Optimal sequential sampling rules for the economic evaluation of health technologies
AbstractReferring 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.
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Bibliographic InfoPaper provided by Department of Economics, University of York in its series Discussion Papers with number 10/24.
Date of creation: Dec 2010
Date of revision:
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Postal: Department of Economics and Related Studies, University of York, York, YO10 5DD, United Kingdom
Phone: (0)1904 323776
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Web page: http://www.york.ac.uk/economics/
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Cost-effectiveness analysis; Sequential sampling; Dynamic programming;
Find related papers by JEL classification:
- I10 - Health, Education, and Welfare - - Health - - - General
- D92 - Microeconomics - - Intertemporal Choice - - - 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
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-12-11 (All new papers)
- NEP-DGE-2010-12-11 (Dynamic General Equilibrium)
- NEP-HEA-2010-12-11 (Health Economics)
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- Daniele Bregantini, 2014. "Donâ€™t Stop â€™Til You Get Enough: a quickest detection approach to HTA," Discussion Papers 14/04, Department of Economics, University of York.
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