Guide
How Medicaid Fraud Works
Common schemes, red flags, and how data analysis can detect them.
The Scale of the Problem
Medicaid fraud is estimated to cost taxpayers $100 billion or more annually — roughly 10% of total program spending. The HHS Office of Inspector General (OIG) recovers less than 5% of that each year.
The problem is structural: Medicaid processes billions of claims per year through a fee-for-service model that pays providers for each service billed. This creates inherent incentives to over-bill. With 617,000+ active providers and 10,000+ billing codes, manual auditing can only catch a fraction of abuse.
That's why data-driven detection matters. By analyzing 227 million billing records at scale, patterns emerge that would be invisible to traditional auditing. Our analysis flagged 1,860 providers with unusual billing patterns worth investigating.
Common Fraud Schemes
Phantom Billing
Billing for services, procedures, or supplies that were never actually provided to a patient. This is the most straightforward form of fraud — pure fabrication of claims.
Example: A provider submits claims for 50 home health visits that never occurred.
Upcoding
Billing for a more expensive service or procedure than what was actually provided. By substituting higher-paying billing codes, providers can dramatically inflate their reimbursements.
Example: Billing a comprehensive office visit (99215) when only a basic visit (99213) occurred.
Unbundling
Splitting services that should be billed as a single bundled code into multiple separate charges to increase total reimbursement.
Example: Billing lab tests individually instead of as a panel, charging 3× more than the bundled rate.
Kickbacks & Referral Schemes
Paying or receiving payment for patient referrals. Federal anti-kickback laws prohibit any form of compensation for referring Medicaid patients.
Example: A lab paying doctors $50 per patient referral for unnecessary blood tests.
Patient Churning
Scheduling unnecessary return visits or repeat services to generate additional billable claims. Patients may not realize they’re being used to pad billing.
Example: Requiring weekly visits for a condition that only needs monthly monitoring.
Identity Fraud
Using stolen patient identities or Medicaid numbers to bill for services. Sometimes involves enrolling fake patients or billing for deceased individuals.
Example: A provider billing under 200 patient IDs, many of whom have never visited the facility.
How Data Analysis Detects Fraud
Statistical Testing
We run 9 statistical tests that compare each provider's billing against national benchmarks for their specific procedure codes. Tests include cost outlier detection, billing swing analysis, new entrant monitoring, and rate outlier identification. Providers are flagged when their patterns deviate significantly from peers billing the same codes. Read full methodology →
Machine Learning
Our Random Forest ML model (AUC 0.77) was trained on 514 providers confirmed as fraudulent by the OIG Exclusion List. It scores every provider on how similar their billing patterns are to known fraud cases — catching subtle multi-feature patterns that rule-based tests might miss. Learn about the ML model →
Advanced Techniques
We also apply Benford's Law analysis (digit distribution anomalies), CUSUM change-point detection (sudden billing shifts), billing velocity analysis (impossible claim volumes), and peer similarity clustering. When multiple independent methods flag the same provider, the probability of a false positive drops dramatically.
What We Found
1,860
providers flagged
$226B
in flagged spending
0
on OIG exclusion list
24
investigations published
None of our flagged providers appear on the OIG's existing exclusion list — suggesting our analysis surfaces new suspicious activity that hasn't been investigated yet. Explore the findings in our 24 investigation articles.
Explore the Data Yourself
Search any provider, filter by state, or browse our investigations.
Related Guides
How to Read a Medicaid Billing Record
Understand NPIs, claims, beneficiaries, and what the numbers mean on provider profiles.
Understanding HCPCS Codes
What billing codes mean, how they're structured, and which ones are most associated with fraud.
Top Medicaid Billing Codes
The highest-spending HCPCS codes explained in plain English with fraud risk levels.
Medicaid Fraud by State
Which states have the most flagged providers and biggest spending anomalies.