Prescriber preferences for behavioural economics interventions to improve treatment of acute respiratory infections: a discrete choice experiment

Cynthia L Gong, Joel W Hay, Daniella Meeker, Jason N Doctor, Cynthia L Gong, Joel W Hay, Daniella Meeker, Jason N Doctor

Abstract

Objective: To elicit prescribers' preferences for behavioural economics interventions designed to reduce inappropriate antibiotic prescribing, and compare these to actual behaviour.

Design: Discrete choice experiment (DCE).

Setting: 47 primary care centres in Boston and Los Angeles.

Participants: 234 primary care providers, with an average 20 years of practice.

Main outcomes and measures: Results of a behavioural economic intervention trial were compared to prescribers' stated preferences for the same interventions relative to monetary and time rewards for improved prescribing outcomes. In the randomised controlled trial (RCT) component, the 3 computerised prescription order entry-triggered interventions studied included: Suggested Alternatives (SA), an alert that populated non-antibiotic treatment options if an inappropriate antibiotic was prescribed; Accountable Justifications (JA), which prompted the prescriber to enter a justification for an inappropriately prescribed antibiotic that would then be documented in the patient's chart; and Peer Comparison (PC), an email periodically sent to each prescriber comparing his/her antibiotic prescribing rate with those who had the lowest rates of inappropriate antibiotic prescribing. A DCE study component was administered to determine whether prescribers felt SA, JA, PC, pay-for-performance or additional clinic time would most effectively reduce their inappropriate antibiotic prescribing. Willingness-to-pay (WTP) was calculated for each intervention.

Results: In the RCT, PC and JA were found to be the most effective interventions to reduce inappropriate antibiotic prescribing, whereas SA was not significantly different from controls. In the DCE however, regardless of treatment intervention received during the RCT, prescribers overwhelmingly preferred SA, followed by PC, then JA. WTP estimates indicated that each intervention would be significantly cheaper to implement than pay-for-performance incentives of $200/month.

Conclusions: Prescribing behaviour and stated preferences are not concordant, suggesting that relying on stated preferences alone to inform intervention design may eliminate effective interventions.

Trial registration number: NCT01454947; Results.

Keywords: antibiotic prescribing; conjoint analysis; discrete choice; revealed preference; stated preference.

Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Figures

Figure 1
Figure 1
DCE treatment scenarios. DCE, discrete choice experiment.

