Recover Lost Revenue With AI-Powered Underpayment Detection & Recovery

HealOS detects, analyzes, and recovers underpaid claims in real-time using advanced AI trained on payer rules, contract terms, CPT logic, and clinical coding structures. Every payment is validated against expected contract rates, ensuring you never miss a dollar you've earned.

Stop silent revenue leakage. Enforce payer compliance. Recover revenue instantly.

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AI-Powered Underpayment Detection & Recovery for Healthcare

Proven Results with AI Underpayment Detection

HealOS clients consistently recover revenue that traditional workflows miss.

5–8%
Revenue Recovered Annually
AI captures underpayments across all payers, contracts, and CPT codes.
$250,000–$400,000/year
Average Recovery
Typical mid-sized practices recapture hundreds of thousands annually.
95%
Detection Accuracy
AI compares every payment against the correct contract term with exceptional precision.

The Problem. The Impact. The HealOS Solution.

ChallengeImpact on RevenueHealOS Underpayment Detection Solution
Payments that "look paid" but are incorrectSilent revenue leakage that grows unnoticedReal-time reconciliation validates each payment line-by-line
Manual staff reviewing EOBs, ERAs, fee schedulesSlow, error-prone audits; missed variancesAI compares paid vs contracted rates instantly
Underpayments found after appeal window closesPermanent, unrecoverable revenueReal-time alerts ensure timely appeals
Complex payer rules, modifiers, carve-outsHard to identify mismatches manuallyContract-intelligent AI interprets payer terms with precision
No visibility into payer patternsSystematic underpayments go unnoticedMachine learning uncovers payer trends & recurring variances
Staff bandwidth limits full reviewMillions lost annuallyFull automation performs 24/7 reconciliation without human labor

Challenges in Traditional Underpayment Detection

Healthcare teams lose 3–11% of net revenue each year due to underpayments, most of which go completely unnoticed. Manual workflows simply cannot keep up.

1.

Heavy Manual Review

Teams scan contracts, EOBs, spreadsheets, and remits line-by-line, leading to inconsistencies and missed discrepancies.

2.

Hidden Complexity

Underpayments often stem from: Modifier issues, Bundled/unbundled CPT errors, Fee schedule mismatches, Payer carve-outs, Incorrect rate escalators. These are nearly impossible to detect manually.

3.

Late Discovery

Many variances surface after appeal windows close, permanently turning recoverable revenue into write-offs.

4.

Silent Revenue Leakage

Small discrepancies across thousands of monthly claims $4 here, $18 there, quietly add up to millions lost annually.

AI-Powered Underpayment Detection & Recovery Features

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Real-Time Payment Reconciliation

HealOS validates every payment against contracted rates the moment ERAs/EOBs arrive. Detect discrepancies instantly, compare expected vs. actual payments, and trigger alerts before deadlines lapse.

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Line-Item Contract Comparison

AI checks every CPT code, modifier, service line, add-on, bundling rule, and adjustment. Catches underpayments that human reviewers miss. Flags wrong rates, incorrect escalators, and missing add-ons.

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Automated Contract Intelligence

HealOS ingests payer contracts using an LLM trained on fee schedules, carve-outs, bundled payment rules, annual rate escalators, and CPT/HCPCS reimbursement variations. Contracts are digitized into a dynamic rules engine for accurate comparisons.

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Missed Charge & Variance Detection

Automatically identifies missing CPT/HCPCS codes, incorrect bundling/unbundling, misapplied payer policies, and rate table variances.

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Automated Appeal Generation

HealOS drafts payer-specific appeals using contract citations, line-item variance reports, payment history, and clinical justification.

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Evidence Pack Compilation

Each underpayment generates claim details, expected vs paid amounts, rate tables, contract terms, attachments & supporting documents, ready for instant submission.

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Payer Behavior & Trend Analytics

ML identifies repeat underpayment patterns, systematic payer issues, high-risk CPT groups, and negotiation priorities.

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A/R Prioritization by Recovery Value

Claims are ranked by expected recovery amount, likelihood of overturn, timeliness of appeal window, and payer behavior history.

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Zero-Disruption EHR/RCM Integration

Works seamlessly with Epic, Cerner, Athenahealth, NextGen, eClinicalWorks, Allscripts, DrChrono, 150+ RCM platforms.

How HealOS Underpayment Detection Works

End-to-End AI Workflow That Protects Every Dollar of Your Revenue

HealOS uses contract-intelligent AI, real-time reconciliation, and automated appeals to detect, analyze, and recover underpaid claims with unmatched accuracy. Every step is optimized for speed, compliance, and maximum revenue recovery.

