AI medical coding drives rising healthcare costs and automation

The deployment of artificial intelligence in medical coding is driving significant financial shifts within the U.S. healthcare system. An analysis by the Blue Cross Blue Shield Association estimates that AI-assisted coding added approximately $942 million to health plan costs between 2023 and 2025. This increase is largely attributed to AI identifying secondary diagnoses that qualify patients for higher reimbursement tiers, often without changing the actual clinical care provided.

Luke Chalker of the Blue Cross Blue Shield Association noted that roughly 70%, or $653 million, of this identified billing was tied to additional diagnoses that did not result in a change in care. While insurers suggest these tools accelerate billing incentives, the American Hospital Association maintains that the technology captures the true clinical complexity of patients.

In the same sector, AKASA has launched an autonomous generative AI platform designed to automate inpatient medical coding and clinical documentation integrity. The technology aims to address operational bottlenecks by coding inpatient encounters in under 90 seconds, compared to the 30 to 60 minutes typically required by human coders. AKASA's models currently process encounters representing approximately 1 in every 10 U.S. inpatient hospital discharges.