Literature DB >> 8161982

Relationship between psychometric and utility-based approaches to the measurement of health-related quality of life.

D A Revicki1, R M Kaplan.   

Abstract

This paper summarizes selected evidence pertaining to the relationship between psychometric health status measures and utility/preference measures of health outcome. Few studies contain measures of both health status and utility/preference. The evidence to date suggests that various health status measures are at best only moderately correlated with standard gamble (SG) and time trade-off (TTO) utilities. Results from regression analysis, predicting SG or TTO utilities from combinations of health status scales, typically have an R2 of 0.18 to 0.43. Preferences determined by rating scale methods are more strongly related to health status scores, but correlations are variable ranging from 0.17 to 0.46 and only about 27% to 34% of variance can be explained in regression models. The Quality of Well-Being Scale and other multi-attribute preference measures have low to moderate correlations with health status measures (r = 0.03 to 0.71). Health utility/preference measures and psychometric health status scores are only moderately correlated. Health utility and psychometric health status scales may measure different attributes of health. Although both approaches are useful for evaluating medical outcomes, they are not interchangeable indicators of health-related quality of life.

Mesh:

Year:  1993        PMID: 8161982     DOI: 10.1007/bf00422222

Source DB:  PubMed          Journal:  Qual Life Res        ISSN: 0962-9343            Impact factor:   4.147


  34 in total

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9.  Measurement of quality of life in end-stage renal disease: the time trade-off approach.

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Authors:  G H Guyatt; D H Feeny; D L Patrick
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  60 in total

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4.  The effect of individually assessed preference weights on the relationship between holistic utilities and nonpreference-based assessment.

Authors:  S J Jansen; A M Stiggelbout; M A Nooij; J Kievit
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5.  Quality of life related to fear of falling and hip fracture in older women: a time trade off study.

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Journal:  BMJ       Date:  2000-02-05

6.  The case for domains of function in quality of life assessment.

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Journal:  Qual Life Res       Date:  2003       Impact factor: 4.147

7.  Testing subject comprehension of utility questionnaires.

Authors:  Deborah G Dobrez; Elizabeth A Calhoun
Journal:  Qual Life Res       Date:  2004-03       Impact factor: 4.147

8.  Using the effect size to model change in preference values from descriptive health status.

Authors:  Kristy Sanderson; Gavin Andrews; Justine Corry; Helen Lapsley
Journal:  Qual Life Res       Date:  2004-09       Impact factor: 4.147

9.  Economic evaluation in healthcare. A brief history and future directions.

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Review 10.  Measuring the effect of cancer on health-related quality of life.

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