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Commentary. In Praise of Studies That Use More Than One Generic Preference-Based Measure

Published online by Cambridge University Press:  12 July 2019

David Feeny ,
William Furlong  and
George W. Torrance
David Feeny*
Affiliation:
Department of Economics and Centre for Health Economics and Policy Analysis, McMaster University, Hamilton, ONCanada; Health Utilities Incorporated, Dundas ONCanada
William Furlong
Affiliation:
Centre for Health Economics and Policy Analysis, McMaster University, Hamilton, ONCanada; Health Utilities Incorporated, Dundas ONCanada
George W. Torrance
Affiliation:
Centre for Health Economics and Policy Analysis, McMaster University, Hamilton, ONCanada; Health Utilities Incorporated, Dundas ONCanada
*
Author for correspondence: David Feeny, E-mail: [email protected]
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Abstract

Objectives and Background

Generic preference-based (GPB) measures of health-related quality of life (HRQL) are widely used as outcome measures in cost-effectiveness and cost-utility analyses (CEA, CUA). Health technology assessment agencies favor GPB measures because they facilitate comparisons among conditions and because the scoring functions for these measures are based on community preferences. However, there is no gold standard HRQL measure, scores generated by GPB measures may differ importantly, and changes in scores may fail to detect important changes in HRQL. Therefore, to enhance the accumulation of empirical evidence on how well GPB measures perform, we advocate that investigators routinely use two (or more) GPB measures in each study.

Methods

We discuss key measurement properties and present examples to illustrate differences in responsiveness for several major GPB measures across a wide variety of health contexts. We highlight the contributions of longitudinal head-to-head studies.

Results

There is substantial evidence that the performance of GPB measures varies importantly among diseases and health conditions. Scores are often not interchangeable. There are numerous examples of studies in which one GPB measure was responsive while another was not.

Conclusions

Investigators should use two (or more) GPB measures. Study protocols should designate one measure as the primary outcome measure; the other measure(s) would be used in secondary analyses. As evidence accumulates it will better inform the relative strengths and weaknesses of alternative GPB measures in various clinical conditions. This will facilitate the selection and interpretation of GPB measures in future studies.

Keywords

Comparative effectiveness researchCost-effectiveness analysisCost-utility analysisEuroQol EQ-5DGeneric preference-based measuresHealth-related quality of lifeHealth technology assessmentHealth Utilities IndexMulti-attribute utility measuresOutcome measuresQuality-adjusted life-yearsQuality of Well Being ScaleShort-Form 6D
Type
Article Commentary
Information
International Journal of Technology Assessment in Health Care , Volume 35 , Issue 4 , 2019 , pp. 257 - 262
Copyright
Copyright © Cambridge University Press 2019 

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Footnotes

Ethics approval and consent to participate: Not applicable. Availability of data and materials: Not applicable. Competing interests: It should be noted that all three authors have a proprietary interest in Health Utilities Incorporated, Dundas, Ontario, Canada. HUInc. distributes copyrighted Health Utilities Index (HUI) materials and provides methodological advice on the use of the HUI. Funding: There was no funding source for this study. Authors’ contributions: All three authors contributed to the conceptualization and writing of the study and have approved the final version of the manuscript. The authors acknowledge the constructive comments by the Editor, Deputy Editor, Associate Editor, and two reviewers, which have improved the study.

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