Self-Governing Semantic Intelligence for Member–Provider Ecosystems
Keywords:
Autonomous Health Data Fabric;Semantic Interoperability;Member–Provider Intelligence;Healthcare Knowledge Graphs;Distributed Data Processing;Healthcare Data Governance;Privacy-Preserving Analytics;Secure Health Information Exchange;Intelligent Care Coordination;Federated Healthcare Intelligence.Abstract
Sustainable access to confidential health data remains a central challenge for meaningful cross-organizational interoperability while safeguarding stakeholder privacy. Member–provider intelligence is typically confined to production systems that offer little data control or assurance once processing is outsourced. This paper introduces the security, privacy, and data governance principles underlying an autonomous semantic health fabric — an architecture that encapsulates these concerns while enabling semantic interoperability of data federated across stakeholders for distributed processing.
Healthcare data originate from the multiple sources involved in a patient's care journey and unit-record management, making confidentiality, integrity, and availability the core security properties to preserve. Mitigating risk requires a risk-based approach: achieving compliance with legal provisions, remaining accountable to affected parties, obtaining explicit consent to prevent misuse of personal information, limiting stored and processed data to the minimum necessary, conducting regular audits, and preparing for potential legal action. Traditional approaches — using Electronic Health Records (EHRs) alongside HL7 or FHIR — offer a more business-driven route to cross-organizational semantic interoperability, but they require outsourcing health-data processing to jurisdictions with adequate legal protections, resulting in a loss of data ownership.
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No new datasets were generated or analyzed in this study. The figures are illustrative conceptual examples and do not represent measured data.
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