Medical Research Council
Early Career Fellowship in the Economics of Health
Improving statistical methods to address confounding in the economic evaluation of health interventions
Confounding is a major methodological challenge in health economic evaluations that use non-randomised studies. Currently recommended methods are not directly applicable for complex settings, such as when cost-effectiveness of a continuous or dynamic treatment regime is of interest. The causal inference literature proposes methods to address confounding in these settings. This fellowship aims to critically assess and extend these methods, to deal with the specific challenges of economic evaluation. Examples include the extension of the generalised propensity score method with machine learning, and the use of the synthetic control approach to evaluate health policies.