AI is rapidly gaining traction across the healthcare space, driven by growing interest in generative AI, which can create content like text, images, and code. AI adoption, which hovered around 50 percent over the past six years, has surged to 72 percent this year. Within payment integrity, AI can help health plans escape from decades of legacy applications and outsourced high contingency fee vendors that have no incentive to automate/innovate.
Listen to industry experts discuss how to start implementing AI today and to create a balanced approach to AI adoption, one that embraces innovation while carefully managing risks.
Learning Objectives:
- Initiating AI Implementation in Healthcare: Understand the practical steps and strategies for beginning AI implementation within payment integrity, moving away from outdated systems and reliance on vendors with limited incentives for innovation.
- Leveraging AI for Payment Integrity: Learn what payment integrity use cases are ready for AI deployment helping reduce dependency on legacy applications, ultimately improving efficiency and reducing costs for health plans.
- Balancing AI Innovation with Risk Management: Explore how to adopt AI in a way that maximizes innovation while carefully managing potential risks.
Prasanna Ganesan
Brandon Shelton
Brandon Shelton is the Senior Director of the Advanced Analytics Lab at L.A. Care, the country's largest public-option health plan, where he leads teams of Data Scientists and Data Analysts to support the health plan's various enterprise domains with machine learning solutions, program impact assessments, and business intelligence deliverables. The team's contributions towards Payment Integrity savings consistently exceeds $20M per year.