Nurse Practitioners Under the Microscope
The Fastest-Growing Medicare Fraud Risk
Nurse practitioners are the fastest-growing provider type in Medicare. They now represent over 11% of all Medicare providers — more than any single physician specialty. They're filling critical access gaps in rural and underserved communities. But our AI fraud detection model has found something troubling: NPs are emerging as a new fraud risk vector, with flagged providers billing millions while operating under less oversight than physicians.
Key Findings
- • Our ML model flagged NPs billing $1.6M–$1.85M while matching convicted fraudster patterns
- • The top-flagged NP has a 94.3% fraud probability — higher than most flagged physicians
- • NPs have 500–1,500 clinical training hours vs 15,000+ for physicians
- • 27 states + DC allow NPs to practice with zero physician oversight
- • NP fraud patterns differ from MD patterns: less markup manipulation, more volume-driven billing
The Growth Explosion
Over the past decade, nurse practitioners have gone from a supporting role in Medicare to the single largest provider category by headcount. With approximately 1.2 million provider-year records, NPs outnumber Internal Medicine, Family Practice, and every other individual specialty.
This growth has been driven by several converging forces: physician shortages (especially in primary care), expanded scope-of-practice laws, lower training costs, and — critically for fraud analysis — the economic incentives of corporate healthcare staffing.
As we documented in our investigation into the nurse practitioner boom, NPs earn an average of just ~$26,000 per year from Medicare. But averages mask a long tail of extreme outliers — and that's where the fraud risk lives.
The AI-Flagged NPs
Our machine learning model — trained on 8,300+ confirmed Medicare fraudsters from LEIE and DOJ data — flagged two nurse practitioners with billing patterns that closely match convicted criminals. Both are billing in the seven-figure range, far above the NP specialty average.
Natalia Maximovsky — NY (Rank #34)
John Adeiza — CA (Rank #311)
Natalia Maximovsky: Rank #34 Out of 500
Maximovsky, a New York-based nurse practitioner, ranks #34 out of 500 flagged providers in our model — placing her in the top 7% of all AI-flagged providers across every specialty. Her 94.3% fraud probability is driven by two factors: a high markup ratio of 2.57x (meaning she charges Medicare 2.57 times what it actually pays) and seven-figure total billing.
To put this in context: the average NP bills Medicare ~$26,000 per year. Maximovsky's total billing of $1.6M is roughly 63x the NP specialty average. While high-volume NP practices exist legitimately, this level of billing typically indicates either an extremely high-volume clinic, "incident-to" billing arrangements, or patterns worth investigating.
John Adeiza: $1.85M from California
Adeiza bills even more than Maximovsky in raw dollars — $1.8M — but with a lower fraud probability of 89.2%. His markup ratio of 2.08x is closer to the system average, and his billing was flagged primarily for sheer volume. With 30,588 services across 10,823 beneficiaries, he's averaging 2.83 services per patient — elevated but not extreme.
The difference between these two cases illustrates how NP fraud patterns diverge from physician fraud. While flagged physicians often show extreme markup manipulation or impossible service volumes, flagged NPs tend to show volume-driven patterns — high total billing driven by high patient throughput rather than aggressive upcoding.
NP vs MD Fraud Patterns: What's Different?
| Factor | Flagged NPs | Flagged MDs (avg) |
|---|---|---|
| Average fraud probability | 91.7% | 90.8% |
| Average markup ratio | 2.33x | 2.41x |
| Average services/beneficiary | 2.72 | 3.64 |
| Primary risk signal | Volume + billing level | Markup + services/patient |
| Oversight level | Variable / Often none | Peer review + hospital credentialing |
The most striking difference isn't in the billing patterns — it's in the oversight infrastructure. Physicians operate within a web of peer review, hospital credentialing, board certification renewal, and malpractice scrutiny. NPs in full-practice-authority states can operate entirely independently, with no physician reviewing their billing or clinical decisions.
The Regulatory Gap
The scope-of-practice debate has traditionally focused on patient safety and access to care. But there's a dimension that rarely gets discussed: fraud risk.
