Skip to main content
SpringerLink
Log in

Societal Preferences for Interventions with the Same Efficiency: Assessment and Application to Decision Making

  • Original Research Article
  • Published:
Applied Health Economics and Health Policy Aims and scope Submit manuscript

Abstract

Background and Objectives

Although quality-adjusted life-years (QALYs) may not completely reflect the value of a healthcare technology, it remains unclear how to adjust the cost per QALY threshold. First, the present study compares two survey methods of measuring people’s preferences for a specific healthcare technology when each choice has the same efficiency. The second objective was to consider how this information regarding preferences could be used in decision making.

Methods

We conducted single-attribute (budget allocation) and multi-attribute (discrete-choice) experiments to survey public medical care preferences. Approximately 1000 respondents were sampled for each experiment. Six questions were prepared to address the attributes included in the study: (a) age; (b) objective of care; (c) disease severity; (d) prior medical care; (e) cause of disease; and (f) disease frequency. For the discrete-choice experiment (a) age, (b) objective of care, (c) disease severity, and (d) prior medical care were orthogonally combined. All assumed medical care had the same costs and incremental cost-effectiveness ratio (ICER; cost per life-year or QALY). We also calculated the preference-adjusted threshold (PAT) to reflect people’s preferences in a threshold range.

Results

The results of both experiments revealed similar preferences: intervention for younger patients was strongly preferred, followed by interventions for treatment and severe disease states being preferred, despite the same cost per life-year or QALY. The single-attribute experiment revealed that many people prefer an option in which resources are equally allocated between two interventions. Marginal PATs were calculated for age, objective of care, disease severity, and prior medical care.

Conclusion

The single- and multi-attribute experiments revealed similar preferences. PAT can reflect people’s preferences within the decision-maker’s threshold range in a numerical manner.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  1. Weinstein MC. A QALY is a QALY–or is it? J Health Econ. 1988;7(3):289–90.

    Article  CAS  PubMed  Google Scholar 

  2. Rawlins M, Barnett D, Stevens A. Pharmacoeconomics: NICE’s approach to decision-making. Br J Clin Pharmacol. 2010;70(3):346–9. doi:10.1111/j.1365-2125.2009.03589.x.

    Article  PubMed  PubMed Central  Google Scholar 

  3. NICE. What is the role of the Citizens Council? https://www.nice.org.uk/get-involved/citizens-council. Accessed 13 Jan 2016.

  4. Chalkidou K. Evidence and values: paying for end-of-life drugs in the British NHS. Health Econ Policy Law. 2012;7(4):393–409. doi:10.1017/s1744133112000205.

    Article  PubMed  Google Scholar 

  5. Cookson R. Can the NICE “end-of-life premium” be given a coherent ethical justification? J Health Polit Policy Law. 2013;38(6):1129–48. doi:10.1215/03616878-2373166.

    Article  PubMed  Google Scholar 

  6. Hope T. Rationing and life-saving treatments: should identifiable patients have higher priority? J Med Ethics. 2001;27(3):179–85.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. McKie J, Richardson J. The rule of rescue. Soc Sci Med. 2003;56(12):2407–19.

    Article  PubMed  Google Scholar 

  8. Hadorn DC. Setting health care priorities in Oregon. Cost-effectiveness meets the rule of rescue. JAMA. 1991;265(17):2218–25.

    Article  CAS  PubMed  Google Scholar 

  9. de Bekker-Grob EW, Ryan M, Gerard K. Discrete choice experiments in health economics: a review of the literature. Health Econ. 2012;21(2):145–72. doi:10.1002/hec.1697.

    Article  PubMed  Google Scholar 

  10. Lancsar E, Louviere J. Conducting discrete choice experiments to inform healthcare decision making: a user’s guide. Pharmacoeconomics. 2008;26(8):661–77.

    Article  PubMed  Google Scholar 

  11. Schwappach DL. Does it matter who you are or what you gain? An experimental study of preferences for resource allocation. Health Econ. 2003;12(4):255–67. doi:10.1002/hec.713.

