzer G. Heuristic decision making in medicine. Dialogues Clin Neurosci. 2012;14(1):77–89.
    1. Wegwarth O, Schwartz LM, Woloshin S, Gaissmaier W, Gigerenzer G. Do physicians understand cancer screening statistics? A national survey of primary care physicians in the United States. Ann Intern Med. 2012;156(5):340–9. doi: 10.7326/0003-4819-156-5-201203060-00005.
    1. Elstein AS. Analytic methods and medical education. Problems and prospects. Med Decis Making. 1983;3(3):279–84. doi: 10.1177/0272989X8300300303.
    1. Elstein AS. Clinical judgment: psychological research and medical practice. Science. 1976;194(4266):696–700. doi: 10.1126/science.982034.
    1. Blumenthal-Barby J, Krieger H. Cognitive biases and heuristics in medical decision making: a critical review using a systematic search strategy. Med Decis Making. 2015;35(4):539–57. doi: 10.1177/0272989X14547740.
    1. Croskerry P. The importance of cognitive errors in diagnosis and strategies to minimize them. Acad Med. 2003;78(8):775–80. doi: 10.1097/00001888-200308000-00003.
    1. Peabody JW, Luck J, Glassman P, Jain S, Hansen J, Spell M, Lee M. Measuring the quality of physician practice by using clinical vignettes: a prospective validation study. Ann Intern Med. 2004;141(10):771–80. doi: 10.7326/0003-4819-141-10-200411160-00008.
    1. Eva KW. What every teacher needs to know about clinical reasoning. Med Educ. 2005;39(1):98–106. doi: 10.1111/j.1365-2929.2004.01972.x.
    1. Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gotzsche PC, Ioannidis JP, Clarke M, Devereaux PJ, Kleijnen J, Moher D. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. Ann Intern Med. 2009;151(4):W65–94. doi: 10.7326/0003-4819-151-4-200908180-00136.
    1. Meyer AN, Payne VL, Meeks DW, Rao R, Singh H. Physicians’ diagnostic accuracy, confidence, and resource requests: a vignette study. JAMA Intern Med. 2013;173(21):1952–8. doi: 10.1001/jamainternmed.2013.10081.
    1. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. [In ]
    1. Cochrane handbook for systematic reviews of interventions version 5.1.0 [updated March 2011] [In ]
    1. Shi Q, MacDermid J, Santaguida L, Kyu HH: Predictors of surgical outcomes following anterior transposition of ulnar nerve for cubital tunnel syndrome: A systematic review. J Hand Surg Am. 2011;36(12):1996–2001.e1–6. doi:10.1016/j.jhsa.2011.09.024.
    1. Mamede S, Splinter TA, van Gog T, Rikers RM, Schmidt HG. Exploring the role of salient distracting clinical features in the emergence of diagnostic errors and the mechanisms through which reflection counteracts mistakes. BMJ Qual Saf. 2012;21(4):295–300. doi: 10.1136/bmjqs-2011-000518.
    1. Mamede S, van Gog T, van den Berge K, Rikers RM, van Saase JL, van Guldener C, Schmidt HG. Effect of availability bias and reflective reasoning on diagnostic accuracy among internal medicine residents. JAMA. 2010;304(11):1198–203. doi: 10.1001/jama.2010.1276.
    1. Msaouel P, Kappos T, Tasoulis A, Apostolopoulos AP, Lekkas I, Tripodaki ES, Keramaris NC. Assessment of cognitive biases and biostatistics knowledge of medical residents: a multicenter, cross-sectional questionnaire study. Med Educ Online. 2014;19:23646. doi: 10.3402/meo.v19.23646.
    1. Ross S, Moffat K, McConnachie A, Gordon J, Wilson P. Sex and attitude: a randomized vignette study of the management of depression by general practitioners. Br J Gen Pract. 1999;49(438):17–21.
    1. Perneger TV, Agoritsas T. Doctors and patients’ susceptibility to framing bias: a randomized trial. J Gen Intern Med. 2011;26(12):1411–7. doi: 10.1007/s11606-011-1810-x.
