🏥 Introduction In Medicare Advantage (MA), accurate risk adjustment via Hierarchical Condition Category (HCC) coding is crucial for proper reimbursement. Errors or omissions in HCC coding result in lower Risk Adjustment Factor (RAF) scores, leading to substantial underpayment and reduced care resources. A payer-provider organization based in the Western U.S. deployed a machine learning (ML) and natural language processing (NLP) solution to enhance HCC coding accuracy. This initiative led to a 7% increase in RAF scores and a $5 million annual increase in capitation payments — achieved without changes in patient volume or demographics. 🧠 The AI Approach Model Capabilities:…