The Oversight Asymmetry
- • 4 years medical school + 3-7 years residency
- • Hospital credentialing committees
- • Peer review requirements
- • Board certification and MOC
- • Malpractice insurance scrutiny
- • 2-3 year graduate program
- • 500-1,500 clinical hours
- • Independent practice in 27 states + DC
- • No mandatory peer review
- • Limited billing audit triggers
When a physician bills $1.6 million to Medicare, it triggers internal flags at their hospital, their malpractice insurer, and often their specialty board. When an NP in a full-practice-authority state does the same thing, who's watching?
CMS's fraud detection systems were built for a physician-dominated system. The algorithms compare providers against specialty peers — but NP "peers" span an enormous range from part-time rural primary care to high-volume urban specialty clinics. The statistical baselines that catch physician outliers may miss NP outliers entirely.
The "Incident-To" Loophole
One of the most exploitable billing arrangements in Medicare involves NPs. Under "incident-to" billing, services provided by an NP can be billed under a supervising physician's NPI at 100% of the physician rate (vs 85% under the NP's own NPI). The requirements are minimal: the physician must have seen the patient initially and be "in the suite" during subsequent visits.
This creates a perverse incentive structure. A single physician can "supervise" multiple NPs across a practice, billing all their services at full physician rates. The volume appears under the physician's NPI, potentially inflating their numbers. Or the NP bills under their own NPI at 85% — still generating more revenue than the NP's salary costs. Either way, the corporate math works.
Corporate Medicine Meets NP Staffing
As we explored in our corporate medicine investigation, large healthcare companies have discovered that NPs are a profit center. An NP earning $110,000 in salary who bills Medicare $500,000+ generates significant margin — margin that increases further if the billing is aggressive.
The flagged NPs in our model may be individual bad actors, or they may be symptoms of a system that incentivizes volume over quality while providing insufficient oversight. The data can't tell us which — but it can tell us that the patterns match those of convicted fraudsters.
What Needs to Change
This isn't an argument against NPs. Nurse practitioners provide vital care to millions of Medicare beneficiaries, often in communities that physicians won't serve. The average NP billing ~$26,000/year is doing exactly what they should be: providing accessible primary care.
But the fraud detection and oversight infrastructure needs to catch up to the workforce reality:
- NP-specific fraud baselines: CMS should develop statistical norms specifically for NP billing rather than lumping them with physician specialties
- Billing audit triggers: NPs billing above $500K should face the same audit scrutiny as physicians at equivalent levels
- Incident-to reform: The 100% billing rate for NP services billed under physician NPIs creates misaligned incentives
- State reporting: Full-practice-authority states should implement billing oversight mechanisms to replace the physician supervision they eliminated
The Bottom Line
NPs are here to stay — and that's a good thing for healthcare access. But Medicare's fraud detection systems were designed for a world where physicians did most of the billing and faced multiple layers of institutional oversight. That world no longer exists. The fastest-growing provider type in Medicare deserves fraud detection systems built for how they actually practice — not systems designed for a different era.
Disclaimer: This analysis is based on publicly available CMS Medicare Provider Utilization and Payment Data (2014–2023) and our machine learning model trained on confirmed fraud cases. Being flagged by an AI model does not constitute an accusation of fraud. Named providers have not been charged with any crime. All data is from public sources.
Related Investigations
Data Sources
- • Centers for Medicare & Medicaid Services (CMS) — Medicare Provider Utilization and Payment Data (2014–2023)
- • OpenMedicare ML Fraud Detection Model v2.0 — Trained on 8,300+ LEIE/DOJ confirmed fraud cases
- • American Association of Nurse Practitioners — State Practice Environment Map (2025)
- • U.S. Department of Health and Human Services — Office of Inspector General Reports
- • Bureau of Labor Statistics — Nurse Practitioner Employment Projections
Last Updated: February 2026
Note: All data is from publicly available Medicare records. OpenMedicare is an independent journalism project not affiliated with CMS.