A loop with a human somewhere in it
Many tools describe themselves as human-in-the-loop because a person can, technically, look at what the AI did. Often that look happens after the claim has already gone out.
That's not a loop. That's a report.
Put the person at the decision
In billing, there are a few moments that matter:
- When a code becomes final
- When a claim is sent to a payer
- When a payment is posted
- When a denied claim is changed and resent
A meaningful human-in-the-loop design puts a person at each of those moments, every time, with no setting to switch it off.
Make the AI visible
The other half of the idea is visibility. If AI suggested a code and the coder rejected it, that's useful information. If the denial agent's proposals are accepted 90% of the time for one payer and 20% for another, a supervisor should know.
MEDBIX keeps an activity feed of every AI proposal and every human decision about it. It's the simplest way we know to build trust in a tool: let people check its work.
Rules first, models second
Finally, the boring part: deterministic rules should do the checking they're good at. A missing authorization number doesn't need a model to spot it. Save the AI for the work that actually needs reading and judgement, and keep the final call with your team.
#ai#hitl#compliance
