White Rose University Consortium logo
University of Leeds logo University of Sheffield logo York University logo

Bayesian approaches to technology assessment and decision making

Luce, B.R., Shih, Y.T. and Claxton, K. (orcid.org/0000-0003-2002-4694) (2001) Bayesian approaches to technology assessment and decision making. International Journal of Technology Assessment in Health Care. pp. 1-5. ISSN 0266-4623

Text (claxtonk2.pdf)

Download (25Kb)


Until the mid-1980s, most economic analyses of healthcare technologies were based on decision theory and used decision-analytic models. The goal was to synthesize all relevant clinical and economic evidence for the purpose of assisting decision makers to efficiently allocate society's scarce resources. This was true of virtually all the early cost-effectiveness evaluations sponsored and/or published by the U.S. Congressional Office of Technology Assessment (OTA) (15), Centers of Disease Control and Prevention (CDC), the National Cancer Institute, other elements of the U.S. Public Health Service, and of healthcare technology assessors in Europe and elsewhere around the world. Methodologists routinely espoused, or at minimum assumed, that these economic analyses were based on decision theory (8;24;25). Since decision theory is rooted in—in fact, an informal application of—Bayesian statistical theory, these analysts were conducting studies to assist healthcare decision making by appealing to a Bayesian rather than a classical, or frequentist, inference approach. But their efforts were not so labeled. Oddly, the statistical training of these decision analysts was invariably classical, not Bayesian. Many were not—and still are not—conversant with Bayesian statistical approaches.

Item Type: Article
Copyright, Publisher and Additional Information: Copyright © 2001 Cambridge University Press.
Institution: The University of York
Academic Units: The University of York > Economics and Related Studies (York)
Depositing User: Sherpa Assistant
Date Deposited: 20 Jan 2006
Last Modified: 15 May 2016 03:28
Published Version: http://dx.doi.org/10.1017/S0266462301104010
Status: Published
Refereed: Yes
URI: http://eprints.whiterose.ac.uk/id/eprint/947

Actions (repository staff only: login required)