Advertisement

Measuring QALYs for HTA and Health Policy Decision Making: Bridging the Gap Between Power and Act

  • José-María Abellán-Perpiñán
Chapter
  • 949 Downloads

Abstract

‘Dynamic’ and ‘energy’ are two modern words coming from the Ancient Greek words ‘dunamis’ and ‘energeia’, respectively. In times of Aristotle these terms described the tension between potency and actuality. Something can exist potentially in the sense that there is the capability that allows it to become real. In contrast, actuality denotes the fulfilment of that potentiality. Therefore, the dichotomy power-act finishes when, thanks to an activity, something merely possible becomes fully actual.

Keywords

Expect Utility Health Technology Assessment Prospect Theory Loss Aversion Standard Gamble 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bleichrodt H, Johannesson M. An experimental test of a theoretical foundation for rating-scale valuations. Med Decis Making. 1997;17(2):208-16.Google Scholar
  2. 2.
    Bleichrodt H, Pinto JL, Abellán-Perpiñán JM. A consistency test of the time trade-off. J Health Econ. 2003;22:1037-52.Google Scholar
  3. 3.
    Bleichrodt H, Pinto JL, Wakker PP. Using descriptive findings of prospect theory to improve the prescriptive use of expected utility. Management Science. 2001;47:1498-514.Google Scholar
  4. 4.
    Pinto JL, Abellán-Perpiñán JM. When normative and descriptive diverge: how to bridge the difference. Soc Choice Welfare. 2012;38(4):569-84.Google Scholar
  5. 5.
    Garratt AM, Schmidt L, MacKintosh A, Fitzpatrick R. Quality of life measurement: Bibliographic study of patient assessed health outcome measures. British Medical Journal. 2002;324:1417-21.Google Scholar
  6. 6.
    Robinson A, Loomes G, Jones-Lee M. Visual analog scales standard gambles and relative risk aversion. Med Decis Making. 2001;21(1):17-27.Google Scholar
  7. 7.
    Abellán-Perpiñán JM, Pinto JL, Méndez I, Badía X. Towards a better QALY model. Health Economics. 2006;15:665-76.Google Scholar
  8. 8.
    Abellán-Perpiñán JM, Bleichrodt H, Pinto JL. The predictive validity of prospect theory versus expected utility in health utility measurement. J Health Econ. 2009;28:1039-47.Google Scholar
  9. 9.
    Abellán-Perpiñán JM, Sánchez FI, Martínez JE, Méndez I. Lowering the floor of the SF-6D algorithm using a lottery equivalent method. Health Economics. 2012;21:1271-85.Google Scholar
  10. 10.
    Starmer C. Developments in non-expected utility theory: the hunt for a descriptive theory of choice under risk. J Econ Literature. 2000;38:332-82.Google Scholar
  11. 11.
    Bleichrodt H, Abellan-Perpiñán JM, Pinto-Prades JL, Mendez-Martinez I. Resolving inconsistencies in utility measurement under risk: tests of generalizations of expected utility. Management Science. 2007;53(3):469.Google Scholar
  12. 12.
    Pinto JL, Herrero C, Abellán-Perpiñán J. QALY-based cost-effcetiveness analysis. Adler MD, Fleurbaey M, (eds). Handbook of well-being and public policy. Oxford University Press, In press.Google Scholar
  13. 13.
    Plott CP. Rational individual behavior in markets and social choice processes. Arrow KJ, Colombatto E, Perlman M, Schmidt C, (eds). The Rational Foundations of Economic Behavior: Proceedings of the IEA Conference Held in Turin Italy. St Martin’s Press New York, 1996:225-50.Google Scholar
  14. 14.
    Torrance GW. Measurement of health state utilities for economic appraisal. J Health Econ. 1986;12:39-53.Google Scholar
  15. 15.
    Bleichrodt H, Quiggin J. Characterizing QALYs under a general rank-dependent utility model. J Risk Uncertainty. 1997;15:151-65.Google Scholar
  16. 16.
    Abellán-Perpiñán JM, Pinto JL. Quality adjusted life years as expected utilities. Spanish Economic Review. 2000;2(1):49-63.Google Scholar
  17. 17.
    Pliskin JS, Shepard DS, Weinstein MC. Utility functions for life years and health status. Operations Research. 1980;28(1):206-54.Google Scholar
  18. 18.
    Miyamoto JM. Quality-adjusted life years (QALY) utility models under expected utility and rank dependent utility assumptions. J Mathematical Psychol. 1999; 43:201-37.Google Scholar
  19. 19.
