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

Authors: Brazier, J; Rowen, D; Tsuchiya, A; Yang, Y; Young, T;

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

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 U.K. 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.

Country
United Kingdom
Keywords

Adult, Male, Adolescent, Psychometrics, Preference-based measures of health, Pain, Cross programme comparability, Severity of Illness Index, Article, Health(social science), Interview, Psychological, Health Status Indicators, Humans, UK, Aged, Pain Measurement, condition-specific measures, Analysis of Variance, Chi-Square Distribution, Data Collection, Middle Aged, Asthma, cross programme comparability, Condition-specific measures, Patient Satisfaction, Regression Analysis, Female, Quality-Adjusted Life Years

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    16
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
16
Top 10%
Top 10%
Top 10%
Green
hybrid