clinical data Tag

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Healthcare AI and interoperability trends shaping data exchange, privacy and patient care

12 Oct Health Data News Roundup: Healthcare AI Faces Greater Scrutiny; Interoperability Challenges Persist; and HIEs Expand Access to Care Data

Posted at 14:54h in Health Data News Roundup by Matt Langan 0 Comments
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Welcome to the Health Data Weekly News Roundup from IMAT Solutions. This week’s healthcare data news highlights the opportunities and challenges emerging as organizations expand their use of AI and work to improve interoperability. From new approaches to personalized care and more efficient workflows to persistent data exchange barriers, AI oversight and growing privacy concerns, healthcare organizations are balancing innovation with the need for trusted, accessible and actionable data. AI Fuels Growth of Healthcare Data Economy...

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Trusted healthcare data supporting health plan quality measurement

22 Sep Health Plan Quality Is Improving. Trusted Data Helps Make It Measurable.

Posted at 15:11h in Health Payers by Matt Langan 0 Comments
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Top Takeaways • More health plans achieved NCQA’s highest rating in 2026, with 18 plans earning 5 stars compared with 11 last year.• Measuring quality improvement depends on having clinical data that is accurate, complete and usable across increasingly complex healthcare environments.• As quality measurement becomes more digital, health plans need stronger data foundations that can support reporting, analytics and ongoing performance improvement.• NCQA Data Aggregator Validation provides an important framework for establishing confidence in aggregated...

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AI-ready healthcare data supporting better AI, clinical workflows, analytics, and decision making

19 Aug AI Shouldn’t Automate Healthcare’s Data Problems

Posted at 10:07h in Hospitals and Clinics by Matt Langan 0 Comments
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Top Takeaways • AI can accelerate healthcare workflows, but it can also magnify longstanding problems with fragmented data, redundant processes, and inconsistent information. • Healthcare organizations should evaluate the data and workflows behind a process before using AI to automate it.• AI-ready healthcare data must be complete, standardized, normalized, and usable across systems and applications.• A trusted enterprise data foundation can support AI while also improving quality reporting, analytics, population health, and other healthcare priorities.• AI implementation...

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29 Apr Healthcare Business Today: Why MSSP ACOs Must Rethink Data Infrastructure for the APP Era

Posted at 10:53h in Hospitals and Clinics by Matt Langan 0 Comments
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Top Takeaways • APP reporting requires MSSP ACOs to move beyond sampling and manual chart abstraction to support full population digital quality reporting.• Clinical data quality now directly impacts performance, making complete, standardized, and report ready data essential for accurate measurement.• Fragmented data environments across EHRs, coding systems, and provider workflows make full population reporting far more difficult at scale.• Manual chart chasing is no longer sustainable and is being replaced by centralized data curation and...

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