References

    1. Shapiro DJ, Hicks LA, Pavia AT et al. . Antibiotic prescribing for adults in ambulatory care in the USA, 2007–09. J Antimicrob Chemother 2014;69:234–40. 10.1093/jac/dkt301
    1. Steinman M. Changing use of antibiotics in community-based outpatient practice, 1991–1999. Ann Intern Med 2003;138:525–33. 10.7326/0003-4819-138-7-200304010-00008
    1. Grijalva CG, Nuorti JP, Griffin MR. Antibiotic prescription rates for acute respiratory tract infections in US ambulatory settings. JAMA 2009;302:758–66. 10.1001/jama.2009.1163
    1. Ranji SR, Steinman MA, Shojania KG et al. . Antibiotic prescribing behavior Vol. 4: closing the quality gap: a critical analysis of quality improvement strategies. Technical Review 9 (Prepared by Stanford University-UCSF Evidence-based Practice Center under Contract No. 290-02-0017 Rockville: (MD: ): Agency for Healthcare Research and Quality, 2006.
    1. Van Bokhoven MA, Kok G, Van Der Weijden T. Designing a quality improvement intervention: a systematic approach. Qual Saf Health Care 2003;12:215–20. 10.1136/qhc.12.3.215
    1. Demakis J, Mcqueen L, Kizer KW et al. . Quality Enhancement Research Initiative (QUERI): a collaboration between research and clinical practice. Med Care 2000;38(Suppl 1):I17 10.1097/00005650-200006001-00003
    1. Rubenstein LV, Mittman BS, Yano EM et al. . From understanding health care provider behavior to improving health care: the QUERI framework for quality improvement. Quality Enhancement Research Initiative. Med Care 2000;38(Suppl 1):I129–41. 10.1097/00005650-200006001-00013
    1. Robinson JC. Theory and practice in the design of physician payment incentives. Milbank Q 2001;79:149–77, III 10.1111/1468-0009.00202
    1. Scott A. Eliciting GPs’ preferences for pecuniary and non-pecuniary job characteristics. J Health Econ 2001;20:329–47. 10.1016/S0167-6296(00)00083-7
    1. Armour BS, Pitts MM, Maclean R et al. . The effect of explicit financial incentives on physician behavior. Arch Intern Med 2001;161:1261–6. 10.1001/archinte.161.10.1261
    1. Town R, Kane R, Johnson P et al. . Economic incentives and physicians’ delivery of preventive care: a systematic review. Am J Prev Med 2005;28:234–40. 10.1016/j.amepre.2004.10.013
    1. Loewenstein G, Brennan T, Volpp K. Asymmetric paternalism to improve health behaviors. JAMA 2007;298:2415–17. 10.1001/jama.298.20.2415
    1. Frolich A, Talavera JA, Broadhead P et al. . A behavioral model of clinician responses to incentives to improve quality. Health Policy 2007;80:179–93. 10.1016/j.healthpol.2006.03.001
    1. Thaler RH, Sunstein CR. Nudge: improving decisions about health, wealth, and happiness. New York: Penguin Books, 2009.
    1. Who We Are (cited 19 May 2016).
    1. Hallsworth M, Chadborn T, Sallis A et al. . Provision of social norm feedback to high prescribers of antibiotics in general practice: a pragmatic national randomised controlled trial. Lancet 2016;387:1743–52. 10.1016/S0140-6736(16)00215-4
    1. Persell S, Friedberg M, Meeker D et al. . Use of behavioral economics and social psychology to improve treatment of acute respiratory infections (BEARI): rationale and design of a cluster randomized controlled trial—study protocol and baseline practice and provider characteristics. BMC Infect Dis 2013;13:290–300. 10.1186/1471-2334-13-290
    1. Meeker D, Linder JA, Fox CR et al. . Effect of behavioral interventions on inappropriate antibiotic prescribing among primary care practices. JAMA 2016;315:562–70. 10.1001/jama.2016.0275
    1. Ryan M, Gerard K. Using discrete choice experiments to value health care programmes: current practice and future research reflections. Appl Health Econ Health Policy 2003;2:55–64.
    1. Whitty JA, Lancsar E, Rixon K et al. . A systematic review of stated preference studies reporting public preferences for healthcare priority setting. Patient 2014;7:365–86. 10.1007/s40271-014-0063-2
    1. De Bekker-Grob E, Ryan M, Gerard K. Discrete choice experiments in health economics: a review of the literature. Health Econ 2012;21:145–72. 10.1002/hec.1697
    1. Clark MD, Determann D, Petrou S et al. . Discrete choice experiments in health economics: a review of the literature. Pharmacoeconomics 2014;32:883–902. 10.1007/s40273-014-0170-x
    1. Krucien N, Gafni A, Pelletier-Fleury N. Empirical testing of the external validity of a discrete choice experiment to determine preferred treatment option: the case of sleep apnea. Health Econ 2015;24:951–65. 10.1002/hec.3076
    1. Linley W, Hughes D. Decision-makers’ preferences for approving new medicines in wales: a discrete-choice experiment with assessment of external validity. Pharmacoeconomics 2013;31:345–55. 10.1007/s40273-013-0030-0
    1. Ryan M, Watson V. Comparing welfare estimates from payment card contingent valuation and discrete choice experiments. Health Econ 2009;18:389–401. 10.1002/hec.1364
    1. Lambooij MH, Irene A, Veldwijk J et al. . Consistency between stated and revealed preferences: a discrete choice experiment and a behavioural experiment on vaccination behaviour compared. BMC Med Res Methodol 2015;15:19 10.1186/s12874-015-0010-5
    1. Mark TL, Swait J. Using stated preference modeling to forecast the effect of medication attributes on prescriptions of alcoholism medications. Value Health 2003;6:474–82. 10.1046/j.1524-4733.2003.64247.x
    1. Arrow K, Solow R, Portney PR et al. . Report of the NOAA Panel on Contingent Valuation, US National Oceanic and Atmospheric Administration (NOAA), 1993.
    1. Louviere J, Flynn T, Carson R. Discrete choice experiments are not conjoint analysis. J Choice Model 2010;3:57–72. 10.1016/S1755-5345(13)70014-9
    1. Louviere J, Hensher D, Swait J. Stated choice methods analysis and applications. Cambridge: (UK: ): Cambridge University Press, 2000.
    1. Lancaster KJ. A new approach to demand theory. J Polit Econ 1966;74:132–57. 10.1086/259131
    1. Maviglia SM, Zielstorff RD, Paterno M et al. . Automating complex guidelines for chronic disease: lessons learned. J Am Med Inform Assoc 2003;10:154–65. 10.1197/jamia.M1181
    1. Kawamoto K, Houlihan CA, Balas EA et al. . Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. BMJ 2005;330:765 10.1136/bmj.38398.500764.8F
    1. Kerr N. Anonymity and social control in social dilemmas. In: Foddy M, Smithson M, Schneider S et al.. eds Resolving social dilemmas: dynamics, structural, and intergroup aspects. Philadelphia: (PA: ): Psychology Press, 1999:103–9.
    1. Kesselheim AS, Cresswell K, Phansalkar S et al. . Clinical decision support systems could be modified to reduce ‘alert fatigue’ while still minimizing the risk of litigation. Health Aff (Millwood) 2011;30:2310–7. 10.1377/hlthaff.2010.1111
    1. Veldwijk J, Lambooij MS, De Bekker-Grob EW et al. . The effect of including an opt-out option in discrete choice experiments. PLoS ONE 2014;9:e111805 10.1371/journal.pone.0111805
    1. Lancsar E, Louviere J. Conducting discrete choice experiments to inform healthcare decision making: a user's guide. Pharmacoeconomics 2008;26:661–77. 10.2165/00019053-200826080-00004
    1. Parker LE, Ritchie MJ, Kirchner JAE et al. . Balancing health care evidence and art to meet clinical needs: policymakers’ perspectives. J Eval Clin Pract 2009;15:970–5. 10.1111/j.1365-2753.2009.01209.x

Source: PubMed

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