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The Relationship between Descriptive and Valuational Quality-of-life Measures in Patients with Intermittent Claudication

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  • Johanna L. Bosch
  • Maria G.M. Hunink

Abstract

The study objective was to assess the relationship between descriptive and valuational quality-of-life measures in patients with intermittent claudication. In telephone inter views, 68 patients completed a questionnaire consisting of a descriptive health status measure (RAND 36-Item Health Survey 1.0), and several valuational measures (stan dard gamble, time tradeoff, rating scale, and McMaster health utility index). All mea sures demonstrated reduced quality of life in the patients. Scores on the RAND-36 dimensions correlated moderately well with the rating scale and McMaster health utility index (R = 0.37-0.67) but less well with the standard gamble and the time tradeoff (R = 0.10-0.46). Multiple regression analysis demonstrated that 28% of the variance in the time-tradeoff values and 14% of the variance of the standard-gamble utilities could be explained by the best combination of RAND dimensions. These results suggest that answers to descriptive health-status questions cannot reliably predict standard-gamble utilities or time-tradeoff values. Key words: quality of life; health status; utility assess ment ; peripheral vascular diseases; intermittent claudication. (Med Decis Making 1996;16:217-225)

Suggested Citation

  • Johanna L. Bosch & Maria G.M. Hunink, 1996. "The Relationship between Descriptive and Valuational Quality-of-life Measures in Patients with Intermittent Claudication," Medical Decision Making, , vol. 16(3), pages 217-225, August.
    • Handle: RePEc:sae:medema:v:16:y:1996:i:3:p:217-225
    DOI: 10.1177/0272989X9601600305
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    References listed on IDEAS

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    1. D Feeny & G Torrance, 1989. "Incorporating Utility-based Quality-of-life Assessment Measures in Clinical Trials: Two Examples," Centre for Health Economics and Policy Analysis Working Paper Series 12, Centre for Health Economics and Policy Analysis (CHEPA), McMaster University, Hamilton, Canada.
    2. Nord, Erik, 1992. "Methods for quality adjustment of life years," Social Science & Medicine, Elsevier, vol. 34(5), pages 559-569, March.
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    2. Burstrom, Kristina & Johannesson, Magnus & Diderichsen, Finn, 2006. "A comparison of individual and social time trade-off values for health states in the general population," Health Policy, Elsevier, vol. 76(3), pages 359-370, May.
    3. John Brazier & Yaling Yang & Aki Tsuchiya & Donna Rowen, 2010. "A review of studies mapping (or cross walking) non-preference based measures of health to generic preference-based measures," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 11(2), pages 215-225, April.
    4. Gerdtham, U. -G. & Johannesson, M. & Lundberg, L. & Isacson, D., 1999. "The demand for health: results from new measures of health capital," European Journal of Political Economy, Elsevier, vol. 15(3), pages 501-521, September.
    5. Jan Roelf Bult & Johanna L. Bosch & Maria G.M. Hunink, 1996. "Heterogeneity in the Relationship between the Standard-gamble Utility Measure and Health-status Dimensions," Medical Decision Making, , vol. 16(3), pages 226-233, August.
    6. Karen Gerard & Katharine Johnston & Jackie Brown, 1999. "The role of a pre‐scored multi‐attribute health classification measure in validating condition‐specific health state descriptions," Health Economics, John Wiley & Sons, Ltd., vol. 8(8), pages 685-699, December.
    7. G. Ardine De Wit & Jan J.V. Busschbach & Frank Th. De Charro, 2000. "Sensitivity and perspective in the valuation of health status: whose values count?," Health Economics, John Wiley & Sons, Ltd., vol. 9(2), pages 109-126, March.

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