Technology was supposed to make health care more transparent, efficient, and accountable. Instead, it’s created new ways to commit fraud—faster, quieter, and at scale.
What used to take a coding clerk with a spreadsheet can now be done by an algorithm touching millions of claims. The fraud hasn’t gone away; it’s just gone digital.
Welcome to the era of data-driven health care fraud. If you believe that you are aware of data-driven healthcare fraud occurring, contact our algorithm fraud lawyer today.
The New Face Of Medicare Fraud
Traditional fraud—kickbacks, upcoding, fake patients—still dominates the enforcement headlines. But beneath that, a quieter revolution is happening inside the billing systems, data warehouses, and EHRs of hospitals, insurers, and vendors.
Today, the fraud isn’t always the result of a rogue doctor or corrupt facility. Increasingly, it’s baked into software logic, predictive algorithms, and automated billing pathways.
If you’re an insider who works with electronic health records, revenue-cycle management, or coding software, you might already see it: the same “optimizations” applied over and over, creating inflated claims en masse.
What “Data-Driven Fraud” Means
The term covers a wide spectrum. It includes everything from simple automation abuse to deliberate manipulation of health data. The common thread: the fraud originates in software design or data handling, not just human judgment.
Common Patterns:
- EHR Manipulation: Templates that auto-populate exam findings or “copy forward” old notes, making every patient appear sicker or every exam more comprehensive.
- Algorithmic Upcoding: Billing software that automatically selects higher paying CPT or DRG codes under the guise of “revenue optimization.”
- Data Mining for Unsupported Diagnoses: Risk-adjustment vendors comb through charts to find any past mention of a diagnosis, valid or not, then feed it to Medicare Advantage systems to inflate capitation payments.
- “Documentation Assist” Tools: AI or NLP tools that suggest phrasing or diagnoses that boost coding levels, regardless of medical necessity.
- Manipulated Audit Trails: IT departments altering timestamps or user logs to cover up phantom documentation or after-the-fact edits.
All of these can create a false claim—just at a volume and speed that paper-based fraud could never achieve.
The False Claims Act Still Applies
Some executives seem to think that because the fraud is committed by software, not a person, it’s somehow legally different. It isn’t. The False Claims Act (31 U.S.C. §§ 3729–3733) applies just the same.
If a hospital, insurer, or vendor knows its technology is generating false claims—or even acts with reckless disregard—it’s liable. That includes knowingly using algorithms or tools designed to inflate reimbursement.
Key Point:
The “knowledge” requirement under the FCA doesn’t mean someone must intend to defraud. It’s enough that management knew or should have known that the system was producing inaccurate claims and failed to correct it.
Where It’s Happening
1. Electronic Health Record (EHR) Manipulation
EHRs were supposed to reduce errors. Instead, they’ve made it easier to hide them. Common abuses include:
- Auto-filled templates that record full physical exams even when only limited exams occurred.
- “Copy-forward” functions that replicate diagnoses and findings from prior visits.
- Default settings that mark all patients as having high-complexity histories or reviews of systems.
Case in point: DOJ has already settled with several EHR vendors for certification fraud—falsifying product testing to meet “Meaningful Use” standards. The same enforcement logic applies to vendors whose software knowingly generates false documentation.
2. Medicare Advantage Risk-Score Inflation
This is perhaps the most lucrative data-driven fraud in the country right now. Medicare Advantage (MA) plans receive fixed monthly payments per enrollee, adjusted for how “sick” the patient population appears. The sicker the patient, the higher the payment. That creates a powerful incentive to make everyone look sicker on paper.
Insurers and their contractors use data-mining algorithms to hunt for any potential diagnosis—often from years-old or irrelevant records—and submit it to CMS for higher reimbursement.
DOJ has already filed or settled risk-adjustment cases against Cigna, Kaiser Permanente, Elevance (Anthem), Sutter Health, and UnitedHealth. In each, the allegations center on algorithmic identification of unsupported diagnoses, internal warnings ignored, and a systemic effort to inflate scores.
