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Guide to Design and Development of Health-State Utility Instrumentation

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Author Info

  • William Furlong

    (Department of Clinical Epidemiology & Biostatistics, McMaster University)

  • David Feeny

    (Department of Clinical Epidemiology & Biostatistics, Department of Economics, Centre for Health Economics & Policy Analysis, McMaster University)

  • George Torrance

    (Department of Clinical Epidemiology & Biostatistics, Department of Business, Centre for Health Economics & Policy Analysis, McMaster University)

  • Ronald Barr

    (Department of Pediatrics, McMaster University)

  • John Horsman

    (Department of Medicine, McMaster University)

Abstract

Growing interest in methods of quantifying health-related quality of life has resulted in demand for a manual describing general techniques that may be customized by health researchers and used to measure preferences in applications having a wide variety of objectives. This report is intended to provide practice guidelines to researchers who require information about the design, construction and administration of instruments used to obtain estimates of health utility. The focus is on the steps required to conduct a study in which preferences are measured; the theory that underlies utility measurement is not presented. Utility scores may be used to assess the health-related quality of life for specific health states. Utility scores are also useful in evaluations, such as cost-utility analyses, in which the costs of health care interventions are compared to their consequences both in terms of quantity and quality of life. In order to obtain reliable, valid, and responsive utility scores, however, the instruments must be carefully designed, tested and executed. Experience to date indicates that careful instrument development requires time, effort and care. Three major instruments are described: rating scale, standard gamble and time trade-off. Methodologically correct techniques are recommended where possible and suggestions, based on experience, are presented for situation in which theoretical or empirical evidence is lacking. The guide discusses the criteria for selection of techniques, materials, interviewers and respondents. Examples of an interviewer training manual, interview scripts and data recording forms are also included. Detailed diagrams provide specifications for assembling visual aids (i.e., interviewing props) and an extensive bibliography will direct readers interested in specific issues to appropriate references.

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Bibliographic Info

Paper provided by Centre for Health Economics and Policy Analysis (CHEPA), McMaster University, Hamilton, Canada in its series Centre for Health Economics and Policy Analysis Working Paper Series with number 1990-09.

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Length: 148 pages
Date of creation: 1992
Date of revision:
Handle: RePEc:hpa:wpaper:199009

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Cited by:
  1. Valerie Seror, 2008. "Fitting observed and theoretical choices - women's choices about prenatal diagnosis of Down syndrome," Health Economics, John Wiley & Sons, Ltd., vol. 17(5), pages 557-577.
  2. Brazier, J & Dolan, P, 2005. "Evidence of preference construction in a comparison of variants of the standard gamble method," MPRA Paper 29760, University Library of Munich, Germany.
  3. Zafar Hakim & Dev S. Pathak, 1999. "Modelling the EuroQol data: a comparison of discrete choice conjoint and conditional preference modelling," Health Economics, John Wiley & Sons, Ltd., vol. 8(2), pages 103-116.
  4. Paul McNamee & Sharon Glendinning & Jonathan Shenfine & Nick Steen & S. Griffin & John Bond, 2004. "Chained time trade-off and standard gamble methods," The European Journal of Health Economics, Springer, vol. 5(1), pages 81-86, February.
  5. McCabe, C & Stevens, K & Roberts, J & Brazier, JE, 2003. "Health state values for the HUI 2 descriptive system: results from a UK survey," MPRA Paper 29744, University Library of Munich, Germany.
  6. Brazier, J, 2005. "Current state of the art in preference-based measures of health and avenues for further research," MPRA Paper 29762, University Library of Munich, Germany.
  7. Katherine J. Stevens & Christopher J. McCabe & John E. Brazier, 2006. "Mapping between Visual Analogue Scale and Standard Gamble data; results from the UK Health Utilities Index 2 valuation survey," Health Economics, John Wiley & Sons, Ltd., vol. 15(5), pages 527-533.
  8. McCabe, Christopher & Brazier, John & Gilks, Peter & Tsuchiya, Aki & Roberts, Jennifer & O'Hagan, Anthony & Stevens, Katherine, 2006. "Using rank data to estimate health state utility models," Journal of Health Economics, Elsevier, vol. 25(3), pages 418-431, May.
  9. 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.
  10. Andrew Lloyd & Scott Doyle & Sarah Dewilde & Florian Turk, 2008. "Preferences and utilities for the symptoms of moderate to severe allergic asthma," The European Journal of Health Economics, Springer, vol. 9(3), pages 275-284, August.
  11. 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.
  12. 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.
  13. 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.
  14. Arthur Attema & Yvette Edelaar-Peeters & Matthijs Versteegh & Elly Stolk, 2013. "Time trade-off: one methodology, different methods," The European Journal of Health Economics, Springer, vol. 14(1), pages 53-64, July.

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