Advancing Spatiotemporal Modeling of Access to Healthcare – A Methodological Perspective

Abstract

Modelers apply system dynamics (SD) modeling in various fields for different purposes including policy analysis, however, they need to integrate SD with other methodologies to facilitate the inclusion of spatial factors and study their influence on the system’s behavior. We investigate the combination of SD modeling with Geographic Information Systems using healthcare data to facilitate the study of both spatial and systemic factors for more effective policy design. We propose an algorithm for integrating these methodologies and explain one of its applications in the complex health systems—Medicaid beneficiaries’ access to primary care (PC). Our results reveal insights and information that were not available through merely SD modeling; this approach provides the opportunity for policymakers to learn about the influence of spatiotemporal factors on health outcomes in a complex health system, and identify the areas with a high need for PC providers.