Executive Command Center
Real-time fraud detection across $2.14 trillion in annual Medicare and Medicaid expenditures. CY 2025 est., 20,000 providers in sample dataset.
Annual Spending Trend
2018–2024Top 10 States by Spending
SampleRisk Distribution
Geographic Risk Density
Top 10 StatesRecent Alerts
View All →Provider Search
Search and filter 2,000 Medicaid providers (75 real HHS-verified + 1,925 synthetic) by NPI, name, state, specialty, or risk level.
| Provider ↕ | NPI ↕ | State ↕ | Specialty ↕ | Total Billed ↓ | Claims ↕ | Risk ↕ | Flags ↕ |
|---|
Provider Name
Critical OrganizationMonthly Spending Trend
Year-over-Year Comparison
Top HCPCS Codes
| Code | Description | Claims | Total Paid | Cost/Claim | Median | Ratio |
|---|
Peer Benchmarking
vs Specialty PeersBeneficiary Demographics
Affiliations / Network
Fraud Test Results
30 testsRisk Watchlist
Providers flagged by statistical fraud detection tests, sorted by risk severity.
Critical
High
Elevated
Total Flagged
| Provider | State | Specialty | Total Billed | Risk Score | Flags | Affil. Flagged | Flag Details |
|---|
Geographic Intelligence
Interactive map of Medicaid spending and provider risk across all 50 states.
State Explorer
All 50 states + DC. Medicaid spending and provider analysis. Click a state to drill in.
State Name XX
Spending by Year
Top Specialties
Top Providers
| Provider | Specialty | Total Billed | Risk | Flags |
|---|
Top Procedures
| Code | Description | Total Paid | Claims |
|---|
Fraud Analysis
30 statistical tests to identify suspicious billing patterns. Toggle tests to see impact on flag counts.
Procedures
45+ HCPCS codes by total Medicaid spending, grouped by category.
Top 10 HCPCS Codes by Spending
| Code | Category | Description | Total Spending | Total Claims | Avg Cost/Claim | Providers |
|---|
Network Analysis
Provider clusters (3+ affiliated providers) with shared beneficiaries and combined risk profiles.
| Cluster | Members | State | Total Spending | Shared Beneficiaries | Flagged Members | Risk Level |
|---|
Prescribing Data
Prescription patterns, controlled substance rates, and opioid prescribing analysis.
Controlled Substance % by Top Prescribers
Opioid Prescribing Rate by Specialty
| Provider | Specialty | State | Total Rx | Controlled % | Opioid % | Risk |
|---|
Ownership Analysis
Spending and risk distribution by ownership type and entity structure.
Spending by Ownership Type
Risk Distribution by Ownership
Corporate Chain Spotlight
| Provider | Specialty | State | Total Billed | Risk | Flags |
|---|
ROI Calculator
Projected fraud recovery and return on investment for IMX-Ray deployment.
Estimates are illustrative projections based on sample dataset extrapolation to national program figures. Actual recovery depends on investigation capacity, legal outcomes, and program-specific factors. Sources: GAO-25-106335, OIG Semi-Annual Report FY 2025, CMS NHE CY 2025 est.
System Documentation
IMX-Ray™ Fraud Detection Decision Support System. Technical methodology, data governance, and compliance.
System Overview
IMX-Ray™ is a Fraud Detection Decision Support System (FDSS) designed for federal and state agencies responsible for Medicaid program integrity. The system applies advanced statistical analytics, machine learning, and real-time data integration to identify anomalous billing patterns, high-risk providers, and potential fraud, waste, and abuse (FWA) across the Medicaid ecosystem.
Data Architecture
IMX-Ray™ is powered by IMX Data's proprietary healthcare claims repository, one of the largest commercially available datasets in the United States:
- 100+ billion healthcare claims processed
- 300+ million unique patient records
- $1.17 trillion in annual Medicare expenditures analyzed (CMS Actuaries CY 2025 est.)
- $971.4 billion in annual Medicaid expenditures analyzed (CMS-64 preliminary CY 2025)
- 617,503 unique billing provider NPIs tracked
- 227 million Medicaid billing records in current analysis set
- 9 live CMS data feeds integrated for real-time enrichment
Primary data sources include the HHS T-MSIS (Transformed Medicaid Statistical Information System), CMS NPPES NPI Registry, CMS-64 State Expenditure Reports, OIG LEIE Exclusion Database, Open Payments, Hospital Compare, Nursing Home Compare, and State Drug Utilization data.
Analytical Capabilities
The system employs 30 validated statistical tests organized across nine detection categories:
Claims Submission Tests (#1-15)
- Volume Anomaly Detection: Identifies providers with statistically significant deviations in claims volume, beneficiary counts, and billing frequency relative to specialty and geographic peers.
