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Bayesian approaches to the value of information: implications for the regulation of new pharmaceuticals
Author(s) -
Claxton Karl
Publication year - 1999
Publication title -
health economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.55
H-Index - 109
eISSN - 1099-1050
pISSN - 1057-9230
DOI - 10.1002/(sici)1099-1050(199905)8:3<269::aid-hec425>3.0.co;2-d
Subject(s) - bayesian probability , value (mathematics) , value of information , economics , sample (material) , risk analysis (engineering) , management science , public economics , computer science , microeconomics , business , mathematical economics , artificial intelligence , chemistry , chromatography , machine learning
The current regulation of new pharmaceuticals is inefficient because it demands arbitrary amounts of information, the type of information demanded is not relevant to decision‐makers and the same standards of evidence are applied across different technologies. Bayesian decision theory and an analysis of the value of both perfect and sample information is used to consider the efficient regulation of new pharmaceuticals. This type of analysis can be used to decide whether the evidence in an economic study provides ‘sufficient substantiation’ for an economic claim, and assesses whether evidence can be regarded as ‘competent and reliable’. Copyright © 1999 John Wiley & Sons, Ltd.