Cloud-Enabled Enterprise Data Warehouse Architecture for Regional Health Resource Optimization and Insurance Analytics - Krutika Shah (International Journal of Intelligent Systems and Data Science, 2026)
This paper presents an enterprise-level decision support framework leveraging data warehousing and multidimensional modeling to optimize healthcare resource allocation and insurance analytics. Using Microsoft SQL Server and OLAP cubes, the system integrates heterogeneous clinical and administrative data from regional health institutions to support strategic planning. The platform enables policymakers to analyze disease patterns, patient demographics, and resource utilization for informed decisions on hospital placements, specialty distribution, medical equipment procurement, and staff recruitment. While implemented at a regional scale, the architecture demonstrates scalability to enterprise-wide deployments with cloud integration for enhanced data accessibility, real-time analytics, and interoperability with insurance claim systems. The framework supports value-based care models by linking resource allocation to population health outcomes and facilitates insurance risk stratification, premium modeling, and reimbursement optimization through integrated administrative data. This approach provides a foundation for cloud-based enterprise health IT systems that align clinical resource planning with insurance analytics for improved healthcare delivery and financial sustainability.