Healthcare and life sciences data is fragmented across clinical records, claims, narrative documentation, social services, environmental data, regulatory filings and systems that were not designed to work together. Yet decisions based on this data must withstand audit, fiscal scrutiny, equity review and litigation discovery.
This session presents an architectural pattern for integrating structured, unstructured and semantic data across high-consequence healthcare domains. The session will examine how the Progress Data Platform can combine document storage, triples, ontology management, semantic enrichment, governed business rules and workflow to support cohort identification, signal detection, outcomes attribution and provenance tracing. Worked examples include a drug safety investigation, a diabetes care measure across a Medicare Advantage population and a housing remediation cohort that spans clinical, eligibility, environmental and social services data.
Attendees will learn how an integrated data foundation can support both analytics and AI workloads that must be accurate, consistent and defensible. The session will close with practical guidance for architects deciding where to start, how to prioritize domains and how to design for governance from the beginning.
