title: Bayesian approaches to the value of information: implications for the regulation of new pharmaceuticals.
abstract: 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'.
authors.affiliation: Harkness Fellow of the Commonwealth Fund of New York, Harvard Center for Risk Analysis, USA.
authors.forename: K
authors.initials: K
authors.lastname: Claxton
mesh_terms: D001499:Bayes Theorem; D003362:Cost-Benefit Analysis; D003662:Decision Theory; D017277:Drug Approval / Q000191:economics* / Q000706:statistics & numerical data*; D017598:Efficiency, Organizational; D006801:Humans; D014481:United States; D014486:United States Food and Drug Administration