    1. Ogdie AR, Reilly JB, Pang WG, Keddem S, Barg FK, Von Feldt JM, Myers JS. Seen through their eyes: residents’ reflections on the cognitive and contextual components of diagnostic errors in medicine. Acad Med. 2012;87(10):1361–7. doi: 10.1097/ACM.0b013e31826742c9.
    1. Friedman C, Gatti G, Elstein A, Franz T, Murphy G, Wolf F. Are clinicians correct when they believe they are correct? Implications for medical decision support. Stud Health Technol Inform. 2001;84(Pt 1):454–8.
    1. Baldwin RL, Green JW, Shaw JL, Simpson DD, Bird TM, Cleves MA, Robbins JM. Physician risk attitudes and hospitalization of infants with bronchiolitis. Acad Emerg Med. 2005;12(2):142–6. doi: 10.1111/j.1553-2712.2005.tb00852.x.
    1. Reyna VF, Lloyd FJ. Physician decision making and cardiac risk: effects of knowledge, risk perception, risk tolerance, and fuzzy processing. J Exp Psychol Appl. 2006;12(3):179–95. doi: 10.1037/1076-898X.12.3.179.
    1. Yee LM, Liu LY, Grobman WA. The relationship between obstetricians’ cognitive and affective traits and their patients’ delivery outcomes. Am J Obstet Gynecol. 2014;211(6):692 e691–696. doi: 10.1016/j.ajog.2014.06.003.
    1. Graber MA, Bergus G, Dawson JD, Wood GB, Levy BT, Levin I. Effect of a patient’s psychiatric history on physicians’ estimation of probability of disease. J Gen Intern Med. 2000;15(3):204–6. doi: 10.1046/j.1525-1497.2000.04399.x.
    1. Bytzer P. Information bias in endoscopic assessment. Am J Gastroenterol. 2007;102(8):1585–7. doi: 10.1111/j.1572-0241.2006.00911.x.
    1. Sorum PC, Shim J, Chasseigne G, Bonnin-Scaon S, Cogneau J, Mullet E. Why do primary care physicians in the United States and France order prostate-specific antigen tests for asymptomatic patients? Med Decis Making. 2003;23(4):301–13. doi: 10.1177/0272989X03256010.
    1. Redelmeier DA, Shafir E. Medical decision making in situations that offer multiple alternatives. JAMA. 1995;273(4):302–5. doi: 10.1001/jama.1995.03520280048038.
    1. Dibonaventura M, Chapman GB. Do decision biases predict bad decisions? Omission bias, naturalness bias, and influenza vaccination. Med Decis Making. 2008;28(4):532–9. doi: 10.1177/0272989X08315250.
    1. Saposnik G, Cote R, Mamdani M, Raptis S, Thorpe KE, Fang J, Redelmeier DA, Goldstein LB. JURaSSiC: Accuracy of clinician vs risk score prediction of ischemic stroke outcomes. Neurol. 2013;81(5):448–55. doi: 10.1212/WNL.0b013e31829d874e.
    1. Stiegler MP, Ruskin KJ. Decision-making and safety in anesthesiology. Curr Opin Anaesthesiol. 2012;25(6):724–9.
    1. Gupta M, Schriger DL, Tabas JA. The presence of outcome bias in emergency physician retrospective judgments of the quality of care. Ann Emerg Med. 2011;57(4):323–8. doi: 10.1016/j.annemergmed.2010.10.004.
    1. Crowley RS, Legowski E, Medvedeva O, Reitmeyer K, Tseytlin E, Castine M, Jukic D, Mello-Thoms C. Automated detection of heuristics and biases among pathologists in a computer-based system. Adv Health Sci Educ Theory Pract. 2013;18(3):343–63. doi: 10.1007/s10459-012-9374-z.
    1. Mamede S, Schmidt HG, Rikers RM, Custers EJ, Splinter TA, van Saase JL. Conscious thought beats deliberation without attention in diagnostic decision-making: at least when you are an expert. Psychol Res. 2010;74(6):586–92. doi: 10.1007/s00426-010-0281-8.
    1. Zwaan L, Thijs A, Wagner C, van der Wal G, Timmermans DR. Relating faults in diagnostic reasoning with diagnostic errors and patient harm. Acad Med. 2012;87(2):149–56. doi: 10.1097/ACM.0b013e31823f71e6.
