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Why do multi-attribute utility instruments produce different utilities: the relative importance of the descriptive systems, scale and 'micro-utility' effects.

Richardson J, Iezzi A, Khan MA - Qual Life Res (2015)

Bottom Line: Scale effects were determined by the linear relationship between utilities, the effect of the descriptive system by comparison of scale-adjusted values and 'micro-utility effects' by the unexplained difference between utilities and values.Overall, 66 % of the differences between utilities was attributable to the descriptive systems, 30.3 % to scale effects and 3.7 % to micro-utility effects.Other differences, attributable to utility formula, are comparatively unimportant.

View Article: PubMed Central - PubMed

Affiliation: Centre for Health Economics, Monash Business School, Monash University, Wellington Road, Clayton, VIC, 3800, Australia, jeffrey.richardson@monash.edu.

ABSTRACT

Purpose: Health state utilities measured by the major multi-attribute utility instruments differ. Understanding the reasons for this is important for the choice of instrument and for research designed to reconcile these differences. This paper investigates these reasons by explaining pairwise differences between utilities derived from six multi-attribute utility instruments in terms of (1) their implicit measurement scales; (2) the structure of their descriptive systems; and (3) 'micro-utility effects', scale-adjusted differences attributable to their utility formula.

Methods: The EQ-5D-5L, SF-6D, HUI 3, 15D and AQoL-8D were administered to 8,019 individuals. Utilities and unweighted values were calculated using each instrument. Scale effects were determined by the linear relationship between utilities, the effect of the descriptive system by comparison of scale-adjusted values and 'micro-utility effects' by the unexplained difference between utilities and values.

Results: Overall, 66 % of the differences between utilities was attributable to the descriptive systems, 30.3 % to scale effects and 3.7 % to micro-utility effects.

Discussion: Results imply that the revision of utility algorithms will not reconcile differences between instruments. The dominating importance of the descriptive system highlights the need for researchers to select the instrument most capable of describing the health states relevant for a study.

Conclusions: Reconciliation of inconsistent utilities produced by different instruments must focus primarily upon the content of the descriptive system. Utility weights primarily determine the measurement scale. Other differences, attributable to utility formula, are comparatively unimportant.

No MeSH data available.


Related in: MedlinePlus

Hypothetical utilities, U, values, V and scores, S
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getmorefigures.php?uid=PMC4493939&req=5

Fig1: Hypothetical utilities, U, values, V and scores, S

Mentions: The methods detailed below are illustrated in Fig. 1. This plots scores, Si, Sj, derived by summing item responses from two MAU instruments, MAUIi and MAUIj on the horizontal axis, and the corresponding utilities, U, and values, V, on the vertical axis. Values are a linear transformation of scores and are represented by the lines XY and ZY. Due to the micro-utility effects of the MAU formula, the corresponding instrument utilities are scattered randomly around the two lines. The differing measurement scales embodied in the utility formula are illustrated by the differing slopes of XY and ZY. For a given individual, A, the scores from the unweighted instruments SiA, SjA differ. Application of the two MAUI formulae result in estimates of utility which differ by (UiA − UjA). The aim of the analysis below is to attribute this difference to a difference in the scale (ViA − VjA), a difference in the micro-utility effect (ViA − UiA) and (VjA − UjA) and the effect attributable to the structure of the descriptive systems which results in the difference, SiA − SjA.Fig. 1


Why do multi-attribute utility instruments produce different utilities: the relative importance of the descriptive systems, scale and 'micro-utility' effects.

Richardson J, Iezzi A, Khan MA - Qual Life Res (2015)

Hypothetical utilities, U, values, V and scores, S
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4493939&req=5

Fig1: Hypothetical utilities, U, values, V and scores, S
Mentions: The methods detailed below are illustrated in Fig. 1. This plots scores, Si, Sj, derived by summing item responses from two MAU instruments, MAUIi and MAUIj on the horizontal axis, and the corresponding utilities, U, and values, V, on the vertical axis. Values are a linear transformation of scores and are represented by the lines XY and ZY. Due to the micro-utility effects of the MAU formula, the corresponding instrument utilities are scattered randomly around the two lines. The differing measurement scales embodied in the utility formula are illustrated by the differing slopes of XY and ZY. For a given individual, A, the scores from the unweighted instruments SiA, SjA differ. Application of the two MAUI formulae result in estimates of utility which differ by (UiA − UjA). The aim of the analysis below is to attribute this difference to a difference in the scale (ViA − VjA), a difference in the micro-utility effect (ViA − UiA) and (VjA − UjA) and the effect attributable to the structure of the descriptive systems which results in the difference, SiA − SjA.Fig. 1

Bottom Line: Scale effects were determined by the linear relationship between utilities, the effect of the descriptive system by comparison of scale-adjusted values and 'micro-utility effects' by the unexplained difference between utilities and values.Overall, 66 % of the differences between utilities was attributable to the descriptive systems, 30.3 % to scale effects and 3.7 % to micro-utility effects.Other differences, attributable to utility formula, are comparatively unimportant.

View Article: PubMed Central - PubMed

Affiliation: Centre for Health Economics, Monash Business School, Monash University, Wellington Road, Clayton, VIC, 3800, Australia, jeffrey.richardson@monash.edu.

ABSTRACT

Purpose: Health state utilities measured by the major multi-attribute utility instruments differ. Understanding the reasons for this is important for the choice of instrument and for research designed to reconcile these differences. This paper investigates these reasons by explaining pairwise differences between utilities derived from six multi-attribute utility instruments in terms of (1) their implicit measurement scales; (2) the structure of their descriptive systems; and (3) 'micro-utility effects', scale-adjusted differences attributable to their utility formula.

Methods: The EQ-5D-5L, SF-6D, HUI 3, 15D and AQoL-8D were administered to 8,019 individuals. Utilities and unweighted values were calculated using each instrument. Scale effects were determined by the linear relationship between utilities, the effect of the descriptive system by comparison of scale-adjusted values and 'micro-utility effects' by the unexplained difference between utilities and values.

Results: Overall, 66 % of the differences between utilities was attributable to the descriptive systems, 30.3 % to scale effects and 3.7 % to micro-utility effects.

Discussion: Results imply that the revision of utility algorithms will not reconcile differences between instruments. The dominating importance of the descriptive system highlights the need for researchers to select the instrument most capable of describing the health states relevant for a study.

Conclusions: Reconciliation of inconsistent utilities produced by different instruments must focus primarily upon the content of the descriptive system. Utility weights primarily determine the measurement scale. Other differences, attributable to utility formula, are comparatively unimportant.

No MeSH data available.


Related in: MedlinePlus