The economics of targeting systemic drivers of mental health using dynamic simulation modelling

Abstract

The objective of this PhD research project was to use system dynamics modelling (SDM) to conduct economic evaluation of mental health interventions through the application of the approach to three case studies. A literature review conducted for this thesis did not find any studies that used a SDM approach for economic evaluation of mental health interventions.

Modelling Study 1 was a cost-utility analysis of eight interventions for youth mental health. It found that Technology-enabled integrated care, Family education, an Online parenting programme and Multi-cultural informed care were cost effective. Methodological insights included the identification of synergistic effects, identification of emergent outcomes in the form of unintended consequences, and the influence of mental health service capacity on the cost effectiveness of some interventions. Modelling Study 2 estimated the health benefits and economic value of improving the social determinants of mental health in the Brisbane South region. Even modest improvements in determinants resulted in material increases in health outcomes and reduction in costs. Modelling Study 3 used constrained optimisation analysis with a SDM framework to systematically test the cost effectiveness of seven scenarios varying existing mental health services capacity growth, new interventions targeted at youths, and budget constraints on the amount of investment funds available for new interventions. The analysis demonstrated there is health and economic value in expanding existing services and implementing new interventions concurrently to capitalise on synergistic effects; the combination of interventions that is most cost effective can be identified using systematic methods in response to changes in the budget constraint; and there are health and economic consequences to attenuated levels of investment in new interventions.