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    Estimating Health-State Utility for Economic Models in Clinical Studies: an ISPOR Good Research Practices Task Force Report

    Access Status
    Fulltext not available
    Authors
    Wolowacz, S.
    Briggs, A.
    Belozeroff, V.
    Clarke, P.
    Doward, L.
    Goeree, R.
    Lloyd, A.
    Norman, Richard
    Date
    2016
    Type
    Journal Article
    
    Metadata
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    Citation
    Wolowacz, S. and Briggs, A. and Belozeroff, V. and Clarke, P. and Doward, L. and Goeree, R. and Lloyd, A. et al. 2016. Estimating Health-State Utility for Economic Models in Clinical Studies: an ISPOR Good Research Practices Task Force Report. Value in Health. 19 (6): pp. 704-719.
    Source Title
    Value in Health
    DOI
    10.1016/j.jval.2016.06.001
    ISSN
    1524-4733
    School
    Department of Health Policy and Management
    URI
    http://hdl.handle.net/20.500.11937/38646
    Collection
    • Curtin Research Publications
    Abstract

    Cost-utility models are increasingly used in many countries to establish whether the cost of a new intervention can be justified in terms of health benefits. Health-state utility (HSU) estimates (the preference for a given state of health on a cardinal scale where 0 represents dead and 1 represents full health) are typically among the most important and uncertain data inputs in cost-utility models. Clinical trials represent an important opportunity for the collection of health-utility data. However, trials designed primarily to evaluate efficacy and safety often present challenges to the optimal collection of HSU estimates for economic models. Careful planning is needed to determine which of the HSU estimates may be measured in planned trials; to establish the optimal methodology; and to plan any additional studies needed. This report aimed to provide a framework for researchers to plan the collection of health-utility data in clinical studies to provide high-quality HSU estimates for economic modeling. Recommendations are made for early planning of health-utility data collection within a research and development program; design of health-utility data collection during protocol development for a planned clinical trial; design of prospective and cross-sectional observational studies and alternative study types; and statistical analyses and reporting.

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