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Measuring Preferences for Cost-Utility Analysis

How Choice of Method May Influence Decision-Making

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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.

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Acknowledgements

This paper was funded by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (P60-AR048094) and the National Institute on Aging (R01-AG12262). The authors have no conflicts of interest that are directly relevant to the content of this article.

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Authors and Affiliations

  1. Dartmouth Medical School, Multidisciplinary Clinical Research Center in Musculoskeletal Diseases and the Center for the Evaluative Clinical Sciences, Lebanon, New Hampshire, USA

    Christine M. McDonough &  Anna N. A. Tosteson

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  1. Christine M. McDonough
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  2. Anna N. A. Tosteson
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Correspondence to Anna N. A. Tosteson.

Appendix

Appendix

1. Literature Search Strategy

The following key words were used in Medline to identify papers addressing the topic of preference measurement method and policy decision-making. In addition, selected authors, references from papers known from previous work and known websites were hand-searched. Searches were limited to English language and carried out between December 2005 and June 2006.

  • Cost-utility analysis

  • Cost-effectiveness analysis

  • Economic evaluation

  • Methods

  • Attitude to health

  • Health status indicators

  • Health status

  • Quality of life

  • Quality-adjusted life years

  • QALYs

  • Time trade off

  • Standard gamble

  • Rating scale

  • Visual analogue scale

  • Utilities

  • Health state values

  • Values

  • Preferences

  • Preferences for health states

  • Preference classification systems

  • Preference-based

  • EQ-5D

  • HUI

  • SF-6D

  • SF

  • Quality of well-being.

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McDonough, C.M., Tosteson, A.N.A. Measuring Preferences for Cost-Utility Analysis. Pharmacoeconomics 25, 93–106 (2007). https://doi.org/10.2165/00019053-200725020-00003

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