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Measuring the value of health-related quality of life

  • Graeme Hawthorne
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Abstract

Health-related quality of life is concerned with the relationship between the effect of treatment on the patient’s life with society’s value for this effect. It is only through balancing these two concerns that transparent decisions concerning the best choice of treatment at the intervention level and, at the policy level, the allocation of scarce health resources can incorporate both the patient’s and society’s views. Where these decisions are important, the appropriate form of evaluation is cost-utility analysis (CUA). With rising health care costs, the ageing of populations and the determination of governments to cap health care expenditure, the mental health field will increasingly be asked for evidence of its cost-effectiveness. In the absence of such evidence, patients access to mental health services in the future may be hindered and the choice of treatment restricted as decision-makers may be disinclined to increase or even maintain funding.

This paper reviews the axioms of cost-utility analysis and the role of multi-attribute (MAU) utility instruments. Seven leading instruments are reviewed, and examples of their use in cost-utility analysis in the mental health field are presented. It is concluded that none of the existing instruments fully meet the axioms of either utility or measurement theory, and that the instruments provide HRQoL estimates that are so different that study outcomes are likely to be as much a function of the instrument chosen for a particular study as the effectiveness of the intervention itself.

It is recommended that mental health professionals undertaking CUAs review available instruments carefully, use two MAU-instruments in any particular study, and report both sets of results. The shortcomings of existing MAU-instruments should not be taken as a reason to avoid economic evaluation; at the moment they are the only practical way of capturing the balance described above. Few CUA studies have been carried out in the mental health field, there is thus an opportunity to undertake studies providing the evidence needed by clinicians and decision-makers for transparent decisions regarding treatment options and the future funding of mental health care

Key words

AQoL Burden of disease Cost-effectiveness Cost-utility analysis CUA Economic evaluation EQ5D Health-related quality of life HUI3 15D Multi-attribute utility instrument Quality-adjusted life years QALY QWB Rosser Index SF6D 

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Copyright information

© springer 2007

Authors and Affiliations

  • Graeme Hawthorne
    • 1
  1. 1.Department of PsychiatryThe University of MelbourneAustralia

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