- Cost Anomaly Detection: Flags outlier reimbursement patterns including per-claim cost deviations, rate anomalies, and disproportionate spending relative to service mix.
- Pattern Recognition: Detects suspicious billing patterns including single-code concentration, temporal consistency anomalies, Benford's Law violations, and systematic upcoding indicators.
- Growth Anomaly Detection: Identifies explosive billing growth, rapid volume escalation, and new-entrant risk patterns commonly associated with fraudulent operations.
- External Reference Matching: Cross-references OIG Exclusion List, revoked provider databases, and enforcement action histories.
- Prescribing Analytics: Monitors controlled substance and opioid prescribing rates against specialty benchmarks and geographic norms.
Payer Adjudication Tests (#16-30)
- Payment Pattern Analysis: Detects charge-to-payment ratio outliers, allowed amount manipulation, and patient responsibility anomalies using ERA/835 remittance data.
- Denial and Resubmission Analysis: Identifies denial rate outliers, reason code concentration, and denial-and-resubmit cycling patterns indicative of organized billing fraud.
- Payment Velocity and Timing: Flags payment velocity anomalies, service-to-statement lag, payer-specific billing divergence, and Medicare-Medicaid reimbursement arbitrage.
- DRG and Facility Analysis: Detects DRG upcoding, discharge fraction anomalies, and contractual adjustment outliers across inpatient facilities.
- Reversal and Correction Patterns: Monitors reversal/correction frequency and payer-initiated reduction patterns that indicate systemic overbilling.
Risk Classification Framework
Each provider receives a composite Fraud Risk Score (0-100) based on the weighted severity and count of triggered detection flags. Classification tiers align with investigative prioritization:
- Critical (70-100): Immediate investigation recommended. Multiple severe flags indicating high probability of billing anomalies.
- High (40-69): Priority review. Several concerning indicators warranting detailed examination.
- Elevated (15-39): Monitoring recommended. Flags present but lower severity; may reflect legitimate practice variations.
- Standard (0-14): No significant anomalies. Billing patterns within expected parameters.
Important: Risk scores are investigative leads, not determinations of fraud. All flagged providers require human review by qualified investigators before any enforcement action.
Investigation Support Features
- Provider Deep-Dive: Comprehensive profiles including billing history, HCPCS code analysis, peer comparison, and risk factor breakdown
- Network Analysis: Maps provider affiliations and shared beneficiary patterns to identify coordinated fraud schemes
- Geographic Intelligence: Heat-map visualization of fraud density by state and region with drill-down capability
- Case Study Library: Documented analysis of major fraud schemes (Operation Gold Rush, Wound Care Networks, MA Upcoding) with detection methodology
- Real-Time CMS Integration: Live data feeds from 9 CMS endpoints for current provider verification and enrichment
- PDF Report Generation: Export investigation-ready fraud risk assessments with full provider analysis and supporting data
Deployment Options
| Configuration | Description | Data Scope |
|---|---|---|
| SaaS, Multi-tenant | Cloud-hosted, IMX-managed infrastructure. SOC 2 certified. | Full 100B+ claim and adjudication events dataset |
| SaaS, Dedicated | Isolated tenant with dedicated compute and storage. | Full dataset + custom feeds |
| On-Premises | Deployed within agency network boundary. FedRAMP-aligned. | Agency-specified scope |
| GovCloud | AWS GovCloud (US) or Azure Government deployment. | Full dataset, ITAR-compliant |
Data Sources & Integrations
2.7 billion annual claims, $971.4 billion (CY 2025 est.), 617,503 NPIs. T-MSIS data covering all 50 states, DC, and territories. CMS-64 preliminary spending, HMA analysis January 2026.
Real-time provider identity verification. NPI-validated provider records including names, addresses, specialties, and organizational affiliations via the National Plan and Provider Enumeration System.
State-level Medicaid spending calibration. FY 2023 quarterly financial data for geographic distribution weighting and state-level aggregate validation.
Office of Inspector General List of Excluded Individuals/Entities. Real-time cross-referencing against known sanctioned providers and excluded entities.
2.3 million synthetic Medicare claims across carrier, inpatient, outpatient, DME, HHA, hospice, SNF, and Part D. 13,408 unique providers, $4.24 billion in simulated spending. Access via the CMS Live Data view.
About IMX Data
IMX Data (imxresearch.com) operates one of the largest commercially available healthcare claims databases in the United States, processing over 100 billion claim and adjudication events representing 300+ million patients. The company provides data analytics, fraud detection, and healthcare intelligence solutions to federal agencies, state Medicaid programs, health plans, and research institutions.
IMX Data holds SOC 2 Type II certification and maintains security controls aligned with NIST SP 800-53. FedRAMP authorization is in progress.
For inquiries: imxresearch.com · This system contains evaluation data. Contact IMX Data for production deployment with full 100B+ claim and adjudication events dataset access.
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