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Measuring Preferences for Cost-Utility Analysis

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  • Christine McDonough
  • Anna Tosteson

Abstract

Preferences for health are required when the economic value of healthcare interventions are assessed within the framework of cost-utility analysis. The objective of this paper was to review alternative methods for preference measurement and to evaluate the extent to which the method may affect healthcare decision-making. Two broad approaches to preference measurement that provide societal health state values were considered: (i) direct measurement; and (ii) preference-based health state classification systems. Among studies that compared alternative preference-based systems, the EQ-5D tended to provide larger change scores and more favourable cost-effectiveness ratios than the Health Utilities Index (HUI)-2 and -3, while the SF-6D provided smaller change scores and less favourable ratios than the other systems. However, these patterns may not hold for all applications. Empirical evidence comparing systems and decision-making impact suggests that preferences will have the greatest impact on economic analyses when chronic conditions or long-term sequelae are involved. At present, there is no clearly superior method, and further study of cost-effectiveness ratios from alternative systems is needed to evaluate system performance. Although there is some evidence that incremental cost-effectiveness ratio (ICER) thresholds (e.g. $US50 000 per QALY gained) are used in decision-making, they are not strictly applied. Nonetheless, as ICERs rise, the probability of acceptance of a new therapy is likely to decrease, making the differences in QALYs obtained using alternative methods potentially meaningful. It is imperative that those conducting cost-utility analyses characterise the impact that uncertainty in health state values has on the economic value of the interventions studied. Consistent reporting of such analyses would provide further insight into the policy implications of preference measurement. Copyright Adis Data Information BV 2007

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  • Christine McDonough & Anna Tosteson, 2007. "Measuring Preferences for Cost-Utility Analysis," PharmacoEconomics, Springer, vol. 25(2), pages 93-106, February.
  • Handle: RePEc:spr:pharme:v:25:y:2007:i:2:p:93-106
    DOI: 10.2165/00019053-200725020-00003
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    1. Erik Nord & Jose Luis Pinto & Jeff Richardson & Paul Menzel & Peter Ubel, 1999. "Incorporating societal concerns for fairness in numerical valuations of health programmes," Health Economics, John Wiley & Sons, Ltd., vol. 8(1), pages 25-39, February.
    2. Carmen Selva-Sevilla & Paula Ferrara & Manuel Gerónimo-Pardo, 2020. "Interchangeability of the EQ-5D and the SF-6D, and comparison of their psychometric properties in a spinal postoperative Spanish population," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 21(4), pages 649-662, June.
    3. Jeffrey Hoch & Carolyn Dewa, 2007. "Lessons from Trial-Based Cost-Effectiveness Analyses of Mental Health Interventions," PharmacoEconomics, Springer, vol. 25(10), pages 807-816, October.
    4. Hans-Helmut König & Oliver Günther & Matthias Angermeyer & Christiane Roick, 2009. "Utility Assessment in Patients with Mental Disorders," PharmacoEconomics, Springer, vol. 27(5), pages 405-419, May.
    5. J. Tilford & Nalin Payakachat & Erica Kovacs & Jeffrey Pyne & Werner Brouwer & Todd Nick & Jayne Bellando & Karen Kuhlthau, 2012. "Preference-Based Health-Related Quality-of-Life Outcomes in Children with Autism Spectrum Disorders," PharmacoEconomics, Springer, vol. 30(8), pages 661-679, August.

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