FHIR-Powered Intelligence: Cloud and AI for Next-Gen Healthcare
Abstract
Healthcare data has long been locked in silos—fragmented across electronic health records, registries, laboratories, and insurance systems. This fragmentation slows patient care, complicates compliance, and prevents the timely use of analytics. In the U.S., the adoption of FHIR (Fast Healthcare Interoperability Resources) combined with cloud-native data architectures has begun to transform this reality, reducing onboarding time for new data sources, enabling real-time dashboards, and powering AI-ready datasets.
Drawing from my experience leading end-to-end healthcare data platforms, this paper presents an architectural approach to unifying disparate healthcare datasets into a FHIR-native clinical data repository deployed on Google Cloud Platform. I illustrate implementation through concrete use cases—preventive screening, immunization compliance, and AI enablement—and share results that demonstrate reduced latency, compliance-by-design, and improved clinical impact.
The analysis extends beyond the U.S. by examining India’s digital health journey, where national initiatives like the Ayushman Bharat Digital Mission (ABDM) and National Health Claim Exchange (NHCX) are embedding FHIR at the core of a digital public good. By comparing U.S. and Indian contexts, I highlight both challenges and opportunities for scaling interoperability, compliance, and intelligence globally. The paper concludes by looking ahead to future directions—multimodal integration, federated learning, and cross-border health data exchange—positioning FHIR as the foundation for a new era of healthcare intelligence.
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Copyright (c) 2025 Somnath Mahale (Author)
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