Don’t Stop ’Til You Get Enough: a quickest detection approach to HTA

Daniele Bregantini

Discussion Papers from Department of Economics, University of York

Abstract: Within the context of the value of information approach we compare static versus quickest detection rules for research design in health care technology assessment (HTA). We show for a research design that the optimal decision rule cannot be correctly predicted at the start of the trial. We make use of the sequential value of information (S-VoI) decision making model for HTA under uncertainty to show that the static value of information approach leads to lower expected benefit and poses costs, both in terms of resources and forgone health gains, on the health care system.

Keywords: Optimal stopping; HTA; Bayes; Value of Information (search for similar items in EconPapers)
JEL-codes: C00 C11 C12 C15 (search for similar items in EconPapers)
Date: 2014-03
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Persistent link: https://EconPapers.repec.org/RePEc:yor:yorken:14/04

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