Countering cognitive biases in minimising low value care

Scott, Ian A; Soon, Jason; Elshaug, Adam G; Lindner, Robyn

doi:10.5694/mja16.00999

Topics

Health services administration

General medicine

Summary

Cognitive biases in decision making may make it difficult for clinicians to reconcile evidence of overuse with highly ingrained prior beliefs and intuition.
Such biases can predispose clinicians towards low value care and may limit the impact of recently launched campaigns aimed at reducing such care.
Commonly encountered biases comprise commission bias, illusion of control, impact bias, availability bias, ambiguity bias, extrapolation bias, endowment effects, sunken cost bias and groupthink.
Various strategies may be used to counter such biases, including cognitive huddles, narratives of patient harm, value considerations in clinical assessments, defining acceptable levels of risk of adverse outcomes, substitution, reflective practice and role modelling, normalisation of deviance, nudge techniques and shared decision making.
These debiasing strategies have considerable face validity and, for some, effectiveness in reducing low value care has been shown in randomised trials.

1 Princess Alexandra Hospital, Brisbane, QLD
2 University of Queensland, Brisbane, QLD
3 Royal Australasian College of Physicians, Sydney, NSW
4 Menzies Centre for Health Policy, University of Sydney, Sydney, NSW
5 NPS MedicineWise, Sydney, NSW

Correspondence: ian.scott@health.qld.gov.au

Competing interests:

Ian Scott is a member of the Australian Government Department of Health’s Medicare Benefits Schedule Review Taskforce and is a clinical lead for the Royal Australasian College of Physicians (RACP) EVOLVE program. Jason Soon is Senior Policy Officer at the RACP and is the Lead Policy Officer for the EVOLVE program. Adam Elshaug receives salary support as the HCF Research Foundation Professorial Research Fellow, and holds research grants from the Commonwealth Fund and the National Health and Medical Research Council (no. 1109626 and 1104136). He receives consulting fees from Cancer Australia, the Capital Markets Cooperative Research Centre’s Health Quality Program, NPS MedicineWise (as facilitator of Choosing Wisely Australia), the RACP (as facilitator of the EVOLVE program) and the Australian Commission on Safety and Quality in Health Care, and is a member of the Australian Government Department of Health’s Medicare Benefits Schedule Review Taskforce. Robyn Lindner is the Client Relations Manager at NPS MedicineWise and is involved in the implementation of Choosing Wisely Australia.

