Healthcare Data Architecture 2025: Designing a Unified, AI-Ready Framework
Healthcare Data Architecture 2025: Designing a Unified, AI-Ready Framework for
A framework was proposed for designing a unified, AI-ready healthcare data architecture.
Summary
Modern data architecture is necessary to effectively utilize the massive amounts of data generated by hospitals and health systems. The goal is to overcome siloed environments and build a reliable information foundation based on standards like FHIR.
Key Players
Details
Hospitals and health systems generate vast amounts of data from sources like EHRs, billing systems, labs, and imaging repositories, but these signals are often trapped in separate, isolated silos. Addressing this challenge, modern data architecture has become a critical strategic concern for leadership. The ideal 2025-ready architecture is composed of several interconnected layers. The 'Data Ingestion and Integration' layer uses interoperability frameworks like FHIR and HL7 to validate diverse formats and convert them into consistent structures via standardized pipelines. The 'Data Storage' layer adopts governed Lakehouse environments, combining traditional warehouses and data lakes to coexist with massive, varied data while protecting sensitive information. Furthermore, the 'Data Processing and Modeling' layer standardizes values using shared clinical terminologies such as SNOMED CT and LOINC, refining identities into traceable relationships. Finally, the 'Analytics and Activation' layer embeds this reliable information into dashboards and automated workflows to support decision-making. This entire framework is anchored by 'Governance, Security, and Compliance,' ensuring adherence to regulations like HIPAA while providing transparent data necessary for AI development.
Technology Note
FHIR（Fast Healthcare Interoperability Resources）は医療データ交換の国際標準。このエントリの関連技術: HL7
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