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Are subjective well-being measures any better than decision utility measures?

Published online by Cambridge University Press:  01 January 2008

DYLAN M. SMITH ,
STEPHANIE L. BROWN  and
PETER A. UBEL
DYLAN M. SMITH*
Affiliation:
VA Center for Practice Management and Outcomes Research, VA Ann Arbor Healthcare System, Ann Arbor, Center for Behavioral and Decision Sciences in Medicine, University of Michigan School of Medicine and Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, USA
STEPHANIE L. BROWN
Affiliation:
VA Center for Practice Management and Outcomes Research, VA Ann Arbor Healthcare System, Ann Arbor, Center for Behavioral and Decision Sciences in Medicine, University of Michigan School of Medicine and Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, USA
PETER A. UBEL
Affiliation:
VA Center for Practice Management and Outcomes Research, VA Ann Arbor Healthcare System, Ann Arbor, Center for Behavioral and Decision Sciences in Medicine, University of Michigan School of Medicine and Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, USA
*
*Corresponding author: Dylan M. Smith, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI 48109, USA. Email: dylsmith@umich.edu
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Abstract

There are a number of substantial problems with using decision-based utility measures such as the time trade off and standard gamble to value improvements in health. Dolan (this issue) argues that because of these problems, it would be better to use measures of real experiences (subjective well being). We review evidence that supports criticisms of decision-based utility measures, whether provided by patients or non-patients. But we also review a number of substantial problems with currently used measures of subjective well-being, and point out that there is no definitive evidence that they represent any improvement over decision utility measures. We conclude with a call for expanded research into developing new tools for quantifying health-related quality of life that are more valid, more sensitive to changes in health status, and less biased.

Type
Response
Information
Health Economics, Policy and Law , Volume 3 , Issue 1 , January 2008 , pp. 85 - 91
Copyright
Copyright © Cambridge University Press 2008

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