This is the new frontier of health care fraud—false claims generated by data analysis.
3. Revenue-Cycle Automation and “Optimization” Software
Hospitals and health systems increasingly rely on third-party “coding optimization” tools that automatically assign the “best” code for reimbursement. Some of these programs quietly nudge coders toward higher-paying codes or “remind” clinicians to include comorbidities that aren’t clinically relevant.
When a vendor markets a system specifically for its ability to “maximize revenue,” and the result is widespread overbilling, both the vendor and the provider can face FCA liability.
The question DOJ asks is simple: Were the codes supported by the medical record? If not, the defense that “the software did it” doesn’t help.
4. Telehealth and Digital Platforms
The explosion of telemedicine and digital health platforms during COVID-19 opened new fraud vectors:
- Platforms billing for visits that never happened.
- “Automated encounters” where AI-generated notes are submitted as physician documentation.
- DME or lab companies integrating telehealth widgets that instantly generate orders without real exams.
These schemes blur the line between billing automation and fabrication—and DOJ is increasingly treating them as the latter.
Why It’s Hard To Detect
Data-driven fraud hides in plain sight. To regulators, the claims data often look clean: every box is checked, every signature is in order.
The deception lies deeper—in the inputs, defaults, and algorithms that shape the data itself. Unless investigators obtain internal documentation showing how those systems were designed or calibrated, the fraud appears compliant.
That’s why insiders are essential. The people who know how the software actually works—the coders, data analysts, compliance officers, and engineers—are the ones who can explain the gap between what the system reports and what actually happened.
The Whistleblower’s Edge
Whistleblowers have a unique vantage point. They see:
- Emails from executives instructing IT teams to “tune the model” for higher reimbursement.
- Audit results showing that “optimized” documentation doesn’t match patient encounters.
- Compliance concerns dismissed because “everyone in the industry does it.”
Those facts are the connective tissue that turns an algorithmic pattern into an FCA case.
Whistleblowers in data-driven fraud cases don’t just expose billing errors—they expose systems intentionally designed to deceive. That’s a different magnitude of misconduct.
DOJ’s Growing Toolkit
DOJ and HHS-OIG have quietly built internal data analytics teams that can match claim patterns across millions of records. They’re not just flagging outliers; they’re now reconstructing how algorithms make decisions.
Expect DOJ to increasingly use:
- Algorithmic audits to examine how vendors structure coding logic.
- E-discovery of machine learning models to reveal how risk scores or codes are assigned.
- Cooperation with CMS data scientists to identify systematic inflation across payers.
As this capability matures, the agency won’t just prosecute fraud—it will dissect the code that caused it.
Compliance Officers Should Worry
The old defense—“we didn’t know”—doesn’t work anymore. Compliance teams that rely on vendors’ representations about their software are still responsible for ensuring accuracy.
If an internal audit or coder complaint raises concerns and management ignores it, that’s reckless disregard under the FCA. Expect DOJ to hold compliance executives personally accountable for allowing algorithmic fraud to continue.
The Road Ahead
As health care digitizes, fraud will become more technical and less visible. But the principle remains simple: when data is manipulated to extract unearned federal dollars, that’s a false claim.
Whistleblowers are the only people positioned to expose how these systems work from the inside—how algorithms are tuned, how templates are misused, how risk data is “enhanced.”
And the stakes are enormous. Risk-adjustment fraud alone has cost taxpayers tens of billions of dollars; EHR manipulation may rival that over the next decade.
Closing Thoughts
Technology doesn’t commit fraud—people do. But the people who design and deploy these systems have found a new way to exploit Medicare’s trust.
The challenge for enforcement is catching up to the complexity. The challenge for whistleblowers is simpler: recognizing that “optimization” can cross the line into deceit.
If you work in health care technology, billing, or compliance and see systems producing revenue that doesn’t make clinical sense, it’s not a coding quirk. It might be data-driven fraud—and you may be in the best position to stop it. Contact Whistleblower Law Partners today to schedule a consultation.