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