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The impact of adding an extra dimension to a preference-based measure

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  • Brazier, John
  • Rowen, Donna
  • Tsuchiya, Aki
  • Yang, Yaling
  • Young, Tracy A.

Abstract

The ability to compare incremental changes in Quality Adjusted Life Years (QALYs) generated by different condition-specific preference-based measures (CSPBMs), or indeed between generic measures, is often criticised even where the valuation methods and source of values are the same. A key concern is the impact of excluding key dimensions from a descriptive system. This study examines the impact of adding a generic pain/discomfort dimension to a CSPBM, the AQL-5D (an asthma-specific CSPBM), by valuing samples of states from the AQL-5D with and without the new dimension using an interviewer administered time trade-off with a sample of the UK general public. 180 respondents provided 720 valuations for states with and without pain/discomfort. As expected the additional pain/discomfort dimension was found to have a significant and relatively large coefficient. More importantly for comparing changes in QALYs across populations the addition of pain/discomfort significantly impacts on the coefficients of the other dimensions and the degree of impact differs by dimension and severity level. The net effect on the utility value depends on the severity of their state: the addition of pain/discomfort at level 1 (no pain/discomfort) or 2 (moderate pain/discomfort) significantly increased the mean health state values in an asthma patient population; whereas level 3 pain/discomfort (extreme) reduced values. Comparability between measures requires that the impact of different dimensions on preferences is additive, whether or not they are included in the classification system. Our results cast doubt on this assumption, implying that the chosen measure must contain all important and relevant dimensions in its classification system.

Suggested Citation

  • Brazier, John & Rowen, Donna & Tsuchiya, Aki & Yang, Yaling & Young, Tracy A., 2011. "The impact of adding an extra dimension to a preference-based measure," Social Science & Medicine, Elsevier, vol. 73(2), pages 245-253, July.
    • Handle: RePEc:eee:socmed:v:73:y:2011:i:2:p:245-253
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    References listed on IDEAS

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    10. Julie Ratcliffe & John Brazier & Aki Tsuchiya & Tara Symonds & Martin Brown, 2009. "Using DCE and ranking data to estimate cardinal values for health states for deriving a preference‐based single index from the sexual quality of life questionnaire," Health Economics, John Wiley & Sons, Ltd., vol. 18(11), pages 1261-1276, November.
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    1. Yaling Yang & John Brazier & Aki Tsuchiya, 2014. "Effect of Adding a Sleep Dimension to the EQ-5D Descriptive System," Medical Decision Making, , vol. 34(1), pages 42-53, January.
    2. John Brazier & Jennifer Roberts & Donna Rowen, 2012. "Methods for Developing Preference-based Measures of Health," Chapters, in: Andrew M. Jones (ed.), The Elgar Companion to Health Economics, Second Edition, chapter 37, Edward Elgar Publishing.
    3. Aureliano Paolo Finch & John Brazier & Clara Mukuria, 2021. "Selecting Bolt-on Dimensions for the EQ-5D: Testing the Impact of Hearing, Sleep, Cognition, Energy, and Relationships on Preferences Using Pairwise Choices," Medical Decision Making, , vol. 41(1), pages 89-99, January.
    4. McDonald, Rebecca & Mullett, Timothy L. & Tsuchiya, Aki, 2020. "Understanding the composite dimensions of the EQ-5D: An experimental approach," Social Science & Medicine, Elsevier, vol. 265(C).
    5. Koonal K. Shah & Bryan Bennett & Andrew Lenny & Louise Longworth & John E. Brazier & Mark Oppe & A. Simon Pickard & James W. Shaw, 2021. "Adapting preference-based utility measures to capture the impact of cancer treatment-related symptoms," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(8), pages 1301-1309, November.

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