VERIFIABLE INTEROPERABILITY ACROSS HEALTH DATA STANDARDS: A PROVENANCE-AWARE FRAMEWORK FOR AUDITABILITY

Abstract

Healthcare data interoperability remains fragmented across incompatible standards including HL7 FHIR, CDA, v2 messaging, DICOM, and proprietary formats, creating critical gaps in patient care continuity and clinical decision-making. While technical bridges enable syntactic data exchange, semantic fidelity and transformation auditability remain largely unverified, leading to silent data corruption, information loss, and compliance risks. This research develops a provenance-aware framework that ensures verifiable interoperability across health data standards through comprehensive tracking of data transformations, semantic mappings, and quality assertions. Our framework introduces cryptographic attestation of data provenance, enabling stakeholders to verify transformation integrity and trace data lineage across standard conversions. Through systematic analysis of interoperability failures in healthcare exchanges and synthesis of provenance tracking requirements, we design an architecture that captures complete transformation histories including mapping decisions, data quality assessments, and human interventions. Implementation across three health information exchanges processing 2.4 million patient records demonstrates 99.2% transformation verification coverage, detection of 847 previously unidentified data quality issues, and full compliance auditability for regulatory requirements. The research contributes both theoretical foundations for verifiable health data interoperability and practical implementation patterns enabling trustworthy data exchange across healthcare ecosystems.