Literature DB >> 12457369

QALY-maximisation and public preferences: results from a general population survey.

Stirling Bryan1, Tracy Roberts, Chris Heginbotham, Alison McCallum.   

Abstract

The appropriate criteria that should be used in setting priorities in a publicly funded health care system remain open to debate. From a health economics perspective, quality-adjusted life years (QALYs) are increasingly portrayed as a measure of societal value and the criterion of QALY maximisation is then advocated. This paper reports a study that investigated the extent to which some of the assumptions underlying the QALY maximisation approach, notably constant marginal societal value for increases in the size of health programmes, the level of risk, and the level of benefit are supported by members of the public. A general population interview-based survey was conducted. The survey design employed conjoint methods. In general, the public preference data from this study, in themselves, are not much at odds with the core proportionality assumptions concerning societal value in the QALY maximisation model assumptions. The data are, however, at odds with reports from various previous studies. Copyright 2002 John Wiley & Sons, Ltd.

Mesh:

Year:  2002        PMID: 12457369     DOI: 10.1002/hec.695

Source DB:  PubMed          Journal:  Health Econ        ISSN: 1057-9230            Impact factor:   3.046


  9 in total

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Review 2.  A systematic review of stated preference studies reporting public preferences for healthcare priority setting.

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4.  What Does the Public Want? Structural Consideration of Citizen Preferences in Health Care Coverage Decisions.

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7.  Prioritising health service innovation investments using public preferences: a discrete choice experiment.

Authors:  Seda Erdem; Carl Thompson
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8.  Industry Perspectives on Market Access of Innovative Drugs: The Relevance for Oncology Drugs.

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9.  Comparison of Modes of Administration and Alternative Formats for Eliciting Societal Preferences for Burden of Illness.

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Journal:  Appl Health Econ Health Policy       Date:  2016-02       Impact factor: 2.561

  9 in total

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