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dc.contributor.authorWhitehurst, D.
dc.contributor.authorNorman, Richard
dc.contributor.authorBrazier, J.
dc.contributor.authorViney, R.
dc.date.accessioned2017-01-30T10:49:54Z
dc.date.available2017-01-30T10:49:54Z
dc.date.created2015-04-09T09:08:01Z
dc.date.issued2014
dc.identifier.citationWhitehurst, D. and Norman, R. and Brazier, J. and Viney, R. 2014. Comparison of Contemporaneous EQ-5D and SF-6D Responses Using Scoring Algorithms Derived from Similar Valuation Exercises. Value in Health. 17 (5): pp. 570-577.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/6011
dc.identifier.doi10.1016/j.jval.2014.03.1720
dc.description.abstract

Objectives: Poor agreement between preference-based health-related quality-of-life instruments has been widely reported across patient and community-based samples. This study compares index scores generated from contemporaneous EQ-5D (3-level version) and SF-6D (SF-36 version) responses using scoring algorithms derived from independently-conducted Australian population-representative discrete choice experiments (DCEs), providing the first comparative analysis of health state valuations using the same method of valuation across the full value sets. Methods: EQ-5D and SF-6D responses from seven patient data sets were transformed into health state valuations using published DCE-derived scoring algorithms. The empirical comparative evaluation consisted of graphical illustration of the location and spread of index scores, reporting of basic descriptive statistics, exploration of between-measure differences in mean index scores, and analysis of agreement. Results: Compared with previously published findings regarding the comparability of “conventional” EQ-5D and SF-6D index scores, health state valuations from the DCE-derived scoring procedures showed that agreement between scores remained “fair” (intraclass correlation coefficient values across the seven data sets ranged from 0.375 to 0.615). Mean SF-6D scores were significantly lower than the respective mean EQ-5D score across all patient groups (mean difference for the whole sample = 0.253).Conclusions: The magnitude of disagreement previously reported between EQ-5D and SF-6D index scores is not ameliorated through the application of DCE-derived value sets; sizeable discrepancies remain. These findings suggest that differences between EQ-5D and SF-6D index scores persist because of their respective descriptive systems. Further research is required to explore the implications of variations in the descriptive systems of preference-based instruments.

dc.publisherWiley-Blackwell Publishing, Inc.
dc.titleComparison of Contemporaneous EQ-5D and SF-6D Responses Using Scoring Algorithms Derived from Similar Valuation Exercises
dc.typeJournal Article
dcterms.source.volume17
dcterms.source.number5
dcterms.source.startPage570
dcterms.source.endPage577
dcterms.source.issn1098-3015
dcterms.source.titleValue in Health
curtin.accessStatusOpen access via publisher


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