Pre-submission prediction

Know which claims will deny before you submit them.

Recovery gets your money back. Prevention stops it from leaving. Prexisio trains a prediction engine on thirteen months of your adjudicated claims, then evaluates every pre-submission batch against it and hands your billing team a prioritized work order.

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How prediction works here

Trained on your claims. Not on averages.

Generic denial rules describe an average practice that does not exist. Prexisio builds its intelligence from your own adjudicated history: your payers, your procedures, your providers, your denial patterns. The engine learns how your specific payer behaves on your specific codes, and how that behavior has been drifting.

Everything is predicted: how likely the denial, for what reason, and what it costs you if it happens. Where a payer has been paying below its pattern or below your contract, that surfaces too.

Some denials never need a model

Certain denials are caught before the model even runs. A claim past the timely filing window. A deleted diagnosis code. A procedure that does not match its authorization.

These are blocked with the exact reason, because sending them is donating the claim to the payer.

What your team receives

A work order, not a dashboard.

No software for your team to learn. No dashboard to check.

For the billing team

A prioritized list: claims to hold, claims to fix, claims to send with caution, and claims that are clean. Each flagged claim comes with the specific issue and the specific fix.

When the fix is correspondence

The authorization request or appeal letter arrives already drafted, waiting for a person to review and approve it. Nothing is sent automatically.

For leadership

A pattern report naming the payers, procedures, and contract lines behind the losses, with every number carrying its stated basis and every benchmark carrying its source.

Honest expectations

What prevention needs to work.

Prediction quality depends on history. Thirteen months of adjudicated claims is the foundation. Practices with cleaner, longer history get sharper predictions, and the engine tells you its confidence rather than pretending certainty it does not have.

Prevention is also where recovery clients naturally end up: every claim we recover teaches the engine more about your payers, which makes prevention better. Most clients start with the pile. This page is why they stay.