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The Value of Implementation and the Value of Information: Combined and Uneven Development

Author

Listed:
  • Elisabeth Fenwick

    (Public Health and Health Policy, University of Glasgow, Glasgow, UK, e.fenwick@clinmed.gla.ac.uk)

  • Karl Claxton

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

  • Mark Sculpher

    (Centre for Health Economics University of York, York, UK)

Abstract

Aim. In a budget-constrained health care 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 article presents a single, unified framework that simultaneously addresses the problem of allocating funds between these separate but linked activities. Methods. 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). Results. 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. Conclusions. Previous methods for valuing implementation strategies have not distinguished the value of efficacy research and the value of strategies to change the level 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 health care services, further research, and adopting implementation strategies that are likely to differ between technologies.

Suggested Citation

  • Elisabeth Fenwick & Karl Claxton & Mark Sculpher, 2008. "The Value of Implementation and the Value of Information: Combined and Uneven Development," Medical Decision Making, , vol. 28(1), pages 21-32, January.
    • Handle: RePEc:sae:medema:v:28:y:2008:i:1:p:21-32
    DOI: 10.1177/0272989X07308751
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    References listed on IDEAS

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    Cited by:

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    3. Karl Claxton & Elisabeth Fenwick & Mark J. Sculpher, 2012. "Decision-making with Uncertainty: The Value of Information," Chapters, in: Andrew M. Jones (ed.), The Elgar Companion to Health Economics, Second Edition, chapter 51, Edward Elgar Publishing.
    4. Hester V Eeren & Saskia J Schawo & Ron H J Scholte & Jan J V Busschbach & Leona Hakkaart, 2015. "Value of Information Analysis Applied to the Economic Evaluation of Interventions Aimed at Reducing Juvenile Delinquency: An Illustration," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-15, July.
    5. Lauren E. Cipriano & Thomas A. Weber, 2018. "Population-level intervention and information collection in dynamic healthcare policy," Health Care Management Science, Springer, vol. 21(4), pages 604-631, December.
    6. Natalia Kunst & Emily A. Burger & Veerle M. H. Coupé & Karen M. Kuntz & Eline Aas, 2024. "A Guide to an Iterative Approach to Model-Based Decision Making in Health and Medicine: An Iterative Decision-Making Framework," PharmacoEconomics, Springer, vol. 42(4), pages 363-371, April.
    7. Jeremy D. Goldhaber-Fiebert & Lauren E. Cipriano, 2023. "Pricing Treatments Cost-Effectively when They Have Multiple Indications: Not Just a Simple Threshold Analysis," Medical Decision Making, , vol. 43(7-8), pages 914-929, October.
    8. van Baal, Pieter & Morton, Alec & Severens, Johan L., 2018. "Health care input constraints and cost effectiveness analysis decision rules," Social Science & Medicine, Elsevier, vol. 200(C), pages 59-64.
    9. Dirk Müller & Eleanor Pullenayegum & Afschin Gandjour, 2015. "Impact of small study bias on cost-effectiveness acceptability curves and value of information analyses," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(2), pages 219-223, March.
    10. Anna Heath & Petros Pechlivanoglou, 2022. "Prioritizing Research in an Era of Personalized Medicine: The Potential Value of Unexplained Heterogeneity," Medical Decision Making, , vol. 42(5), pages 649-660, July.
    11. 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.
    12. Karl Claxton & Stephen Palmer & Louise Longworth & Laura Bojke & Susan Griffin & Claire McKenna & Marta Soares & Eldon Spackman & Jihee Youn, 2011. "Uncertainty, evidence and irrecoverable costs: Informing approval, pricing and research decisions for health technologies," Working Papers 069cherp, Centre for Health Economics, University of York.
    13. WH Rogowski, 2013. "An Economic Theory Of The Fourth Hurdle," Health Economics, John Wiley & Sons, Ltd., vol. 22(5), pages 600-610, May.
    14. Carlo Federici & Leandro Pecchia, 2022. "Exploring the misalignment on the value of further research between payers and manufacturers. A case study on a novel total artificial heart," Health Economics, John Wiley & Sons, Ltd., vol. 31(S1), pages 98-115, September.
    15. Sean P. Gavan & Stuart J. Wright & Fiona Thistlethwaite & Katherine Payne, 2023. "Capturing the Impact of Constraints on the Cost-Effectiveness of Cell and Gene Therapies: A Systematic Review," PharmacoEconomics, Springer, vol. 41(6), pages 675-692, June.
    16. Anna Heath, 2022. "Calculating Expected Value of Sample Information Adjusting for Imperfect Implementation," Medical Decision Making, , vol. 42(5), pages 626-636, July.
    17. 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.
    18. Jessica Ochalek & Karl Claxton & Paul Revill & Mark Sculpher & Alexandra Rollinger, 2016. "Supporting the development of an essential health package: principles and initial assessment for Malawi," Working Papers 136cherp, Centre for Health Economics, University of York.
    19. Andrew R. Willan & Simon Eckermann, 2010. "Optimal clinical trial design using value of information methods with imperfect implementation," Health Economics, John Wiley & Sons, Ltd., vol. 19(5), pages 549-561, May.
    20. Caroline S. Clarke & Cecilia Vindrola-Padros & Claire Levermore & Angus I. G. Ramsay & Georgia B. Black & Kathy Pritchard-Jones & John Hines & Gillian Smith & Axel Bex & Muntzer Mughal & David Shackle, 2021. "How to Cost the Implementation of Major System Change for Economic Evaluations: Case Study Using Reconfigurations of Specialist Cancer Surgery in Part of London, England," Applied Health Economics and Health Policy, Springer, vol. 19(6), pages 797-810, November.

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