PREDICTING CONFIDENCE SCORE FOR CLAIM TO BE AUTOMATICALLY PROCESSED FOR FRAUD, WASTE AND ABUSE
The model predicts the confidence score for claim to be automatically processed for being Fraud, Waste and Abuse (FWA). The model is trained using claims data with clinical information, vectorized CPT codes and XGBoost modeling technique is used. The resulting model successfully tags 66% of claims known for FWA with 90%+ confidence score.
Input variables : Claims dataset with clinical info (no financial info)
Output Variables : Confidence score on claim being automatically processed for FWA
Metrics to Monitor
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Statistical
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Somers D |
Accuracy |
Precision and Recall |
Confusion Matrix |
F1 Score |
Roc and Auc |
Prevalence |
Detection Rate |
Balanced Accuracy |
Cohen's Kappa |
Concordance |
Gini Coefficent |
KS Statistic |
Youden's J Index
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Business
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Claims Processed |
$ Saved |
FWA Rate |
FWA by CPT |
FWA by Provider
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Infrastructure
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Log Bytes |
Logging/User/IAMPolicy |
Logging/User/VPN |
CPU Utilization |
Memory Usage |
Error Count |
Prediction Count |
Prediction Latencies |
Private Endpoint Prediction Latencies |
Private Endpoint Response Count
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Visit Model :
medictiv.citiustech.com