    Bleichrodt H, Filko M. New tests of QALYs when health varies over time. J Health Econ. 2008;27:1237-49.Google Scholar
  20. 20.
    Feeny D, Furlong W, Torrance GW, Goldsmith C, Zenglong Z, Depauw S, Denton M, Boyle M. Multi-attribute and single-attribute utility functions for the Health Utilities Index Mark 3 System. Medical Care. 2002;40(2):113-28.Google Scholar
  21. 21.
    Brazier J, Roberts J, Deverill M. The estimation of a preference-based measure of health from the SF-36. J Health Econ. 2002;21:271-92.Google Scholar
  22. 22.
    Wakker P, Deneffe D. Eliciting von Newman-Morgenstern utilities when probabilities are distorted or unknown. Management Science. 1996;42(8):1131-50.Google Scholar
  23. 23.
    Pinto JL, Abellán-Perpiñán JM. Measuring the health of populations: the veil of ignorance approach. Health Economics. 2005;14(1):69-82.Google Scholar
  24. 24.
    Bleichrodt H. A new explanation for the difference between time trade-off utilities and standard gamble utilities. Health Economics. 2002;11(5):447-56.Google Scholar
  25. 25.
    Kahneman D, Tversky A. Prospect theory: an analysis of decision under risk. Econometrica. 1979;47:263-91.Google Scholar
  26. 26.
    Tversky A, Kahneman D. Advances in prospect theory: cumulative representation of uncertainty. Journal of Risk and Uncertainty. 1992;5:297-323.Google Scholar
  27. 27.
    Parducci A. Category judgment: a range-frequency model. Psychological Review. 1965;72(6):407-18.Google Scholar
  28. 28.
    Schwartz A. Rating scales in context. Med Decis Making. 1998;18:236.Google Scholar
  29. 29.
    McCord M, de Neufville R. Lottery equivalents: reduction of the certainty effect problem in utility assessment. Management Science. 1986;32:56-60.Google Scholar
  30. 30.
    Camerer C. Recent tests of generalizations of expected utility theory. In utility: theories measurement and applications. Edwards W (ed). Kluwer Academic Publishers: Boston MA; 1992;207-51.Google Scholar
  31. 31.
    Brazier J, Roberts J. The estimation of a preference-based measure of health from the SF-12. Medical Care. 2004;42:851-9.Google Scholar
  32. 32.
    Dolan P. Modeling valuations for EuroQol health states. Medical Care. 1997;35:1095-108.Google Scholar
  33. 33.
    Badia X, Roset M, Herdman M, Kind P. A comparison of United Kingdom and Spanish general population time trade-off values for EQ-5D health states. Med Decis Making. 2001;21:7-16.Google Scholar
  34. 34.
    Patrick DK, Starks HE, Cain KC, Uhlmann RF, Pearlman RA. Measuring preferences for health states worse than death. Med Decis Making. 1994;14:9-18.Google Scholar
  35. 35.
    Devlin NJ, Tsuchiya A, Buckingham K, Tilling C. A uniform time trade off method for states better and worse than dead: feasibility study of the ‘lead time’ approach. Health Econ. 2011;20(3):348-61.Google Scholar
  36. 36.
    Wakker P. Lessons learned by (from?). An economist working in medical decision making. Med Decis Making. 2008;28(5):690-8.Google Scholar
  37. 37.
    Van Osch SM, Wakker PP, van den Hout WB, Stiggelbout AM. Correcting biases in standard gamble and time tradeoff utilities. Med Decis Making. 2004;24(5):11-7.Google Scholar
  38. 38.
    Doctor JN, Bleichrodt HJ, Lin H. Health utility bias: a systematic review and meta-analytic evaluation. Med Decis Making. 2010;30:58-67.Google Scholar
  39. 39.
    Robinson A, Spencer A. Exploring challenges to TTO utilities: valuing states worse than dead. Health Econ. 2006;15(4):393-402.Google Scholar
  40. 40.
    Pinto JL, Rodríguez E. The lead time trade-off: the case of health states better than death. WP ECON 1110 Universidad Pablo de Olavide, 2011.Google Scholar
  41. 41.
    Parkin D, Devlin N. Is there a case for using visual analogue scale valuations in cost-utility analysis? Health Economics. 2006;15(7):653-64.Google Scholar
  42. 42.
    Abellán-Perpiñán JM, Sánchez FI, Martínez JE, Méndez I. Debiasing Eq-5D tariffs. New estimations of the Spanish Eq-5D value set under nonexpected utility. 2009; CENTRA Documento de Trabajo E2009/06.Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • José-María Abellán-Perpiñán
    • 1
  1. 1.University of MurciaMurciaSpain

Personalised recommendations