clinical data Tag

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

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

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

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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