, Volume 23, Issue 12, pp 1207–1214 | Cite as

Cost-effectiveness acceptability curves and a reluctance to lose

  • Johan L. Severens
  • Daniëlle E. M. Brunenberg
  • Elisabeth A. L. Fenwick
  • Bernie O’Brien
  • Manuela A. Joore
Leading Article


Cost-effectiveness acceptability curves (CEACs) are a method used to present uncertainty surrounding incremental cost-effectiveness ratios (ICERs). Construction of the curves relies on the assumption that the willingness to pay (WTP) for health gain is identical to the willingness to accept (WTA) health loss. The objective of this paper is to explore the impact that differences between WTP and WTA health changes have on CEACs.

Previous empirical evidence has shown that the relationship between WTP and WTA is not 1: 1. The discrepancy between WTP and WTA for health changes can be expressed as a ratio: the accept/reject ratio (which can vary between 1 and infinity). Depending on this ratio, the area within the southwest quadrant of the cost-effectiveness plane in which any bootstrap cost-effect pairs will be considered to be cost effective will be smaller, resulting in a lower CEAC. We used data from two clinical trials to illustrate that relaxing the 1: 1 WTP/WTA assumption has an impact on the CEACs. Given the difficulty in assessing the accept/reject ratio for every evaluation, we suggest presenting a series of CEACs for a range of values for the accept/reject ratio, including 1 and infinite.

Although it is not possible to explain this phenomenon within the extra-welfarist framework, it has been shown empirically that individuals give a higher valuation to the removal of effective therapies than to the introduction of new therapies that are more costly and effective. In cost-effectiveness analyses where uncertainty of the ICER covers the southwest quadrant of the cost-effectiveness plane, the discrepancy between societies’ WTP and WTA should be indicated by drawing multiple CEACs.



This work was performed within the authors’ institutes without additional, external funding. We acknowledge Dr J. Prins and Dr G. Bleijenberg (Radboud University Nijmegen, The Netherlands) and Dr M. van M. Steijn, J. Sluimer, L. Bekebrede and S. Bulstra (University Hospital Maastricht) for making their trial data available.

The authors take full responsibility for any remaining inaccuracies and the viewpoints expressed. The authors have no conflicts of interest to declare.


