Abstract
This chapter aims to improve the applicability of the data created by a microsimulation model, not by increasing the complexity of the simulation framework, but by integrating the newly created data within a meso-level, spatial interaction framework. Spatial microsimulation modelling is a means of synthetically creating geographically referenced micro-data. With increases in computational power and increased access to spatially referenced micro-data, spatial microsimulation has been used extensively over the last decade to inform health policy. However, the complex dynamics which underlie health-care markets require both meso- and micro-level tools to formulate appropriate and effective health policies. In particular, there is a need to understand, estimate or predict how meso-level interactions such as access to services are going to impact on individuals and areas. To ensure that these meso-level interactions are accounted for, this chapter incorporates data from a spatial interaction model and spatial microsimulation models to account for the impact on access to GPs on individual’s health. Such an analysis provides policymakers with information on both demand for and supply of health-care services, thus allowing them to shape future service provision and target existing health resources in a more efficient and effective manner.
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Morrissey, K., Clarke, G., O’Donoghue, C. (2012). Linking Static Spatial Microsimulation Modelling to Meso-scale Models: The Relationship Between Access to GP Services and Long-Term Illness. In: Tanton, R., Edwards, K. (eds) Spatial Microsimulation: A Reference Guide for Users. Understanding Population Trends and Processes, vol 6. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4623-7_8
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