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Globally optimal trial design for local decision making

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  • Simon Eckermann
  • Andrew R. Willan

Abstract

Value of information methods allows decision makers to identify efficient trial design following a principle of maximizing the expected value to decision makers of information from potential trial designs relative to their expected cost. However, in health technology assessment (HTA) the restrictive assumption has been made that, prospectively, there is only expected value of sample information from research commissioned within jurisdiction. This paper extends the framework for optimal trial design and decision making within jurisdiction to allow for optimal trial design across jurisdictions. This is illustrated in identifying an optimal trial design for decision making across the US, the UK and Australia for early versus late external cephalic version for pregnant women presenting in the breech position. The expected net gain from locally optimal trial designs of US$0.72M is shown to increase to US$1.14M with a globally optimal trial design. In general, the proposed method of globally optimal trial design improves on optimal trial design within jurisdictions by: (i) reflecting the global value of non‐rival information; (ii) allowing optimal allocation of trial sample across jurisdictions; (iii) avoiding market failure associated with free‐rider effects, sub‐optimal spreading of fixed costs and heterogeneity of trial information with multiple trials. Copyright © 2008 John Wiley & Sons, Ltd.

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  • Simon Eckermann & Andrew R. Willan, 2009. "Globally optimal trial design for local decision making," Health Economics, John Wiley & Sons, Ltd., vol. 18(2), pages 203-216, February.
  • Handle: RePEc:wly:hlthec:v:18:y:2009:i:2:p:203-216
    DOI: 10.1002/hec.1353
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    References listed on IDEAS

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    Cited by:

    1. Simon Eckermann & Andrew Willan, 2011. "Presenting Evidence and Summary Measures to Best Inform Societal Decisions When Comparing Multiple Strategies," PharmacoEconomics, Springer, vol. 29(7), pages 563-577, July.
    2. 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.
    3. Hendrik Koffijberg & Claire Rothery & Kalipso Chalkidou & Janneke Grutters, 2018. "Value of Information Choices that Influence Estimates: A Systematic Review of Prevailing Considerations," Medical Decision Making, , vol. 38(7), pages 888-900, October.
    4. Mark Strong & Jeremy E. Oakley & Alan Brennan & Penny Breeze, 2015. "Estimating the Expected Value of Sample Information Using the Probabilistic Sensitivity Analysis Sample," Medical Decision Making, , vol. 35(5), pages 570-583, July.
    5. Andrew R. Willan & Simon Eckermann, 2012. "Accounting For Between‐Study Variation In Incremental Net Benefit In Value Of Information Methodology," Health Economics, John Wiley & Sons, Ltd., vol. 21(10), pages 1183-1195, October.
    6. Edward C. F. Wilson & Miranda Mugford & Garry Barton & Lee Shepstone, 2016. "Efficient Research Design," Medical Decision Making, , vol. 36(3), pages 335-348, April.
    7. Lou Garrison;Ruth Puig-Peiro;Adrian Towse, 2012. "The Use of Pay-for-Performance for Drugs: Can It Improve Incentives for Innovation?," Occasional Paper 000167, Office of Health Economics.
    8. David O. Meltzer & Ties Hoomans & Jeanette W. Chung & Anirban Basu, 2011. "Minimal Modeling Approaches to Value of Information Analysis for Health Research," Medical Decision Making, , vol. 31(6), pages 1-22, November.
    9. Andrew Willan, 2011. "Sample Size Determination for Cost-Effectiveness Trials," PharmacoEconomics, Springer, vol. 29(11), pages 933-949, November.
    10. Andrew Willan & Simon Eckermann, 2012. "Value of Information and Pricing New Healthcare Interventions," PharmacoEconomics, Springer, vol. 30(6), pages 447-459, June.
    11. Mathyn Vervaart & Mark Strong & Karl P. Claxton & Nicky J. Welton & Torbjørn Wisløff & Eline Aas, 2022. "An Efficient Method for Computing Expected Value of Sample Information for Survival Data from an Ongoing Trial," Medical Decision Making, , vol. 42(5), pages 612-625, July.
    12. 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.
    13. Lotte Steuten & Gijs Wetering & Karin Groothuis-Oudshoorn & Valesca Retèl, 2013. "A Systematic and Critical Review of the Evolving Methods and Applications of Value of Information in Academia and Practice," PharmacoEconomics, Springer, vol. 31(1), pages 25-48, January.
    14. Susan C. Griffin & Karl P. Claxton & Stephen J. Palmer & Mark J. Sculpher, 2011. "Dangerous omissions: the consequences of ignoring decision uncertainty," Health Economics, John Wiley & Sons, Ltd., vol. 20(2), pages 212-224, February.

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