AI Medical Coding Audit Agent

How Cassidy automates this using AI

Step 1: Trigger on encounter ready for billing

The Workflow activates when an encounter reaches the pre-bill queue—pulling structured and unstructured data from the EHR, encoder/grouper outputs, charge capture systems, and current code sets (ICD-10-CM/PCS, CPT, HCPCS).

Step 2: Ingest payer edit libraries and policies

Cassidy pulls NCCI PTP/MUE edits, LCD/NCD rules, payer-specific medical necessity policies, and prior authorization flags from your Knowledge Base to ensure audits reflect current requirements.

Step 3: Run variance analysis against encounter context

The AI analyzes coding against clinical documentation, grouper results, and payer rules—flagging potential DRG changes, CC/MCC capture gaps, bundling conflicts, modifier needs, HCC opportunities, and medical necessity risks with confidence ratings and estimated financial impact.

Step 4: Route flagged encounters with actionable guidance

Cassidy auto-routes variances to coders, CDI specialists, or compliance reviewers through role-based queues, providing encounter-specific recommendations and supporting documentation references to accelerate resolution.

Step 5: Generate compliant provider queries when needed

For documentation insufficiencies, Cassidy drafts provider queries aligned to AHIMA/ACDIS standards—ready for Human-in-the-Loop review before sending to physicians.

Step 6: Confirm clean claim and release

After corrections, Cassidy re-runs payer edit checks to validate the encounter passes all rules, then releases the claim for submission with a complete audit trail for compliance documentation.