Cutting Claim Denials by 75% with Predictive AI

The Challenge

A mid-size medical laboratory was facing a growing revenue crisis. Their claim denial rate had climbed to 12%, meaning roughly one in eight claims submitted to insurance was being rejected. Each denied claim triggered a costly manual review, appeal, and resubmission cycle that consumed 15+ hours of staff time every week.

The root causes were varied and difficult to catch manually: incorrect CPT codes for the test ordered, missing prior authorization numbers, mismatched patient demographics, and coverage gaps that weren't verified before the specimen was processed. By the time a denial came back, the opportunity to easily fix the issue had often passed.

The revenue cycle team was stuck in reactive mode — spending the majority of their time managing denials after the fact rather than preventing them. The laboratory's cash flow suffered, and the team was burning out from the volume of manual rework required to recover revenue that should never have been lost.

Our Approach

DxLogic deployed a predictive denial model trained on the laboratory's historical claims data. The model analyzes each claim before submission, scoring it on likelihood of denial based on patterns learned from thousands of previously denied claims. High-risk claims are flagged with specific reasons — missing authorization, coding mismatch, coverage gap — and routed for human review before submission.

Beyond prediction, the system auto-corrects common coding errors that account for a significant portion of denials. When the AI detects a likely CPT code error, incorrect modifier, or missing diagnostic code, it applies the correction automatically. Only edge cases and genuinely ambiguous claims are flagged for human judgment.

DxLogic also built an automated submission pipeline that handles the full claims lifecycle — from initial submission through follow-up and appeal when necessary. A denial analysis dashboard gives the revenue cycle team real-time visibility into denial patterns, payer behavior, and emerging issues before they become systemic problems.

The Results

The denial rate dropped from 12% to 3% — a 75% reduction. With 80% of claims now fully automated end-to-end, the revenue cycle team was freed from 15 hours of weekly denial management work. Claims processing speed increased 4x, meaning faster payments and healthier cash flow. The denial analysis dashboard continues to identify emerging patterns, allowing the team to proactively address issues before they impact revenue.