  1. 1.
    Van-Hout BA, Al MJ, Gordon GS, et al. Costs, effects and C/E-ratios alongside a clinical trial. Health Econ 1994; 3 (5): 309–19PubMedCrossRefGoogle Scholar
  2. 2.
    Gray A, Raikou M, McGuire A, et al. Cost-effectiveness of an intensive blood glucose control policy in patients with type 2 diabetes: economic analysis alongside randomised controlled trial (UKPDS 41). United Kingdom Prospective Diabetes Study Group. BMJ 2000; 320 (7246): 1373–8PubMedCrossRefGoogle Scholar
  3. 3.
    Briggs AH, Gray AM. Handling uncertainty when performing economic evaluation of health care interventions. Health Technol Assess 1999; 3 (2): 1–134PubMedGoogle Scholar
  4. 4.
    Fenwick E, Claxton K, Sculpher M. Representing uncertainty: the role of cost-effectiveness acceptability curves. Health Econ 2001; 10: 779–87PubMedCrossRefGoogle Scholar
  5. 5.
    Eichler HG, Kong SX, Gerth WC, et al. Use of cost-effectiveness analysis in health-care resource allocation decision making: how are cost-effectiveness thresholds expected to emerge? Value Health 2004; 7 (5): 518–28PubMedCrossRefGoogle Scholar
  6. 6.
    O’Brien BJ, Gertsen K, Willan AR, et al. Is there a kink in consumers’ threshold value for cost-effectiveness in health care? Health Econ 2002; 11: 175–80PubMedCrossRefGoogle Scholar
  7. 7.
    Briggs AH, Fenn P. Confidence intervals or surfaces? Uncertainty on the cost-effectiveness plane. Health Econ 1998; 7: 723–40PubMedCrossRefGoogle Scholar
  8. 8.
    Briggs AH. A Bayesian approach to stochastic cost-effectiveness analysis. Health Econ 1999; 8: 257–61PubMedCrossRefGoogle Scholar
  9. 9.
    Briggs AH. Handling uncertainty in cost-effectiveness models. Pharmacoeconomics 2000; 17 (5): 479–500PubMedCrossRefGoogle Scholar
  10. 10.
    Severens JL, Prins JB, van der Wilt GJ, et al. Cost-effectiveness of cognitive behaviour therapy for patients with chronic fatigue syndrome. QJM 2004; 97: 153–61PubMedCrossRefGoogle Scholar
  11. 11.
    Shogren JF, Shin SY, Hayes DJ, et al. Resolving differences in willingness to pay and willingness to accept. Am Econ Rev 1994; 84 (1): 225–70Google Scholar
  12. 12.
    Gyrd-Hansen D. Willingness to pay for a QALY. Health Econ 2003; 12: 1049–60PubMedCrossRefGoogle Scholar
  13. 13.
    Willan AR, O’Brien BJ, Leyva RA. Cost-effectiveness analysis when the WTA is greater than the WTP. Stat Med 2001; 20: 3251–9PubMedCrossRefGoogle Scholar
  14. 14.
    Prins JB, Bleijenberg G, Bazelmans E, et al. Cognitive behaviour therapy for chronic fatigue syndrome: a multicentre randomised controlled trial. Lancet 2001; 357: 841–7PubMedCrossRefGoogle Scholar
  15. 15.
    Reid S, Chalder T, Cleare A, et al. Chronic fatigue syndrome. BMJ 2000; 320: 292–6PubMedCrossRefGoogle Scholar
  16. 16.
    Fukuda K, Straus SE, Hickie I, et al. The chronic fatigue syndrome: a comprehensive approach to its definition and study. Ann Intern Med 1994; 121: 953–9PubMedGoogle Scholar
  17. 17.
    Bombardier CH, Buchwald D. Chronic fatigue, chronic fatigue syndrome and fibromyalgia: disability and health care use. Med Care 1996; 34 (9): 924–30PubMedCrossRefGoogle Scholar
  18. 18.
    Whiting P, Bagnall A, Sowden AJ, et al. Interventions for the treatment and management of chronic fatigue syndrome: a systematic review. JAMA 2001; 286: 1360–8PubMedCrossRefGoogle Scholar
  19. 19.
    Dolan P. Modeling valuations for EuroQol health states. Med Care 1997; 35: 1095–108PubMedCrossRefGoogle Scholar
  20. 20.
    Severens JL, De Boo TM, Konst EM. Uncertainty of incremental cost-effectiveness ratios: a comparison of Fieller and bootstrap confidence intervals. Int J Technol Assess Health Care 1999; 15: 608–14PubMedCrossRefGoogle Scholar
  21. 21.
    Brunenberg D, Van-Steijn M, Sluimer J, et al. Joint recovery programme versus usual care programme: an economic evaluation of a new care protocol for joint replacement surgery. Med Care 2005; 43 (10): 1018–26PubMedCrossRefGoogle Scholar
  22. 22.
    Hawker GA, Wright JG, Coyle PC. Health related quality of life after knee replacement. J Bone Joint Surg Am 1998; 80: 163–73PubMedGoogle Scholar
  23. 23.
    Hitch HS. Total joint replacement: a cost-effective procedure for the 1990s. Med Health R I 1998; 81: 162–4Google Scholar
  24. 24.
    Birell F, Johnell O, Sillman A. Projecting the need for hip replacement over the next three decades: influence of changing demography and threshold for surgery. Ann Rheum Dis 1999; 58: 569–72CrossRefGoogle Scholar
  25. 25.
    Ryan P. The benefits of a nurse-led preoperative assessment clinic. Nurs Times 2000; 96: 42–3PubMedGoogle Scholar
  26. 26.
    Gammon J, Mulholland CW. Effect of preparatory information prior to elective total hip replacement on post-operative physical coping outcomes. Int J Nurs Stud 1966; 33: 589–604CrossRefGoogle Scholar
  27. 27.
    Lin YK, Lin GT, Tien YC, et al. Impact of a clinical pathway for total knee arthroplasty. Kaohsiung J Med Sci 2002; 28: 134–40Google Scholar
  28. 28.
    Pearson SD, Kleefield SF, Soukop JR, et al. Critical pathways intervention to reduce length of hospital stay. Am J Med 2001; 110: 175–80PubMedCrossRefGoogle Scholar
  29. 29.
    Weingarten S, Riedinger MS, Sandhu M, et al. Can practice guidelines safely reduce hospital length of stay? Results from a multicentre interventional study. Am J Med 1998; 105: 33–40PubMedCrossRefGoogle Scholar
  30. 30.
    Dowie J. Why cost-effectiveness should trump (clinical) effectiveness: the ethical economics of the South West quadrant. Health Econ 2004; 13: 453–9PubMedCrossRefGoogle Scholar

Copyright information

© Adis Data Information BV 2005

Authors and Affiliations

  • Johan L. Severens
    • 1
    • 2
  • Daniëlle E. M. Brunenberg
    • 2
  • Elisabeth A. L. Fenwick
    • 3
  • Bernie O’Brien
    • 4
  • Manuela A. Joore
    • 2
  1. 1.The Department of Health Organisation, Policy and EconomicsUniversity MaastrichtMaastrichtThe Netherlands
  2. 2.The Department of Clinical Epidemiology and Medical Technology AssessmentUniversity Hospital MaastrichtMaastrichtThe Netherlands
  3. 3.The Centre for Health EconomicsUniversity of YorkYorkUK
  4. 4.The Centre for the Evaluation of MedicineMcMaster UniversityHamiltonCanada

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