Opexia
Predictive AI

AI-Powered Claim Denial Prediction Model

Using Machine Learning to proactively flag insurance claim errors prior to submission, significantly increasing revenue capture.

Main Impact

42% Drop in Denials

Time Reduction

30% avg

Accuracy

99.9%

Security

HIPAA Grade

Overview

High claim denial rates cripple clinic cash flow. We developed a custom XGBoost machine learning model that integrates directly into the clinic's billing workflow. By training on 3 years of historical 835 remittance data, the model flags high-risk claims and suggests specific modifier corrections before the claim ever leaves the building.

Key Results

Reduced initial claim denial rate by 42%
Increased captured revenue by 35% within 6 months
Decreased A/R days from 45 to 28
Automated scrub checks for 10,000+ monthly claims

Services Delivered

  • Predictive ML Model Development
  • Historical 835/837 Data Parsing
  • Workflow Integration API
  • Real-time Modifier Suggestions

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