AI is reshaping how health systems and payer-aligned organizations improve performance in Medicare Advantage (MA) Stars and HEDIS® measures. This session examines how AI-enabled quality gap closure is moving quality improvement from retrospective reporting to proactive, in-workflow execution.

Drawing on real-world implementations from organizations such as Guidehealth and leading health systems including Emory Healthcare, this  session will highlight proven use cases that delivered measurable gains in MA Stars and HEDIS performance. Attendees will learn how AI voice agents helped improve home blood pressure reporting, driving rapid improvement from 1-Star to 4-Star ratings on blood pressure control measures. The session also explores how blended AI-plus-human engagement models improved medication adherence by converting chronic therapies to 90-day fills for conditions such as hypertension, diabetes and hyperlipidemia.

The session addresses regulatory and operational considerations, key design decisions and the role of clinicians, pharmacists, quality and operations teams in successful deployment. Designed for healthcare executives and population health leaders, this session offers practical insight into how AI-enabled quality programs can improve MA Stars and HEDIS results, reduce administrative burden and improve outcomes and experience for beneficiaries.

Learning Objectives:

• Explain how AI-enabled quality gap closure improves MA Stars and HEDIS® metrics, emphasizing the shift from retrospective reporting to proactive, in-workflow execution.
•  Describe real-world use cases that drive measurable quality improvement, such as AI-supported blood pressure gap closure and hybrid AI-plus-human methods to boost medication adherence through 90-day fills.
• Identify key regulatory, operational and implementation considerations for scaling AI-enabled quality programs while maintaining clinical oversight, auditability and care team alignment.