Why Bayesian analysis hasn't caught on in healthcare decision making

The objective of this paper is to discuss why Bayesian statistics is not us ed more-in healthcare decision making and what might be done to increase th e use of Bayesian methods. First,a case is made for why Bayesian analysis s hould be used more widely. Serious weaknesses of commonly used frequentist methods are discussed and contrasted with advantages of Bayesian methods. N ext, the question of why Bayesian methods are not used more widely is addre ssed, considering both philosophical differences and practical issues. Cont rary to what some might think, the practical issues are more important in t his regard. Finally same steps to encourage increased use of Bayesian metho ds in healthcare decision making are presented and discussed. These ideas a re straightforward but are by no means trivial to implement, largely becaus e it is difficult to fight tradition and make major paradigm shifts quickly . The primary needs are improved Bayesian training at the basic level (whic h means textbooks and other materials as well as training or those who teac h at the basic level), procedures to make Bayesian analysis easier to under stand and use (better software and standard methods for displaying and comm unicating Bayesian outputs will help here), and the education of decision m akers about the advantages of Bayesian methods in important healthcare deci sion-making problems.