OpenEvidence has introduced "Coding Intelligence," a new feature designed to automate the complex task of medical billing and clinical documentation. Embedded within the company's existing clinical assistant, the tool analyzes full transcripts of doctor-patient interactions to suggest specific billing codes. By reasoning through the nuances of a medical visit, it generates recommendations for Current Procedural Terminology (CPT) and ICD-10 diagnoses, while providing written rationales for medical decision-making directly in the patient note.

The system addresses a major pain point in healthcare: the administrative burden of navigating tens of thousands of potential billing codes. Unlike older solutions that rely on simple keyword mapping, this AI-driven approach evaluates the entire context of the encounter—including ordered labs and treatments—to ensure accuracy. It even handles sophisticated evaluation and management (E/M) level recommendations, which determine the complexity and billing tier of a visit based on either the time spent or the medical risk involved.

To maximize reimbursement and ensure compliance, the platform incorporates Medicare’s Multiple Procedure Payment Reduction policies and Correct Coding Initiative (CCI) rules. By validating code combinations before they are submitted, the system prevents common errors that lead to claim denials. This shift from manual or outsourced coding to real-time AI automation allows physicians to focus more on patient care while reducing the risk of lost revenue from missed procedure codes.

OpenEvidence has introduced "Coding Intelligence," a new feature designed to automate the complex task of medical billing and clinical documentation. Embedded within the company's existing clinical assistant, the tool analyzes full transcripts of doctor-patient interactions to suggest specific billing codes. By reasoning through the nuances of a medical visit, it generates recommendations for Current Procedural Terminology (CPT) and ICD-10 diagnoses, while providing written rationales for medical decision-making directly in the patient note.

The system addresses a major pain point in healthcare: the administrative burden of navigating tens of thousands of potential billing codes. Unlike older solutions that rely on simple keyword mapping, this AI-driven approach evaluates the entire context of the encounter—including ordered labs and treatments—to ensure accuracy. It even handles sophisticated evaluation and management (E/M) level recommendations, which determine the complexity and billing tier of a visit based on either the time spent or the medical risk involved.

To maximize reimbursement and ensure compliance, the platform incorporates Medicare’s Multiple Procedure Payment Reduction policies and Correct Coding Initiative (CCI) rules. By validating code combinations before they are submitted, the system prevents common errors that lead to claim denials. This shift from manual or outsourced coding to real-time AI automation allows physicians to focus more on patient care while reducing the risk of lost revenue from missed procedure codes.