Interoperability Challenges in Electronic Health Record Systems with Emphasis on HL7 FHIR Adoption and Data Standardization
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Abstract
Interoperability of Electronic Health Record (EHR) systems remains a persistent challenge despite widespread digitization and the growing adoption of standardized exchange frameworks. In recent years, HL7 Fast Healthcare Interoperability Resources (FHIR) has emerged as a dominant standard intended to facilitate seamless health information exchange across healthcare organizations. However, real-world implementations continue to exhibit limitations related to data completeness, semantic consistency, and cross-hospital exchange reliability. This study presents a quantitative, data-driven analysis of EHR interoperability challenges by examining FHIR-compliant synthetic datasets representing multiple healthcare organizations. Using a Python-based analytical pipeline, the study evaluates structural interoperability, semantic conformity, and exchange performance through formally defined metrics and statistical analysis. The results reveal significant variability across organizations and resource types, demonstrating that technical standard adoption alone does not ensure meaningful interoperability. The findings provide empirical evidence to inform healthcare organizations, vendors, and policymakers on critical gaps in current interoperability practices and offer insights for improving standardized EHR data exchange.
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