A chain of primary- and urgent-care clinics in North and South Carolina called Med First has reported that using artificial-intelligence tools for medical coding boosted revenue by about 6 % for the same visits. Historically, the doctors at Med First coded their own visits, but beginning around June, the clinics began using an AI system in parallel with standard human coding. The additional funds from enhanced coding accuracy have helped fund the chain’s expansion plans.
Because of this revenue lift, Med First is working to grow from its existing 27 locations to around 40, using the gains to stay open longer, add services, and support care in smaller communities. The article interprets this as early proof that AI-driven administrative workflows — beyond direct clinical diagnostics — can have tangible business and operational impacts for health-care providers.
However, this trend also raises broader questions about workflow changes, the role of human coders, compliance and eventual oversight. As AI takes over more repetitive administrative tasks (such as translating clinical notes into billing codes), the responsibilities for audit, exception handling and ensuring fairness arguably shift. The article suggests that while revenue gains are evident, the system must ensure accuracy, regulatory compliance and integration with existing workflows.
In short, the case of Med First illustrates how AI in medical coding is moving from pilot to production — not only enhancing efficiency for providers but influencing strategic decisions such as expansion and service delivery. But it also signals that with such gains come increased complexity in governance, human-machine collaboration and oversight of AI systems in health care.
