Improving RAF accuracy and audit readiness

This major payer had a mature risk adjustment program: multiple vendors, established first-pass coding logic, and over a million charts processed annually. But under the surface, the organization was finding diminishing returns and potential gaps in their risk adjustment submissions. 

As the industry transitioned into CMS-HCC V28, the payer discovered that their existing workflows exposed a second-pass gap. Valid HCC opportunities were slipping through the cracks between first-pass logic and manual review, creating downstream reimbursement leakage. At the same time, the existing second pass vendors were struggling to identify unsupported codes, also known as “deletes,” to ensure compliance with CMS standards and OIG scrutiny. 

The most urgent signal was a 2% drop in code recapture tied directly to V28 mapping changes, a gap that was quietly eroding the accuracy of their financial forecasts and putting revenue projections at risk. 

Charta’s AI-enhanced approach to retrospective chart review combines LLM-enabled claims matching with deep AI analysis of chart documentation. Charta AI surfaces incremental and unsupported codes to a team of human reviewers, who vet each code against the AI citations and to deliver best-in-class accuracy at unparalleled speed, guaranteeing higher ROI than other coding teams. 

In addition to a 26x ROI, Charta delivered clinician- and site-specific data on validated add and delete codes, so the payer could arm its risk adjustment team with specific, actionable data for improving provider coding.