Implications of heterogeneity in cost-effectiveness analysis and value of information analysis

Abstract: Cost-effectiveness analyses rely on treatment effect estimates that are typically obtained from a meta-analysis of RCT evidence.  However, heterogeneity is ubiquitous in meta-analysis and this needs to be accounted for in the cost-effectiveness analysis model. Furthermore, Value of Information analyses also need further to consider the relationship between the existing evidence and what is expected to be seen in a new study, and how the new study results will be integrating into an updated cost-effectiveness analysis.  In this talk we describe a range of summaries that can be used, and discuss their implications for cost-effectiveness analysis and value of information analysis. We illustrate the ideas with a meta-analysis of magnesium vs placebo for myocardial infarction. In some cases heterogeneity can be explained (at least partially) by inclusion of study-level covariates. We describe how these covariates can be incorporated in a cost-effectiveness analysis. Often there may be little to choose between competing models in terms of model fit.  We describe a model selection process to identify potential explanatory factors, including the use of expert opinion, to help choose between competing models. We illustrate the approach with an example of a health technology assessment of intravenous immunoglobulin (IVIG) for the management of adult patients with severe sepsis and septic shock in an intensive care setting.