Integrating Distributed Health Records Using Cloud Computing Technologies

The fragmentation of patient health data across disparate healthcare institutions, proprietary electronic medical record systems, and unconnected care settings represents a fundamental barrier to coordinated care delivery and optimal clinical decision-making. This research addresses the critical challenge of integrating distributed health records through the systematic application of cloud computing technologies. The study employed a design science research methodology to develop and validate an architectural framework for cloud-based health information integration. The proposed architecture leverages a hybrid cloud model combining a FHIR-standardized data lake for longitudinal patient records with edge computing nodes for low-latency data ingestion from distributed sources. A federated data management approach enables cross-institutional data access without requiring complete data centralization, addressing both technical and governance challenges.

The integration layer implements HL7 FHIR as the primary interoperability standard, with Clinical Document Architecture support for legacy system compatibility. Security is enforced through a zero-trust model incorporating attribute-based access control, end-to-end encryption, and comprehensive audit logging aligned with HIPAA and GDPR requirements. A prototype integrating synthetic data from multiple simulated healthcare sources demonstrated successful record linkage across institutions with 94 percent accuracy, reduced data retrieval latency by 67 percent compared to traditional query methods, and maintained sub-second response times for integrated record access. The research contributes a validated architectural framework and implementation guidance for healthcare organizations seeking to overcome data fragmentation through cloud-based integration, ultimately enabling the comprehensive patient views essential for modern care delivery.