Created algorithm that process claims data before sending it to the payer and flags each claim for its probability of denial from payer
Solution
- Processed huge data of claims through the intelligent ML algorithm by random forest method and classified the claim into three categories: Fully Paid, Fully Denied, Partially Denied.
- For the category of full denial and partial denial, the appropriate CARC (Claim Adjustment Reason Codes) were predicted to allow the users to understand the reasons for denial.
- Our algorithm can interpret the denial codes and automate the process to correct the claims and submit to the payers
Key Features
- Claim EDI processing
- Detection of denial claims
- Automation of denial correction
- Prediction of denial reasons
- Supervised learning
Key Metrics
20%
Reduction in claim denial
Saved 50k+ dollars by avoiding rework on denied claims
78%
Accuracy level on denial prediction
200+ hours of man effort reduced per month
Technology Stack