1. Blumenthal-Barby JS, Krieger H. Cognitive biases and heuristics in medical decision-making: a critical review using a systematic search strategy. Med Decis Making 2015; 35: 539-557.
2. Gabbay J, le May A. Evidence based guidelines or collectively constructed “mindlines?” Ethnographic study of knowledge management in primary care. BMJ 2004; 329: 1013.
3. Heller RF, Saltzstein HD, Caspe WB. Heuristics in medical and non-medical decision-making. Q J Exp Psychol A 1992; 44: 211-235.
4. Lomas J, Culyer T, McCutcheon C, et al. Conceptualizing and combining evidence for health system guidance. Canadian Health Services Research Foundation: Ottawa, 2005.
5. Dawson NV, Arkes HR. Systematic errors in medical decision making: judgment limitations. J Gen Intern Med 1987; 2: 183-187.
6. Wang MT, Gamble G, Grey A. Responses of specialist societies to evidence for reversal of practice. JAMA Intern Med 2015; 175: 845-848.
7. Ayanian JZ, Berwick DM. Do physicians have a bias toward action? A classic study revisited. Med Decis Making 1991; 11: 154-158.
8. Kanzaria HK, Hoffman JR, Probst MA, et al. Emergency physician perceptions of medically unnecessary advanced diagnostic imaging. Acad Emerg Med 2015; 22: 390-398.
9. Vincent C, Young M, Phillips A. Why do people sue doctors? A study of patients and relatives taking legal action. Lancet 1994; 343: 1609-1613.
10. Alexander M, Christakis NA. Bias and asymmetric loss in expert forecasts: a study of physician prognostic behavior with respect to patient survival. J Health Econom 2008; 27: 1095-1108.
11. Palda VA, Bowman KW, McLean RF, et al. ‘Futile’ care: do we provide it? Why? A semi-structured, Canada-wide survey of intensive care unit doctors and nurses. J Crit Care 2005; 20: 207-213.
12. Graz, B, Wietlisbach V, Porchet F, Vader J-P. Prognosis or “curabo effect”?: physician prediction and patient outcome of surgery for low back pain and sciatica. Spine 2005; 30: 1448-1452.
13. Schroen AT, Detterbeck FC, Crawford R, et al. Beliefs among pulmonologists and thoracic surgeons in the therapeutic approach to non-small cell lung cancer. Chest 2000; 118: 129-137.
14. Imam MA, Barke S, Stafford GH, et al. Loss to follow-up after total hip replacement: a source of bias in patient reported outcome measures and registry datasets? Hip Int 2014; 24: 465-472.
15. Hoffman T, del Mar C. Patients’ expectations of the benefits and harms of treatments, screening, and tests: a systematic review. JAMA Intern Med 2015; 175: 274-286.
16. Hoffman T, del Mar C. Clinicians’ expectations of the benefits and harms of treatments, screening, and tests: a systematic review. JAMA Intern Med 2017; 177: 407-419.
17. Finucane ML, Alhakami A, Slovic P, Johnson SM. The affect heuristic in judgments of risks and benefits. J Behav Decis Mak 2000; 13: 1-17.
18. Perneger TV, Agoritsas T. Doctors and patients’ susceptibility to framing bias: a randomized trial. J Gen Intern Med 2011; 26: 1411-1417.
19. Poses RM, Anthony M. Availability, wishful thinking, and physicians’ diagnostic judgments for patients with suspected bacteremia. Med Decis Making 1991; 11: 159-168.
20. Mold JW, Stein HF. The cascade effect in the clinical care of patients. N Engl J Med 1986; 314: 512-514.
21. Kachalia A, Berg A, Fagerlin A, et al. Overuse of testing in preoperative evaluation and syncope. A survey of hospitalists. Ann Intern Med 2015; 162: 100-108.
22. Rolfe A, Burton C. Reassurance after diagnostic testing with a low pretest probability of serious disease: systematic review and meta-analysis. JAMA Intern Med 2013; 173: 407-416.
23. Djulbegovic B, Paul A. From efficacy to effectiveness in the face of uncertainty: indication creep and prevention creep. JAMA 2011; 305: 2005-2006.
24. Morewedge CK, Giblin CE. Explanations of the endowment effect: an integrative review. Trends Cogn Sci 2015; 19: 339-348.
25. Anderson K, Stowasser D, Freeman C, Scott IA. Prescriber barriers and enablers to minimising potentially inappropriate medications in adults: a systematic review and thematic synthesis. BMJ Open 2014; 4: e006544.
26. Kressel LM, Chapman GB, Leventhal E. The influence of default options on the expression of end-of-life treatment preferences in advance directives. J Gen Intern Med 2007; 22: 1007-1010.
27. Redelmeier DA, Shafir E. Medical decision-making in situations that offer multiple alternatives. JAMA 1995; 273: 302-305.
28. Bornstein BH, Emler AC, Chapman GB. Rationality in medical treatment decisions: is there a sunk-cost effect? Soc Sci Med 1999; 49: 215-222.
29. Mannion R, Thompson C. Systematic biases in group decision-making: implications for patient safety. Int J Qual Health Care 2014; 26: 606-612.
30. Katz D, Detsky AD. Incorporating metacognition into morbidity and mortality rounds: The next frontier in quality improvement. J Hosp Med 2016; 11: 120-122.
