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Optimal sequential sampling rules for the economic evaluation of health technologies


  • Paolo Pertile
  • Martin Forster
  • Davide La Torre


Referring to the literature on optimal stopping under sequential sampling developed by Chernoff and collaborators, we solve a dynamic model of the economic evaluation of a new health technology, deriving optimal rules for technology adoption, research abandonment and continuation as functions of sample size. The model extends the existing literature to the case where an adoption decision can be deferred and involves a degree of irreversibility. We explore the model's applicability in a case study of the economic evaluation of Drug Eluting Stents (DES), deriving dynamic adoption and abandonment thresholds which are a function of the model's economic parameters. A key result is that referring to a single cost-effectiveness threshold may be sub-optimal.

Suggested Citation

  • Paolo Pertile & Martin Forster & Davide La Torre, 2010. "Optimal sequential sampling rules for the economic evaluation of health technologies," Discussion Papers 10/24, Department of Economics, University of York.
  • Handle: RePEc:yor:yorken:10/24

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    References listed on IDEAS

    1. Jang‐Ting Guo & Alan Krause, 2011. "Optimal Nonlinear Income Taxation with Habit Formation," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 13(3), pages 463-480, June.
    2. Guo, Jang-Ting & Krause, Alan, 2015. "Dynamic income taxation without commitment: Comparing alternative tax systems," Economic Modelling, Elsevier, vol. 47(C), pages 319-326.
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    Cited by:

    1. Daniele Bregantini & Jacco J.J. Thijssen, 2014. "On a simple quickest detection rule for health-care technology assessment," Discussion Papers 14/01, Department of Economics, University of York.
    2. Stephen Chick & Martin Forster & Paolo Pertile, 2017. "A Bayesian decision theoretic model of sequential experimentation with delayed response," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(5), pages 1439-1462, November.
    3. Daniele Bregantini, 2014. "Don’t Stop ’Til You Get Enough: a quickest detection approach to HTA," Discussion Papers 14/04, Department of Economics, University of York.

    More about this item


    Cost-effectiveness analysis; Sequential sampling; Dynamic programming;

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • D92 - Microeconomics - - Micro-Based Behavioral Economics - - - Intertemporal Firm Choice, Investment, Capacity, and Financing
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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