Cross-Agency Interoperability Models: Federated Data Systems That Unify Rehabilitation, Medicaid, and Workforce Programs - Jeet Kocha, (Utilitas Mathematica, 2025)
Fragmented data ecosystems across public health, vocational rehabilitation, and workforce systems hinder the delivery of coordinated care and equitable services to vulnerable populations. This study presents a research-based model for cross-agency interoperability through federated data systems that unify the Department of Rehabilitation (DOR), Medicaid agencies, and Workforce Innovation and Opportunity Act (WIOA)-funded programs. Drawing from federal guidelines, technical architectures, and an analysis of over 150 agency data workflows, this research outlines the structural and technological requirements for secure, policy-compliant data sharing without consolidating databases. The proposed model employs a federated architecture where agencies retain data ownership while enabling real-time querying, validation, and service coordination through interoperable APIs, identity frameworks, and policy engines Key mechanisms include privacy-preserving record linkage (PPRL), standards-based vocabularies (e.g., HL7 FHIR, NIEM), and adaptive access control protocols aligned with HIPAA, FERPA, and WIOA Title I/IV mandates. Findings demonstrate that federated models reduce duplicative service intake by 47%, improve benefit eligibility adjudication by 38%, and enhance program accountability through auditable cross-agency metrics. The study contributes a reference implementation model with defined governance roles, consent management structures, and integration touchpoints. This work offers a scalable pathway for states seeking to modernize public service delivery while preserving jurisdictional autonomy, legal compliance, and citizen trust in digital government infrastructure.