Developing a new version of the SF-6D health state classification system from the SF-36v2: SF-6Dv2

Brazier, J; Mulhern, B; Bjorner, JB; Gandek, B; Rowen, D; Alonso, J; Vilagut, G; Ware, J

Developing a new version of the SF-6D health state classification system from the SF-36v2: SF-6Dv2

Brazier, J Mulhern, B

Bjorner, JB Gandek, B Rowen, D Alonso, J Vilagut, G Ware, J

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Publisher:: Lippincott, Williams & Wilkins
Publication Type:: Journal Article
Citation:: Medical Care, 2020, 58, (6), pp. 557-565
Issue Date:: 2020

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Field	Value	Language
dc.contributor.author	Brazier, J
dc.contributor.author	Mulhern, B https://orcid.org/0000-0003-3656-8063
dc.contributor.author	Bjorner, JB
dc.contributor.author	Gandek, B
dc.contributor.author	Rowen, D
dc.contributor.author	Alonso, J
dc.contributor.author	Vilagut, G
dc.contributor.author	Ware, J
dc.date.accessioned	2020-10-02T03:31:42Z
dc.date.available	2020-10-02T03:31:42Z
dc.date.issued	2020
dc.identifier.citation	Medical Care, 2020, 58, (6), pp. 557-565
dc.identifier.issn	0025-7079
dc.identifier.issn	1537-1948
dc.identifier.uri	http://hdl.handle.net/10453/143001
dc.description.abstract	Objective: The objective of this study was to develop the classification system for version of the SF-6D (SF-6Dv2) from the SF-36v2. SF-6Dv2 is an improved version of SF-6D, one of the most widely used generic measures of health for the calculation of quality-adjusted life years. Study Design and Setting: A 3-step process was undertaken to generate a new classification system: (1) factor analysis to establish dimensionality; (2) Rasch analysis to understand item performance; and (3) tests of differential item function. To evaluate robustness, Rasch analyses were performed in multiple subsets of 2 large cross-sectional datasets from recently discharged hospital patients and online patient samples. Results: On the basis of factor analysis, other psychometric evidence, cross-cultural considerations, and amenability to valuation, the 6-dimension classification used in SF-6D was maintained. SF-6Dv2 resulted in the following modifications to SF-6D: a simpler classification of physical function with clearer separation between levels; a more detailed 5-level description of role limitations; using negative wording to describe vitality; and using pain severity rather than pain interference. Conclusions: The SF-6Dv2 classification system describes more distinct levels of health than SF-6D, changes the descriptions used for a number of dimensions and provides clearer wording for health state valuation. The second stage of the study has developed a utility value set using discrete choice methods so that the measure can be used in health technology assessment. Further work should investigate the psychometric characteristics of the new instrument.
dc.format	Print
dc.language	eng
dc.publisher	Lippincott, Williams & Wilkins
dc.relation.ispartof	Medical Care
dc.relation.isbasedon	10.1097/MLR.0000000000001325
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	1117 Public Health and Health Services, 1402 Applied Economics
dc.subject.classification	Health Policy & Services
dc.subject.mesh	Humans
dc.subject.mesh	Pain
dc.subject.mesh	Factor Analysis, Statistical
dc.subject.mesh	Cross-Sectional Studies
dc.subject.mesh	Reproducibility of Results
dc.subject.mesh	Mental Health
dc.subject.mesh	Psychometrics
dc.subject.mesh	Health Status
dc.subject.mesh	Quality-Adjusted Life Years
dc.subject.mesh	Socioeconomic Factors
dc.subject.mesh	Adolescent
dc.subject.mesh	Adult
dc.subject.mesh	Aged
dc.subject.mesh	Middle Aged
dc.subject.mesh	Cost-Benefit Analysis
dc.subject.mesh	Female
dc.subject.mesh	Male
dc.subject.mesh	Cultural Competency
dc.subject.mesh	Young Adult
dc.subject.mesh	Social Participation
dc.subject.mesh	Surveys and Questionnaires
dc.subject.mesh	Physical Functional Performance
dc.subject.mesh	Adolescent
dc.subject.mesh	Adult
dc.subject.mesh	Aged
dc.subject.mesh	Cost-Benefit Analysis
dc.subject.mesh	Cross-Sectional Studies
dc.subject.mesh	Cultural Competency
dc.subject.mesh	Factor Analysis, Statistical
dc.subject.mesh	Female
dc.subject.mesh	Health Status
dc.subject.mesh	Humans
dc.subject.mesh	Male
dc.subject.mesh	Mental Health
dc.subject.mesh	Middle Aged
dc.subject.mesh	Pain
dc.subject.mesh	Physical Functional Performance
dc.subject.mesh	Psychometrics
dc.subject.mesh	Quality-Adjusted Life Years
dc.subject.mesh	Reproducibility of Results
dc.subject.mesh	Social Participation
dc.subject.mesh	Socioeconomic Factors
dc.subject.mesh	Surveys and Questionnaires
dc.subject.mesh	Young Adult
dc.title	Developing a new version of the SF-6D health state classification system from the SF-36v2: SF-6Dv2
dc.type	Journal Article
utslib.citation.volume	58
utslib.location.activity	United States
utslib.for	1402 Applied Economics
utslib.for	1117 Public Health and Health Services
utslib.for	1402 Applied Economics
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Strength - CHERE - Centre for Health Economics Research and Evaluation
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	open_access	*
pubs.consider-herdc	false
dc.date.updated	2020-10-02T03:31:22Z
pubs.issue	6
pubs.publication-status	Published
pubs.volume	58
utslib.citation.issue	6

Abstract:

Objective: The objective of this study was to develop the classification system for version of the SF-6D (SF-6Dv2) from the SF-36v2. SF-6Dv2 is an improved version of SF-6D, one of the most widely used generic measures of health for the calculation of quality-adjusted life years. Study Design and Setting: A 3-step process was undertaken to generate a new classification system: (1) factor analysis to establish dimensionality; (2) Rasch analysis to understand item performance; and (3) tests of differential item function. To evaluate robustness, Rasch analyses were performed in multiple subsets of 2 large cross-sectional datasets from recently discharged hospital patients and online patient samples. Results: On the basis of factor analysis, other psychometric evidence, cross-cultural considerations, and amenability to valuation, the 6-dimension classification used in SF-6D was maintained. SF-6Dv2 resulted in the following modifications to SF-6D: a simpler classification of physical function with clearer separation between levels; a more detailed 5-level description of role limitations; using negative wording to describe vitality; and using pain severity rather than pain interference. Conclusions: The SF-6Dv2 classification system describes more distinct levels of health than SF-6D, changes the descriptions used for a number of dimensions and provides clearer wording for health state valuation. The second stage of the study has developed a utility value set using discrete choice methods so that the measure can be used in health technology assessment. Further work should investigate the psychometric characteristics of the new instrument.

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http://hdl.handle.net/10453/143001