WEBINAR | AI-powered Risk Adjustment at University of Miami Health System

Hospital and health system leaders increasingly view patient population risk adjustment as a strategic health system imperative. However, while they often have a high-level understanding of how measures such as observed-to-expected (O:E) ratios and other risk-adjustment factors work, they may not know how their clinical documentation teams can improve them, or how technologies such as AI can help.

Join Tiara Minor, Director of Clinical Documentation Integrity for University of Miami Health System, for an in-depth look at adjusting risk for mortality, a key factor that impacts quality ratings and rankings, reimbursement, and health system reputation. She provides an overview of key concepts and strategies, and shares a practical, inside view how her team integrated AI-driven tools into CDI workflows to improve mortality O:E performance.

Attendees learn:

• Fundamentals of risk adjustment and Observed-to-Expected ratios, using Mortality as an example.
• How leveraging AI and automation within CDI workflows enables health systems to capture accurate patient acuity, optimize risk-adjusted metrics, and protect margins under value-based care models.
• The benefits to University of Miami Health System of this important work.