Accounting for Heterogeneity in Relative Treatment Effects for Use in Cost-Effectiveness Models and Value-of-Information Analyses

@inproceedings{Welton2015AccountingFH,
  title={Accounting for Heterogeneity in Relative Treatment Effects for Use in Cost-Effectiveness Models and Value-of-Information Analyses},
  author={Nicky J Welton and Marta Oliveira Soares and Stephen Palmer and Anthony E. Ades and David G Harrison and Manu Shankar-Hari and Kathryn M. Rowan},
  booktitle={Medical decision making : an international journal of the Society for Medical Decision Making},
  year={2015}
}
Cost-effectiveness analysis (CEA) models are routinely used to inform health care policy. Key model inputs include relative effectiveness of competing treatments, typically informed by meta-analysis. Heterogeneity is ubiquitous in meta-analysis, and random effects models are usually used when there is variability in effects across studies. In the absence of observed treatment effect modifiers, various summaries from the random effects distribution (random effects mean, predictive distribution… CONTINUE READING