Current state of the art in preference-based measures of health and avenues for further research
AbstractPreference-based measures of health (PBMH) have been developed primarily for use in economic evaluation. They have two components, a standardized, multidimensional system for classifying health states and a set of preference weights or scores that generate a single index score for each health state defined by the classification, where full health is one and zero is equivalent to death. A health state can have a score of less than zero if regarded as worse than being dead. These PMBH can be distinguished from non-preference-based measures by the way the scoring algorithms have been developed, in that they are estimated from the values people place on different aspects of health rather than a simple summative scoring procedure or weights obtained from techniques based on item response patterns (e.g., factor analysis or Rasch analysis). The use of PBMH has grown considerably over the last decade with the increasing use of economic evaluation to inform health policy. Preference-based measures have become a common means of generating health state values for calculating quality-adjusted life years (QALY). The status of PBMH was considerably enhanced by the recommendations of the U.S. Public Health Service Panel on Cost-Effectiveness in Health and Medicine to use them in economic evaluation. A key requirement for PBHM in economic evaluation is that they allow comparison across programmes. While PBMH have been developed primarily for use in economic evaluation, they have also been used to measure health in populations. PBHM provide a better means than a profile measure of determining whether there has been an overall improvement in self-perceived health. The preference-based nature of their scoring algorithms also offers an advantage over non-preference-based measures since the overall summary score reflects what is important to the general population. A non-preference-based measure does not provide an indication to policy makers of the overall importance of health differences between groups or of changes over time. The purpose of this paper is to critically review methods of designing preference based measures. The paper begins by reviewing approaches to deriving preference weights for PBMH, and this is followed by a brief description and comparison of five common PBMH. The main part of the paper then critically reviews the core components of these measures, namely the classifications for describing health states, the source of their values, and the methods for estimating the scoring algorithm. The final section proposes future research priorities for this field.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 29762.
Date of creation: Dec 2005
Date of revision:
preference-based health measures;
Find related papers by JEL classification:
- I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being
- I19 - Health, Education, and Welfare - - Health - - - Other
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Alan Shiell & Janelle Seymour & Penelope Hawe & Sue Cameron, 2000. "Are preferences over health states complete?," Health Economics, John Wiley & Sons, Ltd., vol. 9(1), pages 47-55.
- Brazier, John & Roberts, Jennifer & Deverill, Mark, 2002. "The estimation of a preference-based measure of health from the SF-36," Journal of Health Economics, Elsevier, vol. 21(2), pages 271-292, March.
- Oliver, Adam, 2003. "The internal consistency of the standard gamble: tests after adjusting for prospect theory," Journal of Health Economics, Elsevier, vol. 22(4), pages 659-674, July.
- Han Bleichrodt, 2002. "A new explanation for the difference between time trade-off utilities and standard gamble utilities," Health Economics, John Wiley & Sons, Ltd., vol. 11(5), pages 447-456.
- Dolan, P. & Gudex, C. & Kind, P. & Williams, A., 1996. "Valuing health states: A comparison of methods," Journal of Health Economics, Elsevier, vol. 15(2), pages 209-231, April.
- Dolan, Paul & Roberts, Jennifer, 2002. "To what extent can we explain time trade-off values from other information about respondents?," Social Science & Medicine, Elsevier, vol. 54(6), pages 919-929, March.
- William Furlong & David Feeny & George Torrance & Ronald Barr & John Horsman, 1992. "Guide to Design and Development of Health-State Utility Instrumentation," Centre for Health Economics and Policy Analysis Working Paper Series 1990-09, Centre for Health Economics and Policy Analysis (CHEPA), McMaster University, Hamilton, Canada.
- Schwartz, Carolyn E. & Sprangers, Mirjam A. G., 1999. "Methodological approaches for assessing response shift in longitudinal health-related quality-of-life research," Social Science & Medicine, Elsevier, vol. 48(11), pages 1531-1548, June.
- John Brazier & Jennifer Roberts & Aki Tsuchiya & Jan Busschbach, 2004. "A comparison of the EQ-5D and SF-6D across seven patient groups," Health Economics, John Wiley & Sons, Ltd., vol. 13(9), pages 873-884.
- Menzel, Paul & Dolan, Paul & Richardson, Jeff & Olsen, Jan Abel, 2002. "The role of adaptation to disability and disease in health state valuation: a preliminary normative analysis," Social Science & Medicine, Elsevier, vol. 55(12), pages 2149-2158, December.
- Richardson, J., 1994. "Cost utility analysis: What should be measured?," Social Science & Medicine, Elsevier, vol. 39(1), pages 7-21, July.
- Buckingham, Ken, 1993. "A note on HYE (healthy years equivalent)," Journal of Health Economics, Elsevier, vol. 12(3), pages 301-309, October.
- McCabe, C & Brazier, J & Gilks, P & Tsuchiya, A & Roberts, J & O'Hagan, A & Stevens, K, 2004. "Estimating population cardinal health state valuation models from individual ordinal (rank) health state preference data," MPRA Paper 29759, University Library of Munich, Germany.
- Louise Longworth & Stirling Bryan, 2003. "An empirical comparison of EQ-5D and SF-6D in liver transplant patients," Health Economics, John Wiley & Sons, Ltd., vol. 12(12), pages 1061-1067.
- Robinson, Angela & Dolan, Paul & Williams, Alan, 1997. "Valuing health status using VAS and TTO: What lies behind the numbers?," Social Science & Medicine, Elsevier, vol. 45(8), pages 1289-1297, October.
- Aki Tsuchiya & Shunya Ikeda & Naoki Ikegami & Shuzo Nishimura & Ikuro Sakai & Takashi Fukuda & Chisato Hamashima & Akinori Hisashige & Makoto Tamura, 2002. "Estimating an EQ-5D population value set: the case of Japan," Health Economics, John Wiley & Sons, Ltd., vol. 11(4), pages 341-353.
- Musal, R. Muzaffer & Soyer, Refik & McCabe, Christopher & Kharroubi, Samer A., 2012. "Estimating the population utility function: A parametric Bayesian approach," European Journal of Operational Research, Elsevier, vol. 218(2), pages 538-547.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Ekkehart Schlicht).
If references are entirely missing, you can add them using this form.