MedicalCoding AI, Right Codes, Fewer Denials

Coding a visit by hand takes five to ten minutes. Get it wrong and the claim comes back. This does the first pass and flags the problems while you can still fix them.

The problem

• Coding takes five to ten minutes a visit, and the backlog only grows
• Between 5 and 15 claims in every 100 get denied, usually over something small and fixable
• Insurer rules keep changing and nobody can hold them all in their head
• Chasing an appeal afterwards is slow, manual work

How it works

It reads the note and suggests the codes, with a short reason for each. Your coder confirms or changes them.

More usefully, it tells you what the note is missing. Things like which side of the body, or how severe it was. Small gaps that get claims denied. You can ask the doctor to add a line before the claim goes anywhere.

It also scores each claim on how likely it is to bounce. High-risk ones get a second look. When something does get denied, the reason feeds back in and the suggestions get better.

A person confirms every code. The AI never submits anything by itself.

What it does for a clinic

Nancy runs billing for a twenty-doctor group. Her coders were doing 80 visits a day each, with 8% getting denied.

Coding a visit went from eight minutes to two and a half. The tool kept flagging things like "no mention of which side" so coders could ask before sending. Denials fell to 5.5%.

She now runs a report of every suggested code with a link to the note behind it, which keeps the compliance team happy. Same team, 40% more work done.

Where it fits

• Billing companies: high volume, coder reviews instead of coding from scratch
• Practices: catch what the note is missing before the claim goes out
• Billing services: score the risky claims and check those properly

Built with: Claude, and connections into record and billing systems.