Denial Resubmission Classification
Challenges
- The provider faces roughly 6% insurance reimbursement denials annually, creating revenue leakage, manual operational load, and delays in cash collection.
- Resubmission delays cause time limits to expire, and classifying a denial between Internal Complaint and Correction is time-consuming.
- There is limited visibility on which claims are worth prioritizing, and a high workload for supervisors and officers produces inconsistent outcomes.
Approach
An AI-driven recommendation engine classifies denied claims and prioritizes them by expected remittance outcome, guiding the team through the optimal resubmission strategy.
It runs on three models: a router that decides how a claim should be handled, a predictor of expected recovery, and a payment predictor at activity level.
Key features
- Resubmission Type Router — Internal Complaint, Correction, or Not for Resubmission
- Resubmission Success Predictor — expected recovery ratio at claim level
- Activity Payment Predictor — payment probability score per activity
- Claims prioritized by expected remittance outcome
Impact
12–18%
Net denial rate improvement among claims with a relevant denial reason
60–70%
Productivity gain, measured against the annual cost of labor
9–10%
Working capital reduction, from the average annual denial-rate improvement