Priors for the degree of 'similarity' between alternative designs can be empirically informed by studies comparing the results of randomised controlled trials and observational data. Comprehensive decision modelling' is likely to become increasingly important in policy making. The BayesWatch criteria described in this report may provide a basis for structured reporting of Bayesian analysis. Bayesian methods can be used to temper overoptimistic conclusions based on meta-analysis of small trials. Modern graphical software can easily handle complex assessments previously analysed using the 'confidence profile' method.
Bayesian methods provide a flexible tool for performance estimation and ranking of institutions.
Two common themes for all participants can immediately be identified. First, the need for an extended set of case studies showing practical aspects of the Bayesian approach, in particular for prediction and handling multiple substudies, in which mathematical details are minimised but details of implementation are provided. Second, the development of standards for the performance and reporting of Bayesian analyses, possibly derived from the BayesWatch checklist. Realistic development of payback models and consideration of 'open' studies. Efficient use of all available evidence by appropriate joint modelling of historical controls, related studies, and so on.