Background and Need

Medical coding converts clinical notes, diagnoses and procedures into standardized alphanumeric codes for billing, reporting and public‑health analysis. In the United States alone, the ICD‑10‑CM system contains 70,000 diagnosis codes, and errors are common, costly and often invisible. Traditional AI approaches treat coding as a classification problem, predicting the most likely code based on historic data, which can struggle as coding guidelines evolve.

Corti’s Approach

Corti developed Symphony for Medical Coding using a peer‑reviewed framework called “Code Like Humans,” presented at EMNLP 2025. The research, based on 1.8 million patient encounters, frames coding as a reasoning task. The system deploys four agents in sequence:

• Evidence extractor – isolates conditions in a clinical note.
• Index navigator – searches the ICD alphabetical index for candidate codes.
• Tabular validator – checks candidates against coding guidelines.
• Code reconciler – sequences and validates the final output.

Each step mirrors the decision process of expert human coders, providing auditable links between assigned codes and the supporting clinical evidence.

Performance Claims

Corti asserts that Symphony outperforms AI models from OpenAI, Anthropic, Amazon, Oracle and Microsoft by up to 25% on clinical accuracy benchmarks. In a peer‑reviewed study of Danish patient data, the system identified three times as many suicide attempts as had been officially coded, uncovering cases present in notes and medication records but missed by time‑pressed coders.

Availability and Integration

Symphony is now available via API and through the Corti Console. It supports both the U.S. coding environment (ICD‑10‑CM for diagnoses, ICD‑10‑PCS and CPT for procedures) and European coding environments without local retraining. The system produces auditable outputs, flags ambiguities for human review, and integrates with the Corti Agentic Framework, supporting A2A and MCP standards. Enterprise and sovereign‑cloud deployments are also offered.

Implications for Healthcare

By improving coding accuracy, Symphony aims to enhance the data layer that health systems rely on for monitoring trends, allocating resources and designing interventions. Accurate coding is presented not as a back‑office cost center but as a critical foundation for health‑system decision‑making.

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