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The value of implementation and the value of information: combined and uneven development

Author

Listed:
  • Elisabeth Fenwick

    (Department of Economics and Related Studies, University of York; Centre for Health Economics, University of York)

  • Karl Claxton

    (Department of Economics and Related Studies, University of York; Centre for Health Economics, University of York)

  • Mark Sculpher

    (Centre for Health Economics, University of York)

Abstract

In a budget constrained healthcare system the decision to invest in strategies to improve the implementation of cost-effective technologies must be made alongside decisions regarding investment in the technologies themselves and investment in further research. This paper presents a single, unified framework that simultaneously addresses the problem of allocating funds between these separate but linked activities. The framework presents a simple 4 state world where both information and implementation can be either at the current level or ‘perfect’. Through this framework it is possible to determine the maximum return to further research and an upper bound on the value of adopting implementation strategies. The framework is illustrated through case studies of health care technologies selected from those previously considered by the UK National Institute for Health and Clinical Excellence (NICE). Through the case studies, several key factors that influence the expected values of perfect information and perfect implementation are identified. These factors include the maximum acceptable cost-effectiveness ratio, the level of uncertainty surrounding the adoption decision, the expected net benefits associated with the technologies, the current level of implementation and the size of the eligible population. Previous methods for valuing implementation strategies have confused the value of research and the value of implementation. This framework demonstrates that the value of information and the value of implementation can be examined separately but simultaneously in a single framework. This can usefully inform policy decisions about investment in healthcare services, further research and adopting implementation strategies which are likely to differ between technologies.

Suggested Citation

  • Elisabeth Fenwick & Karl Claxton & Mark Sculpher, 2005. "The value of implementation and the value of information: combined and uneven development," Working Papers 005cherp, Centre for Health Economics, University of York.
    • Handle: RePEc:chy:respap:5cherp
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    References listed on IDEAS

    as
    1. Johannesson, Magnus & Weinstein, Milton C., 1993. "On the decision rules of cost-effectiveness analysis," Journal of Health Economics, Elsevier, vol. 12(4), pages 459-467, December.
    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. Karl Claxton & Simon Eggington & Laura Ginnelly & Susan Griffin & Christopher McCabe & Zoe Philips & Paul Tappenden & Alan Wailoo, 2005. "A Pilot Study of Value of Information Analysis to Support Research Recommendations for the National Institute for Health and Clinical Excellence," Working Papers 004cherp, Centre for Health Economics, University of York.
    5. 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.
    6. Aaron A. Stinnett & John Mullahy, 1998. "Net Health Benefits: A New Framework for the Analysis of Uncertainty in Cost-Effectiveness Analysis," NBER Technical Working Papers 0227, National Bureau of Economic Research, Inc.
    7. 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.
    8. Dranove, David, 1998. "Is there underinvestment in R & D about prevention?," Journal of Health Economics, Elsevier, vol. 17(1), pages 117-127, January.
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    Cited by:

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    2. Oakley, Jeremy E. & Brennan, Alan & Tappenden, Paul & Chilcott, Jim, 2010. "Simulation sample sizes for Monte Carlo partial EVPI calculations," Journal of Health Economics, Elsevier, vol. 29(3), pages 468-477, May.
    3. 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.

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