Cleveland Clinic deploys GenAI to speed up the medical coding time and boost accuracy across complex patient cases.
Cleveland Clinic deploys GenAI to cut medical coding time and boost accuracy across complex patient cases. They are working with AKASA to bring GenAI into the mid-revenue cycle. This is the step between care and billing. Medical coding at this stage involves sifting through over 100 clinical documents per patient. Coders must choose the right codes from a library of 140,000 options. This process can take nearly an hour per case, especially for high-acuity patients.
With AKASA’s GenAI tools, coders now get a digital assistant that reads and processes documents in under two seconds each. The tool scans 100+ files in about 90 seconds and understands clinical language beyond surface keywords. This context-awareness helps the AI generate more accurate and complete codes. It also adapts to complex patient profiles. Something crucial at a hospital like Cleveland Clinic.
A second GenAI tool, focused on documentation integrity, is now in pilot. It supports better charting and aligns medical records with coding practices. These tools aim to reduce manual work, eliminate repetitive review tasks, and ensure that coding accurately reflects patient care complexity. This is key to quality scores that now influence hospital performance ratings.
The AI also learns from the clinic’s own documentation style. That lets it manage even the most complicated inpatient cases. Coders still make final decisions, but GenAI handles the heavy lifting. This speeds up billing, reduces administrative costs, and improves data accuracy—benefits that scale across Cleveland Clinic’s nationwide operations.