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A little bit of clinical makes the coding go down...

How AI makes population health & revenue analytics actionable

Sponsored by the Jefferson College of Population Health

Population Health programs place two discrete burdens on providers:

  1. Improve care quality, efficiency, and patient satisfaction.

  2. Meet billing, coding, and documentation requirements of the alternative payment models that fund such value-based care.

Health systems frequently employ clinical and revenue cycle analytics to address these two critical issues. Using an illustrative case, this session will explore how a health system (The Villages Health, FL) successfully used AI, including natural language processing (NLP), to unify clinical and financial analytics on a common platform.

The result: increased revenue, improved quality metrics, and better data for physicians.


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