Leveraging Predictive Analytics to Reduce Underpayment Variance

Small underpayments caused a 6–8% revenue variance across 50,000+ claims annually.
Manual reviews were slow and reactive, missing hidden revenue gaps.
Practolytics implemented AI-driven predictive analytics to flag underpayment risks early.
The system integrated EHR, payer contracts, and historical claim data for real-time alerts.
In 6 months, variance dropped from 8% to 3%, recovering $180,000 and improving efficiency by 75%.
Predictive analytics shifted the clinic from reactive billing fixes to proactive revenue protection.

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Small underpayments caused a 6–8% revenue variance across 50,000+ claims annually.
Manual reviews were slow and reactive, missing hidden revenue gaps.
Practolytics implemented AI-driven predictive analytics to flag underpayment risks early.
The system integrated EHR, payer contracts, and historical claim data for real-time alerts.
In 6 months, variance dropped from 8% to 3%, recovering $180,000 and improving efficiency by 75%.
Predictive analytics shifted the clinic from reactive billing fixes to proactive revenue protection.