Operationalizing Geospatial Intelligence for Proactive Regulatory Compliance and Healthcare System Optimization: A Decision-Support Framework for Public Institutions

Abstract

Public institutions face mounting pressure to enhance regulatory compliance monitoring and optimize healthcare delivery amid resource constraints and expanding service demands. This paper synthesizes studies to propose a comprehensive decision-support framework that operationalizes geospatial intelligence for proactive regulatory compliance and healthcare system optimization. Drawing on theoretical foundations in spatial decision science, complex event processing, and multi-criteria analysis, the framework integrates three core architectural components: real-time geospatial data acquisition and integration layers, spatial analytics and modeling engines, and stakeholder-accessible visualization and decision interfaces. Evidence from environmental monitoring, industrial emissions control, and healthcare facility planning demonstrates that GIS-driven, closed-loop decision-support systems can measurably improve compliance detection rates, inspection efficiency, and operational outcomes. Empirical findings reveal accessibility improvements of up to 24% in healthcare service coverage, reduction of average travel times by 25%, and enhanced detection of spatially constrained regulatory violations through geo-event processing. The framework addresses implementation considerations including interoperability standards, open-source technology integration, stakeholder engagement protocols, and performance metrics for continuous improvement. This synthesis extends prior findings on closed-loop geospatial decision support into healthcare and public-sector contexts, providing actionable guidance for institutions seeking to leverage spatial intelligence for evidence-based policy and operational excellence.