Using supply-demand interactions to estimate effects of population health interventions
Evaluations of natural experiments in population health studies typically construct and compare exposed and unexposed populations on supply or demand dimensions. Populations are often dichotomised on one of these dimensions, even if the underlying dose of exposure is graded. We propose that effects of population health interventions can be estimated more accurately by using both dimensions, using an interaction of a continuous measure of dose at area level and probabilities of exposure at the individual level. This is particularly useful when receipt of treatment by individuals is either unknown or endogenous. This supply-demand (or area-individual) interaction can be integrated into many common natural experiment designs and we propose it as a verification test. Furthermore, this interaction term can be calibrated to be a predicted probability of exposure and then used to ensure the magnitude of the estimated treatment effect is plausible. We describe how to use this approach and demonstrate its application in two examples: the effects of introducing social prescribing link workers on whether people feel supported by local services; and the effects of a welfare reform on the mental health of benefit claimants. In both cases, the interactions approach produces more specific, precise and interpretable estimates of intervention effects.
Speaker
Matt Sutton, Professor of Health Economics, University of Manchester
Matt Sutton is a Professor of Health Economics and joint-lead of the Health Organisation, Policy and Economics (HOPE) research group at the University of Manchester.
Matt's research addresses the financing and organisation of health care, the healthcare workforce and influences on health and health behaviours. It primarily involves the development and application of micro-econometric techniques. 
Matt obtained a first-class honours degree in Economics with Econometrics from the University of Leeds, and an MSc and PhD in Health Economics from the University of York.
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