1

STEP 1 β€” Contract Ingestion & Rules Intelligence

HealOS imports and interprets all payer contracts, fee schedules, modifiers, carve-outs, and bundled service rules using a healthcare-trained LLM. What the AI does: Digitizes and normalizes complex contract terms, builds a dynamic, payer-specific rules engine, maps CPT/HCPCS codes, modifiers, escalators, and carve-outs, ensures every future payment is checked against the correct rate.

2

STEP 2 β€” ERA/EOB Payment Capture

Incoming ERAs, EOBs, and remittance files are ingested automatically from clearinghouses, billing systems, and EHRs. What the AI does: Captures remits in real time, syncs payments with originating claims, extracts line-level adjudication details.

3

STEP 3 β€” Real-Time Payment Reconciliation

AI compares paid vs. expected reimbursement for every CPT line, modifier, facility rate, and adjustment. What the AI identifies: Incorrect payment rates, missing add-on codes, bundling/unbundling errors, payer escalator mismatches, carve-out variances.

4

STEP 4 β€” Discrepancy Flagging & Variance Scoring

When variance is detected, HealOS instantly flags the claim and assigns it a priority score based on financial impact, payer behavior patterns, appeal window urgency, and likelihood of successful recovery.

5

STEP 5 β€” Automated Evidence Pack Generation

HealOS auto-produces a complete, audit-ready documentation file for each underpayment. Evidence pack includes: Contract term citations, expected vs. paid calculations, historical payment patterns, supporting medical documentation, relevant coding rules.

6

STEP 6 β€” AI-Powered Appeal Generation

LLM-powered drafting creates payer-specific appeals in secondsβ€”precise, compliant, and backed by contract evidence. What the AI generates: Reconsideration requests, appeal letters, supporting attachments, contract-based arguments, payer-specific justifications.

7

STEP 7 β€” Automated Submission & Follow-Up

HealOS submits appeals and tracks each case across payer portals, IVR systems, and RCM queues. Follow-up automation includes: Status checks, portal updates, documentation resubmission, timely reminders for staff on exceptions.

8

STEP 8 β€” Continuous Monitoring & Prevention

HealOS learns from every recovered claim to prevent future underpayments. System improves by: Identifying systematic payer trends, flagging risky modifiers or CPT combinations, detecting patterns that cause underpayments, updating internal rules automatically.

Key Benefits of AI-Powered Underpayment Detection

Recover lost revenue, ensure contract compliance, and optimize financial performance with intelligent underpayment detection and recovery

Financial Benefits

Recover 5-8% of Lost Revenue Annually

Healthcare providers lose 5-8% of total revenue to underpayments, missed charges, and contractual adjustments. AI-powered underpayment detection identifies and recovers this lost revenue automatically, ensuring you capture every dollar you've earned.

Financial Benefits

Average $250,000+ Annual Recovery

Practices that actively challenge underpayments recover an average of $250,000 per year. For a $5 million practice, that translates to up to $400,000 in recovered revenue that would otherwise be lost.

Operational Efficiency

Real-Time Payment Monitoring

Monitor and compare payments against contract terms in real-time as they're received. Instant detection of discrepancies ensures immediate recovery action, preventing revenue leakage before it compounds.

Operational Efficiency

Automated Recovery Workflows

Eliminate manual underpayment review and recovery processes. AI automatically identifies discrepancies, generates evidence packs, and triggers recovery actions based on payer-specific rules, reducing administrative burden.

Healthcare AI Solutions

95% Detection Accuracy

Achieve 95% accuracy in identifying payment discrepancies through AI-powered analysis. Machine learning models compare allowed amounts from contracts and fee schedules against ERA/EOB payments with precision.

Financial Benefits

Contract Compliance Assurance

Ensure payers comply with contract terms and fee schedules. Continuous monitoring identifies systematic underpayment patterns, providing insights for contract renegotiation and payer performance management.

Financial Benefits

Reduce Revenue Leakage

Prevent revenue leakage from underpayments, missed charges, and contractual adjustments. Automated detection and recovery processes ensure you're paid accurately and on time for all services provided.

Operational Efficiency

Faster Recovery Cycles

Accelerate underpayment recovery with automated workflows that prioritize high-value cases. Evidence packs are generated automatically, and appeals are initiated immediately, reducing time-to-recovery significantly.

Healthcare AI Solutions

Comprehensive Payer Analytics

Gain insights into payer performance and underpayment trends. Detailed analytics identify which payers underpay most frequently, enabling strategic contract negotiations and improved revenue capture.

Why Healthcare Teams Choose HealOS

Healthcare-Trained AI

Built specifically for medical billing and payer rules, not generic automation.

End-to-End RCM Integration

Works with your existing claims, EHR, denial management, and payment systems.

Zero-Disruption Setup

Go live in under 30 minutes using plug-and-play workflows.

Enterprise-Grade Accuracy

95%+ detection accuracy and real-time reconciliation outperform manual workflows.

Frequently Asked Questions

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