Medicare Billing Integrity Detection System

Detecting Systematic Medicare Billing Manipulation Through Advanced Analytics

$31.70B
Improper Payments FY2024
7.66% rate
54M
Part D Beneficiaries
Affected population
101
High-Risk Hospitals
3.5% of 2,911 examined
94.3%
Model Accuracy
Detection performance
42,708
Excess MCC Cases
Annually detected
$213.5M
Identified in Sample
101 hospitals
Data Completeness
99.3%
Cross-Validation
91.3%
False Positive Rate
<10%
Processing Time
<24 hrs
Geographic Distribution of Identified Facilities
Financial Impact Projections
Implementation Roadmap Financial Impact
Model Comparison Results
Implementation Roadmap
Phase Timeline Scope Financial Impact Status
Phase I: Pilot Years 1-2 20-30 hospitals $40M-$60M annually Planning
Phase II: Regional Years 3-5 300-1,500 hospitals $100M-$180M by Year 5 Projected
Phase III: National Years 6+ Broader coverage $200M-$600M annually Future
High-Risk Billing Patterns & Indicators
Metric Value Severity
Major Complications Rate 20.1 percentage points above peers High
Pattern Persistence Score 0.84 High
Confidence Interval $198.3M-$228.7M (95% CI) Validated
Statistical Significance p < 0.001 Strong
Financial Impact Scenarios
Scenario Analytical Basis Projected Impact Progress
Conservative (Top 20) Highest risk in sample $45.8M
Moderate (Top 50) Extended sample $89.3M
Comprehensive (All 101) Full identified set $229M annually
Ten-Year Potential Cumulative projection $2B-$4B
Key Analysis Statistics
Data Analysis
27.5 million Medicare discharges analyzed (2019-2023)
Facilities Examined
2,911 facilities comprehensively evaluated
Validation Method
Bootstrap Resampling (n=1,000) with 5-fold Cross-Validation
Federal Context
324 defendants in National Health Care Fraud Takedown ($14.6B schemes)
GAO Impact
$675B financial benefits from addressing high-risk areas over 17 years