    Article  PubMed  Google Scholar 

  12. Green C, Gerard K. Exploring the social value of health-care interventions: a stated preference discrete choice experiment. Health Econ. 2009;18(8):951–76. doi:10.1002/hec.1414.

    Article  PubMed  Google Scholar 

  13. Lancsar E, Wildman J, Donaldson C, Ryan M, Baker R. Deriving distributional weights for QALYs through discrete choice experiments. J Health Econ. 2011;30(2):466–78. doi:10.1016/j.jhealeco.2011.01.003.

    Article  PubMed  Google Scholar 

  14. Lim MK, Bae EY, Choi SE, Lee EK, Lee TJ. Eliciting public preference for health-care resource allocation in South Korea. Value Health. 2012;15(1 Suppl):S91–4. doi:10.1016/j.jval.2011.11.014.

    Article  PubMed  Google Scholar 

  15. Diederich A, Swait J, Wirsik N. Citizen participation in patient prioritization policy decisions: an empirical and experimental study on patients’ characteristics. PLoS One. 2012;7(5):e36824. doi:10.1371/journal.pone.0036824.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Norman R, Hall J, Street D, Viney R. Efficiency and equity: a stated preference approach. Health Econ. 2013;22(5):568–81. doi:10.1002/hec.2827.

    Article  PubMed  Google Scholar 

  17. Schwappach DL, Strasmann TJ. “Quick and dirty numbers”? The reliability of a stated-preference technique for the measurement of preferences for resource allocation. J Health Econ. 2006;25(3):432–48. doi:10.1016/j.jhealeco.2005.08.002.

    Article  PubMed  Google Scholar 

  18. Whitty JA, Lancsar E, Rixon K, Golenko X, Ratcliffe J. A systematic review of stated preference studies reporting public preferences for healthcare priority setting. Patient. 2014;7(4):365–86. doi:10.1007/s40271-014-0063-2.

    Article  PubMed  Google Scholar 

  19. Johri M, Damschroder LJ, Zikmund-Fisher BJ, Ubel PA. The importance of age in allocating health care resources: does intervention-type matter? Health Econ. 2005;14(7):669–78. doi:10.1002/hec.958.

    Article  PubMed  Google Scholar 

  20. Mirelman A, Mentzakis E, Kinter E, Paolucci F, Fordham R, Ozawa S, et al. Decision-making criteria among national policymakers in five countries: a discrete choice experiment eliciting relative preferences for equity and efficiency. Value Health. 2012;15(3):534–9. doi:10.1016/j.jval.2012.04.001.

    Article  PubMed  Google Scholar 

  21. Linley WG, Hughes DA. Societal views on NICE, cancer drugs fund and value-based pricing criteria for prioritising medicines: a cross-sectional survey of 4118 adults in Great Britain. Health Econ. 2013;22(8):948–64. doi:10.1002/hec.2872.

    Article  PubMed  Google Scholar 

  22. Tappenden P, Brazier J, Ratcliffe J, Chilcott J. A stated preference binary choice experiment to explore NICE decision making. Pharmacoeconomics. 2007;25(8):685–93.

    Article  PubMed  Google Scholar 

  23. Whitty JA, Scuffham PA, Rundle-Thiele SR. Public and decision maker stated preferences for pharmaceutical subsidy decisions: a pilot study. Appl Health Econ Health Policy. 2011;9(2):73–9. doi:10.2165/11537150-000000000-00000.

    Article  PubMed  Google Scholar 

  24. Shah K. Severity of illness and priority setting in healthcare: a review of the literature. Health Policy. 2009;93(2–3):77–84. doi:10.1016/j.healthpol.2009.08.005.

    Article  PubMed  Google Scholar 

  25. Dolan P, Tsuchiya A. Health priorities and public preferences: the relative importance of past health experience and future health prospects. J Health Econ. 2005;24(4):703–14. doi:10.1016/j.jhealeco.2004.11.007.

    Article  PubMed  Google Scholar 

  26. Nord E, Richardson J, Street A, Kuhse H, Singer P. Who cares about cost? Does economic analysis impose or reflect social values? Health Policy. 1995;34(2):79–94.

