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.