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The Option Value of Delay in Health Technology Assessment

Author

Listed:
  • Simon Eckermann

    (Flinders University Centre for Clinical Change and Health Care Research, Adelaide, Australia, simon.eckermann@flinders.edu.au)

  • Andrew R. Willan

    (Sick-Kids Research Institute and University of Toronto, Toronto, Ontario)

Abstract

Processes of health technology assessment (HTA) inform decisions under uncertainty about whether to invest in new technologies based on evidence of incremental effects, incremental cost, and incremental net benefit monetary (INMB). An option value to delaying such decisions to wait for further evidence is suggested in the usual case of interest, in which the prior distribution of INMB is positive but uncertain. Methods of estimating the option value of delaying decisions to invest have previously been developed when investments are irreversible with an uncertain payoff over time and information is assumed fixed. However, in HTA decision uncertainty relates to information (evidence) on the distribution of INMB. This article demonstrates that the option value of delaying decisions to allow collection of further evidence can be estimated as the expected value of sample of information (EVSI). For irreversible decisions, delay and trial (DT) is demonstrated to be preferred to adopt and no trial (AN) when the EVSI exceeds expected costs of information, including expected opportunity costs of not treating patients with the new therapy. For reversible decisions, adopt and trial (AT) becomes a potentially optimal strategy, but costs of reversal are shown to reduce the EVSI of this strategy due to both a lower probability of reversal being optimal and lower payoffs when reversal is optimal. Hence, decision makers are generally shown to face joint research and reimbursement decisions (AN, DT and AT), with the optimal choice dependent on costs of reversal as well as opportunity costs of delay and the distribution of prior INMB.

Suggested Citation

  • Simon Eckermann & Andrew R. Willan, 2008. "The Option Value of Delay in Health Technology Assessment," Medical Decision Making, , vol. 28(3), pages 300-305, May.
  • Handle: RePEc:sae:medema:v:28:y:2008:i:3:p:300-305
    DOI: 10.1177/0272989X07312477
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    References listed on IDEAS

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    1. Jean Tirole, 1988. "The Theory of Industrial Organization," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262200716, December.
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    Cited by:

    1. Simon Walker & Mark Sculpher & Karl Claxton & Steve Palmer, 2012. "Coverage with evidence development, only in research, risk sharing or patient access scheme? A framework for coverage decisions," Working Papers 077cherp, Centre for Health Economics, University of York.
    2. 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.
    3. Penny Breeze & Alan Brennan, 2015. "Valuing Trial Designs from a Pharmaceutical Perspective Using Value‐Based Pricing," Health Economics, John Wiley & Sons, Ltd., vol. 24(11), pages 1468-1482, November.
    4. 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.
    5. 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.
    6. Andrew Willan, 2011. "Sample Size Determination for Cost-Effectiveness Trials," PharmacoEconomics, Springer, vol. 29(11), pages 933-949, November.
    7. Arthur E. Attema & Anna K. Lugnér & Talitha L. Feenstra, 2010. "Investment in antiviral drugs: a real options approach," Health Economics, John Wiley & Sons, Ltd., vol. 19(10), pages 1240-1254, October.
    8. Bognar, Katalin & Romley, John A. & Bae, Jay P. & Murray, James & Chou, Jacquelyn W. & Lakdawalla, Darius N., 2017. "The role of imperfect surrogate endpoint information in drug approval and reimbursement decisions," Journal of Health Economics, Elsevier, vol. 51(C), pages 1-12.
    9. Martin Forster & Paolo Pertile, 2013. "Optimal decision rules for HTA under uncertainty: a wider, dynamic perspective," Health Economics, John Wiley & Sons, Ltd., vol. 22(12), pages 1507-1514, December.
    10. Andrew Willan & Simon Eckermann, 2012. "Value of Information and Pricing New Healthcare Interventions," PharmacoEconomics, Springer, vol. 30(6), pages 447-459, June.
    11. Itamar Megiddo & Dusan Drabik & Tim Bedford & Alec Morton & Justus Wesseler & Ramanan Laxminarayan, 2019. "Investing in antibiotics to alleviate future catastrophic outcomes: What is the value of having an effective antibiotic to mitigate pandemic influenza?," Health Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 556-571, April.
    12. 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.

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