On a simple quickest detection rule for health-care technology assessment
AbstractIn this paper we propose a solution to the Bayesian problem of a decision maker who chooses, while observing trial evidence, an optimal stopping time at which either to invest in a newly developed health care technology or abandon research. We show how optimal stopping boundaries can be computed as a function of the observed cumulative net benefit derived from the new health care technology. At the optimal stopping time, the decision taken is optimal and the decision maker either invest or abandon the technology with consequent health benefits to patients. The model takes into account the cost of decision errors and explicitly models these in the payoff to the heath care system. The implications in terms of opportunity costs of decisions taken at sub-optimal time is discussed and put in the value of information framework. In a case study it is shown that the proposed method, when compared with traditional ones, gives substantial economic gains both in terms of QALYs and reduced trial costs.
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Bibliographic InfoPaper provided by Department of Economics, University of York in its series Discussion Papers with number 14/01.
Date of creation: Jan 2014
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
Fax: (0)1904 323759
Web page: http://www.york.ac.uk/economics/
More information through EDIRC
Optimal stopping; HTA; Bayes; Value of Information;
Find related papers by JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
This paper has been announced in the following NEP Reports:
- NEP-ALL-2014-01-17 (All new papers)
- NEP-HEA-2014-01-17 (Health Economics)
- NEP-ICT-2014-01-17 (Information & Communication Technologies)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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.
- 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.
- Claxton, Karl, 1999. "The irrelevance of inference: a decision-making approach to the stochastic evaluation of health care technologies," Journal of Health Economics, Elsevier, vol. 18(3), pages 341-364, June.
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