Achieving Advanced Healthcare Transformation through Interoperability and AI
Interoperability - The Blue Owls Solutions
Summary
This article explains how to achieve true interoperability beyond simple data exchange by leveraging the HL7 FHIR standard. By using services like Azure Health Data Services, clinical data is centralized into a unified Lakehouse in FHIR format, building a foundation with high 'data liquidity.'
Details
The solution focuses on building a 'Lakehouse' structure in a cloud environment (Azure) that manages diverse clinical data streams based on the HL7 FHIR standard. This establishes a structured, high-fidelity data foundation where legacy systems can communicate using a common language. The concept of 'data liquidity' is used to aim not just for data storage, but for a state immediately usable for real-time analytics and AI consumption. Furthermore, this framework enables the deployment of 'Agentic AI.' By strictly isolating private LLMs within an Azure tenant (ring-fenced), it allows advanced tasks—such as medical coding assistance or administrative automation—to be executed without exposing sensitive patient data (PII) externally. Security is ensured through 'Security by Design' using Microsoft Purview, which mandates automated data labeling and monitoring of AI actions to guarantee the data's sovereignty and ethical guardrails. This approach addresses complex regulatory requirements faced by public sectors while enabling a transition to a modular, flexible data estate (moving away from monolithic systems).
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