ADVANCING HEALTHCARE INTEROPERABILITY THROUGH CLOUD-BASED DATA ANALYTICS: IMPLEMENTING FHIR SOLUTIONS ON AWS

Abstract

Healthcare interoperability continues to pose significant challenges despite advances in cloud computing and data analytics. This study presents an in-depth case analysis of deploying a Fast Healthcare Interoperability Resources (FHIR)-based regional health information exchange (HIE) utilizing Amazon Web Services (AWS). The implementation leveraged AWS services such as AWS Lambda, Amazon API Gateway, Amazon DynamoDB, and Amazon S3 to create a scalable, secure, and cost-effective interoperability solution for multiple healthcare organizations. Our research demonstrates how AWS's cloud-native approach overcame key barriers to interoperability, including data standardization, security compliance, and legacy system integration. Performance metrics analyzed across 1.2 million patient records revealed a 72% reduction in data exchange latency and a 64% decrease in operational costs compared to traditional on-premises solutions. Additionally, the architecture incorporated AWS HealthLake for FHIR-native storage and for clinical documentation processing. A novel consent management framework using AWS-managed blockchain services ensured an immutable audit trail for patient consent, enhancing compliance and trust. By presenting empirical evidence of performance gains, cost reductions, and improved security compliance, this study contributes to the growing body of research on cloud-based healthcare interoperability.