    Article  CAS  PubMed  Google Scholar 

  27. Ubel PA, Baron J, Asch DA. Preference for equity as a framing effect. Med Decis Mak. 2001;21(3):180–9.

    Article  CAS  Google Scholar 

  28. 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(1):55–64.

    PubMed  Google Scholar 

  29. Lloyd AJ. Threats to the estimation of benefit: are preference elicitation methods accurate? Health Econ. 2003;12(5):393–402. doi:10.1002/hec.772.

    Article  PubMed  Google Scholar 

  30. Ryan M, Amaya-Amaya M. ‘Threats’ to and hopes for estimating benefits. Health Econ. 2005;14(6):609–19. doi:10.1002/hec.949.

    Article  PubMed  Google Scholar 

  31. Bryan S, Dolan P. Discrete choice experiments in health economics. For better or for worse? Eur J Health Econ. 2004;5(3):199–202. doi:10.1007/s10198-004-0241-6.

    Article  PubMed  Google Scholar 

  32. Howard K, Salkeld G. Does attribute framing in discrete choice experiments influence willingness to pay? Results from a discrete choice experiment in screening for colorectal cancer. Value Health. 2009;12(2):354–63. doi:10.1111/j.1524-4733.2008.00417.x.

    Article  PubMed  Google Scholar 

  33. National Institute for Health and Care Excellence. Guide to the methods of technology appraisal 2013. London: NICE; 2013. http://publications.nice.org.uk/pmg9. Accessed 22 Feb 2016.

Download references

Author contributions

Conception and planning: Takeru Shiroiwa, Shinya Saito, Kojiro Shimozuma, Satoshi Kodama, Shinichi Noto, and Takashi Fukuda.

Analysis and interpretation: Takeru Shiroiwa, Shinya Saito, Kojiro Shimozuma, and Takashi Fukuda.

Drafting of the manuscript: Takeru Shiroiwa, Shinya Saito, Kojiro Shimozuma, Satoshi Kodama, Shinichi Noto, and Takashi Fukuda.

Approval of the final submitted version of the manuscript: Takeru Shiroiwa, Shinya Saito, Kojiro Shimozuma, Satoshi Kodama, Shinichi Noto, and Takashi Fukuda.

Author information

Authors and Affiliations

  1. Department of Health and Welfare Service, National Institute of Public Health, 2-3-6 Minami, Wako, Saitama, 351-0197, Japan

    Takeru Shiroiwa & Takashi Fukuda

  2. Graduate School of Health Sciences, Okayama University, Okayama, Japan

    Shinya Saito

  3. Department of Biomedical Sciences, College of Life Sciences, Ritsumeikan University, Kusatsu, Japan

    Kojiro Shimozuma

  4. Department of Ethics, Graduate School of Letters, Kyoto University, Kyoto, Japan

    Satoshi Kodama

  5. Department of Health Sciences, Niigata University of Health and Welfare, Niigata, Japan

    Shinichi Noto

Authors
  1. Takeru Shiroiwa
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shinya Saito
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kojiro Shimozuma
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Satoshi Kodama
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Shinichi Noto
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Takashi Fukuda
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Takeru Shiroiwa.

Ethics declarations

Funding

This study was funded by Health and Labour Science Research Grants, Ministry of Health, Labour and Welfare.

Conflict of interest

Takeru Shiroiwa, Shinya Saito, Kojiro Shimozuma, Satoshi Kodama, Shinichi Noto, and Takashi Fukuda have no conflicts of interest to declare.

All participants and panel members agreed with the privacy statements of this survey. This study has not been approved by an ethics committee because it is not required in Japan for this type of population-based study.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shiroiwa, T., Saito, S., Shimozuma, K. et al. Societal Preferences for Interventions with the Same Efficiency: Assessment and Application to Decision Making. Appl Health Econ Health Policy 14, 375–385 (2016). https://doi.org/10.1007/s40258-016-0236-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40258-016-0236-3

Keywords

Search

Navigation