Alaffia Health

Machine learning models automatically scan submitted claims against historical patterns and payer rules to identify underpayments, billing errors, and payment discrepancies without manual auditor review. Detects subtle anomalies that human auditors typically miss through pattern recognition across large claim volumes.

Calculates and quantifies total revenue loss across claims, denials, and billing errors, providing financial impact metrics and recovery potential. Translates detected anomalies into dollar amounts to prioritize recovery efforts and demonstrate ROI.

Analyzes denial trends across payers, claim types, and diagnosis codes to identify root causes of payment rejections. Surfaces systematic issues like missing modifiers, coding errors, or payer-specific requirements that drive recurring denials.

Continuously matches incoming payments and remittance advice against submitted claims to identify discrepancies in real-time. Flags underpayments, missing payments, and posting errors immediately rather than waiting for manual monthly reconciliation.

Ranks identified underpayments and billing errors by recovery potential, effort required, and likelihood of successful appeal. Helps teams focus recovery efforts on high-impact cases rather than pursuing every discrepancy equally.

Identifies common billing errors such as incorrect modifiers, missing required fields, coding mistakes, and claim submission issues. Catches errors before claims are submitted or flags them after rejection to prevent revenue loss.

Compares payment performance metrics across payers including payment rates, denial rates, average payment times, and underpayment frequency. Identifies underperforming payers and contract renegotiation opportunities.

Delivers actionable alerts about identified payment discrepancies directly into existing revenue cycle workflows without requiring system changes or disrupting established processes. Integrates findings into teams' daily work rather than creating separate tools.

Provides clear, transparent reporting on financial returns from payment integrity efforts including recovery amounts, cost savings, and ROI metrics. Uses straightforward pricing model focused on value delivered rather than hidden per-transaction fees.