title: Use of implicit and explicit bayesian methods in health technology assessment.
abstract: OBJECTIVE
  The aim of this study was to examine the use of implicit and explicit Bayesian methods in health technology assessments and to identify whether this has changed over time.
  
  
  METHODS
  A review of all health technology assessment (HTA) reports of secondary research published by the UK National Institute of Health Research (NIHR) between 1997 and 2011. Data were extracted on the use and implementation of Bayesian methods, whether defined as such by the original authors (i.e., explicit) or not (i.e., implicit).
  
  
  RESULTS
  A total of 155 of 375 (41 percent) NIHR HTA reports, identified as relevant to this review, contained a Bayesian analysis. Of these, 128 (83 percent) contained an implicit Bayesian analysis, 3 (2 percent) an explicit Bayesian analysis and 24 (15 percent) both implicit and explicit Bayesian analyses. Of the twenty-seven reports that explicitly used Bayes theorem, only six included prior information in the form of (informative) prior distributions. Over time, the percentage of HTA reports that used Bayesian (implicit and/or explicit) methods increased from 0 percent in 1997 to nearly 80 percent in 2011.
  
  
  CONCLUSIONS
  This review has shown that there has been an increase in the use of Bayesian methods in HTA, which is likely to be a result of the increase in freely available resources to implement the approach. Areas where Bayesian methods have the potential to advance healthcare evaluations in the future are considered in the discussion.
authors.affiliation: Department of Health Sciences, University of Leicester, Leicester, UK.
authors.forename: Nicola J
authors.initials: NJ
authors.lastname: Cooper
authors.forename: David
authors.initials: D
authors.lastname: Spiegelhalter
authors.forename: Sylwia
authors.initials: S
authors.lastname: Bujkiewicz
authors.forename: Pascale
authors.initials: P
authors.lastname: Dequen
authors.forename: Alex J
authors.initials: AJ
authors.lastname: Sutton
mesh_terms: D001499:Bayes Theorem; D013673:Technology Assessment, Biomedical / Q000379:methods*; D006113:United Kingdom