Dynamic analysis of public health insurance programmes

Abstract

Effectiveness and continuity of public health insurance systems are facing signif icant threats from structural and demographic challenges such as principle-agent prob lems and population aging. In this thesis, we construct a multi-sector broad- boundary dynamic simulation model: i) to explore the underlying causal structure surrounding public health insurance systems, and ii) to analyze the operational causality that leads to the development of structural problems for single-payer health insurance models that is financed by employee contributions. The model is simulated under different parameter configurations to analyze the system behavior under different scenarios. We show that the austerity periods carry the danger of overlooking the critical essential demand which would leave collateral damage on population health, lasting long after the first reduction in coverages. Several policy options such as public revenue injections and labor immigration policies are tested to preserve the programme benefits in the long run. We find that greater magnitude interventions generally perform better even with low frequency when the early action is taken. We also show that the effectiveness of some policies are dependent on the scenario conditions. Although highly related, the population health and public programme benefits are found not to share the same exact dynamics and eventual fate. Consequently, the stabilization of programme vari ables does not necessarily mean a better population health outcome for all cases. As a further research avenue to this study, a multi-payer sector can be added to the model in order to conduct a comparative simulation analysis on the health systems performance of single-payer, multi-payer and hybrid insurance models.