Abstract

Medicaid Healthcare provisions and ecosystem involve a complex network with involvement of federal and state support programs. Healthcare organizations, service providers, and technology support entities oversee the processes of Medicaid systems. The complexities are further magnified by the involvement of huge volumes of data from disparate sources to support analytics, detecting fraudulent claims, and developing operational reports complying with regulatory guidelines. Traditional data handling approaches introduce silos due to scalability limitations and lower adaptability. Metadata is an innovative technology supporting systems involved with managing huge volumes of data occurring from various sources. The paper proposes a metadata-motivated framework developed for the automation of data profiling, analytics, and integration across wider Medicaid systems. This metadata has huge operational value. The framework streamlines data governance and expedites analytics processes with maximum traceability across disparate data sources. Using real-time case studies and insights about emerging technologies, the paper outlines an architecture framed with resilience, modularity, and scalability to manage complications in handling public health data information with Medicaid systems.