31. Moser EM, Huang GC, Packer CD, et al. SOAP-V: Introducing a method to empower medical students to be change agents in bending the cost curve. J Hosp Med 2016; 11: 217-220.
32. Raiten JM, Neuman MD. “If I had only known”—on choice and uncertainty in the ICU. N Engl J Med 2012; 367: 1779-1781.
33. Than M, Herbert M, Flaws D, et al. What is an acceptable risk of major adverse cardiac event in chest pain patients soon after discharge from the emergency department? A clinical survey. Int J Cardiol 2013; 166: 752-754.
34. Hess EP, Knoedler MA, Shah ND, et al. The chest pain choice decision aid: a randomized trial. Circ Cardiovasc Qual Outcomes 2012; 5: 251-259.
35. Krogsbøll LT, Jørgensen KJ, Grønhøj Larsen C, Gøtzsche PC. General health checks in adults for reducing morbidity and mortality from disease. Cochrane Database Syst Rev 2012; 10: CD009009.
36. Smith SM, Soubhi H, Fortin M, et al. Interventions for improving outcomes in patients with multimorbidity in primary care and community settings. Cochrane Database Syst Rev 2012; 18: CD006560.
37. Melnick ER, Shafer K, Rodulfo N, et al. Understanding overuse of CT for minor head injury in the ED: a triangulated qualitative study. Acad Emerg Med 2015; 22: 1474-1483.
38. Stammen LA, Stalmeijer RE, Paternotte E, et al. Training physicians to provide high-value, cost-conscious care. A systematic review. JAMA 2015; 314: 2384-2400.
39. Korenstein D, Smith CD. Celebrating minimalism in residency training. JAMA Intern Med 2014; 174: 1649-1650.
40. Webster J, Osborne S, Rickard CM, New K. Clinically-indicated replacement versus routine replacement of peripheral venous catheters. Cochrane Database Syst Rev 2015; 8: CD007798.
41. Liao JM, Fleisher LA, Navathe AS. Increasing the value of social comparisons of physician performance using norms. JAMA 2016; 316: 1151-1152.
42. Meeker D, Knight TK, Friedberg MW, et al. Nudging guideline-concordant antibiotic prescribing: a randomized clinical trial. JAMA Intern Med 2014; 174: 425-431.
43. Meeker D, Linder JA, Fox CR, et al. Effect of behavioral interventions on inappropriate antibiotic prescribing among primary care practices: a randomized clinical trial. JAMA 2016; 315: 562-570.
44. Tannenbaum D, Doctor JN, Persell SD, et al. Nudging physician prescription decisions by partitioning the order set: Results of a vignette-based study. J Gen Intern Med 2014; 30: 298-304.
45. Cornia PB, Amory JK, Fraser S, et al. Computer-based order entry decreases duration of indwelling urinary catheterization in hospitalized patients. Am J Med 2003; 114: 404-407.
46. Sirovich BE, Lipner RS, Johnston M, Holmboe ES. The association between residency training and internists’ ability to practice conservatively. JAMA Intern Med 2014; 174: 1640-1648.
47. Schwartz AL, Chernew ME, Landon BE, McWilliams JM. Changes in low-value services in year 1 of the Medicare Pioneer Accountable Care Organization program. JAMA Intern Med 2015; 175: 1815-1825.
48. Warner AS, Shah N, Morse A, et al. Patient and physician attitudes toward low-value diagnostic tests. JAMA Intern Med 2016; 176: 1219-1221.
49. Stacey D, Légaré F, Col NF, et al. Decision aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev 2014; 1: CD001431.
50. Brett AS, McCullough LB. Addressing requests by patients for nonbeneficial interventions. JAMA 2012; 307: 149-150.
51. Grimshaw J, Eccles M, Tetroe J. Implementing clinical guidelines: current evidence and future implications. J Contin Educ Health Prof 2004; 24 Suppl 1: S31-S37.
52. Ament SM, de Groot JJ, Maessen JM, et al. Sustainability of professionals’ adherence to clinical practice guidelines in medical care: a systematic review. BMJ Open 2015; 5: e008073.
53. Davies P, Walker AE, Grimshaw JM. A systematic review of the use of theory in the design of guideline dissemination and implementation strategies and interpretation of the results of rigorous evaluations. Implement Sci 2010; 5: 14-19.
54. Hicks LA, Taylor TH, Hunkler RJ. US outpatient antibiotic prescribing, 2010 [Letter]. N Engl J Med 2013; 368: 1461-1462.
55. Mehrotra A, Linder JA. Tipping the balance toward fewer antibiotics. JAMA Intern Med 2016; 176: 1649-1650.
56. Sears ED, Caverly TJ, Kullgren JT, et al. Clinicians’ perceptions of barriers to avoiding inappropriate imaging for low back pain — knowing is not enough. JAMA Intern Med 2016; 176: 1866-1868.
57. Fenton JJ, Kravitz RL, Jerant A, et al. Promoting patient-centered counseling to reduce use of low-value diagnostic tests: a randomized clinical trial. JAMA Intern Med 2016; 176: 191-197.
58. Lin GA, Dudley RA, Redberg RF. Cardiologists’ use of percutaneous coronary interventions for stable coronary artery disease. Arch Intern Med 2007; 167: 1604-1609.
59. Colla CH, Kinsella KA, Morden NE, et al. Physician perceptions of Choosing Wisely and drivers of overuse. Am J Manag Care 2016; 22: 337-343.

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