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Setting priorities for research: a practical application of ‘payback’ and expected value of information

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  • Rachael L. Fleurence

Abstract

Background: Setting priorities for research using economic in addition to scientific criteria can ensure that resources are spent efficiently and equitably. Objective: This study applies two priority setting methods ‘payback’ and expected value of information (EVI) to two research areas (osteoporosis and pressure ulcers) and where appropriate to four clinical trials: the Record Trial, the Vitamin D and Calcium Trial and the Hip Protector Trial (osteoporosis), and the Pressure Trial (wound care). Methods: Two decision‐analytic models were developed. For ‘payback’, the PATHS model was used to estimate the expected net benefits of conducting the four clinical trials. An EVI framework was applied to estimate the cost‐effectiveness of conducting further research in the two disease areas investigated. Results: The application of ‘payback’ suggests that the Record Trial and the Vitamin D and Calcium Trial would be cost‐effective. The Hip Protector and the Pressure Ulcer Trial are cost‐effective under certain assumptions concerning the likelihood of obtaining positive, negative or inconclusive results. The EVI method suggests that research would be potentially cost‐effective in these areas in the populations considered. Conclusion: EVI provides strategic information for setting priorities for research between disease areas and study populations. ‘Payback’ provides information on the cost‐effectiveness of specific research designs. However, further work in this area, particularly concerning the issue of implementation of research, is required. Copyright © 2007 John Wiley & Sons, Ltd.

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  • Rachael L. Fleurence, 2007. "Setting priorities for research: a practical application of ‘payback’ and expected value of information," Health Economics, John Wiley & Sons, Ltd., vol. 16(12), pages 1345-1357, December.
  • Handle: RePEc:wly:hlthec:v:16:y:2007:i:12:p:1345-1357
    DOI: 10.1002/hec.1225
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    References listed on IDEAS

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    1. Fleurence, Rachael L. & Torgerson, David J., 2004. "Setting priorities for research," Health Policy, Elsevier, vol. 69(1), pages 1-10, July.
    2. Elisabeth Fenwick & Karl Claxton & Mark Sculpher, 2001. "Representing uncertainty: the role of cost‐effectiveness acceptability curves," Health Economics, John Wiley & Sons, Ltd., vol. 10(8), pages 779-787, December.
    3. Claxton, Karl, 1999. "The irrelevance of inference: a decision-making approach to the stochastic evaluation of health care technologies," Journal of Health Economics, Elsevier, vol. 18(3), pages 341-364, June.
    4. James C. Felli & Gordon B. Hazen, 1998. "Sensitivity Analysis and the Expected Value of Perfect Information," Medical Decision Making, , vol. 18(1), pages 95-109, January.
    5. Steve Hanney & Andrew Davies & Martin Buxton, 1999. "Assessing benefits from health research projects: can we use questionnaires instead of case studies?," Research Evaluation, Oxford University Press, vol. 8(3), pages 189-199, December.
    6. A. E. Ades & G. Lu & K. Claxton, 2004. "Expected Value of Sample Information Calculations in Medical Decision Modeling," Medical Decision Making, , vol. 24(2), pages 207-227, March.
    7. Drummond, Michael F. & Davies, Linda M. & Ferris, Frederick L., 1992. "Assessing the costs and benefits of medical research: The diabetic retinopathy study," Social Science & Medicine, Elsevier, vol. 34(9), pages 973-981, May.
    8. Karl Claxton & John Posnett, "undated". "An Economic Approach to Clinical Trial Design and Research Priority Setting," Discussion Papers 96/19, Department of Economics, University of York.
    9. Townsend, Joy & Buxton, Martin, 1997. "Cost effectiveness scenario analysis for a proposed trial of hormone replacement therapy," Health Policy, Elsevier, vol. 39(3), pages 181-194, March.
    10. Elizabeth Fenwick & Karl Claxton & Mark Sculpher & Andrew Briggs, 2000. "Improving the efficiency and relevance of health technology assessent: the role of iterative decision analytic modelling," Working Papers 179chedp, Centre for Health Economics, University of York.
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    1. Jeffrey, Scott R. & Pannell, David J., 2013. "Economics of Prioritising Environmental Research: An Expected Value of Partial Perfect Information (EVPPI) Framework," Working Papers 144944, University of Western Australia, School of Agricultural and Resource Economics.

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