    1. Graber ML, Kissam S, Payne VL, Meyer AN, Sorensen A, Lenfestey N, Tant E, Henriksen K, Labresh K, Singh H. Cognitive interventions to reduce diagnostic error: a narrative review. BMJ Qual Saf. 2012;21(7):535–57. doi: 10.1136/bmjqs-2011-000149.
    1. Balla JI, Heneghan C, Glasziou P, Thompson M, Balla ME. A model for reflection for good clinical practice. J Eval Clin Pract. 2009;15(6):964–9. doi: 10.1111/j.1365-2753.2009.01243.x.
    1. Raab M, Gigerenzer G. The power of simplicity: a fast-and-frugal heuristics approach to performance science. Front Psychol. 2015;6:1672. doi: 10.3389/fpsyg.2015.01672.
    1. Elwyn G, Thompson R, John R, Grande SW. Developing IntegRATE: a fast and frugal patient-reported measure of integration in health care delivery. Int J Integr Care. 2015;15:e008. doi: 10.5334/ijic.1597.
    1. Hyman DJ, Pavlik VN, Greisinger AJ, Chan W, Bayona J, Mansyur C, Simms V, Pool J. Effect of a physician uncertainty reduction intervention on blood pressure in uncontrolled hypertensives--a cluster randomized trial. J Gen Intern Med. 2012;27(4):413–9. doi: 10.1007/s11606-011-1888-1.
    1. Kachalia A, Mello MM. Defensive medicine—legally necessary but ethically wrong?: Inpatient stress testing for chest pain in low-risk patients. JAMA Intern Med. 2013;173(12):1056–7. doi: 10.1001/jamainternmed.2013.7293.
    1. Smith TR, Habib A, Rosenow JM, Nahed BV, Babu MA, Cybulski G, Fessler R, Batjer HH, Heary RF. Defensive medicine in neurosurgery: does state-level liability risk matter? Neurosurg. 2015;76(2):105–13. doi: 10.1227/NEU.0000000000000576.
    1. Bhatia RS, Levinson W, Shortt S, Pendrith C, Fric-Shamji E, Kallewaard M, Peul W, Veillard J, Elshaug A, Forde I, et al. Measuring the effect of Choosing Wisely: an integrated framework to assess campaign impact on low-value care. BMJ Qual Saf. 2015;24(8):523–31. doi:10.1136/bmjqs-2015-004070.
    1. Levinson W, Huynh T. Engaging physicians and patients in conversations about unnecessary tests and procedures: Choosing Wisely Canada. CMAJ. 2014;186(5):325–6. doi: 10.1503/cmaj.131674.
    1. Kallberg AS, Goransson KE, Ostergren J, Florin J, Ehrenberg A. Medical errors and complaints in emergency department care in Sweden as reported by care providers, healthcare staff, and patients - a national review. Eur J Emerg Med. 2013;20(1):33–8. doi: 10.1097/MEJ.0b013e32834fe917.
    1. Studdert DM, Mello MM, Gawande AA, Gandhi TK, Kachalia A, Yoon C, Puopolo AL, Brennan TA. Claims, errors, and compensation payments in medical malpractice litigation. N Engl J Med. 2006;354(19):2024–33. doi: 10.1056/NEJMsa054479.
    1. Hartling L, Milne A, Hamm MP, Vandermeer B, Ansari M, Tsertsvadze A, Dryden DM. Testing the Newcastle Ottawa Scale showed low reliability between individual reviewers. J Clin Epidemiol. 2013;66(9):982–93. doi: 10.1016/j.jclinepi.2013.03.003.
    1. Lo CK, Mertz D, Loeb M. Newcastle-Ottawa Scale: comparing reviewers’ to authors’ assessments. BMC Med Res Methodol. 2014;14:45. doi: 10.1186/1471-2288-14-45.
    1. Stangierski A, Warmuz-Stangierska I, Ruchala M, Zdanowska J, Glowacka MD, Sowinski J, Ruchala P. Medical errors - not only patients’ problem. Arch Med Sci. 2012;8(3):569–74. doi: 10.5114/aoms.2012.29539.
    1. Graber ML. The incidence of diagnostic error in medicine. BMJ Qual Saf. 2013;22 Suppl 2:ii21–7. doi: 10.1136/bmjqs-2012-001615.

Source: PubMed

Sponsors en medewerkers

Medische omstandigheden

Geneesmiddelinterventies

3
Abonneren