What we're learning from 250,000+ claims

Other than eligibility, patient identity has no effect on adjudication. We strip name, DOB, SSN, address, and the full member ID before analysis, keeping the member prefix, patient age, payer details, and the complete clinical/billing content — provider, codes, modifiers, ICD-10, DRG, rev codes. That's everything a payer's adjudication logic actually evaluates, with no PHI leaving your environment.

Four libraries: payer medical & reimbursement policies, government guidelines (NCD & LCD), governing billing rules (CCI/PTP edits, MUE units, timely filing, POS validity, ICD-10 specificity), and custom rules built from your own denial history and written by your team in plain English. Every rule shows pass or fail — no black box.

99% prediction accuracy, and we prove it the only honest way: every 835 remittance is matched back to the original prediction. Accuracy, precision, and recall are on your dashboard, computed from your claims — not a marketing benchmark.

Before go-live we run a 6-month lookback on your submitted claims and payment data. Your custom rule set and payer behavior profile exist on day one — clients typically see denial rates cut by more than half within the first few months.

Yes — intake via API, RPA bot, or report export, so there's no IT project to start. The optional fix bot applies biller-approved corrections directly inside systems like eClinicalWorks and Athena, with every action logged for audit.

The AI validates the denial against policy. If the payer is wrong, ClearClaim generates an evidence-backed appeal automatically — and protects your rule set from learning the payer's mistake. If the denial was valid and we missed it, a new custom rule is written automatically so it never slips through again.