If you follow False Claims Act (FCA) enforcement, you’ve probably noticed a shift over the last few years. The classic whistleblower – the insider, the employee who witnesses fraud firsthand and comes forward – is no longer the only game in town.
A new kind of relator has arrived: the data miner.
Data miners don’t work inside the companies they’re targeting. Instead, they analyze publicly available government datasets, looking for statistical anomalies that suggest fraud.
In theory, it’s a powerful model. The government generates enormous amounts of data, and patterns that might indicate fraud can hide in plain sight. A company billing a particular procedure at 30 times the national average, for instance, is a signal worth investigating.
And the model has clearly caught on. Total FCA jumped from around 980 in the 2024 fiscal year to roughly 1,300 in 2025. Data miners now account for approximately 45 percent of whistleblower-initiated (qui tam) FCA lawsuits. That is a dramatic shift in a short period of time.
But as artificial intelligence (AI) tools have made it easier to generate statistical analyses, the volume of data-driven filings has grown faster than their quality. Many cases rely on thin inferences that may have entirely lawful explanations. And every filing, regardless of merit, consumes finite U.S. Department of Justice (DOJ) resources.
That’s the backdrop for DOJ Civil Division’s April 30 announcement on the launch of its FOCUS initiative (Fraud Oversight through Careful Use of Statistics). The message from DOJ is essentially this: we welcome data miners, but we’re going to prioritize working with the ones who are doing it right. That means demonstrated analytical rigor, a sound understanding of the relevant legal and regulatory framework, validated methodologies, and allegations specific enough to hold up in court. DOJ has even set up a dedicated email address for data miners to request pre-filing meetings with the Civil Fraud Section.
The government is essentially creating a channel to vet its own future partners in enforcement. And almost immediately, two settlements illustrated what a successful data-mining case looks like in practice.
The first involved Lincoln Analytics, a firm that describes itself as using data and investigation to detect healthcare fraud. Lincoln flagged a California vascular physician, Dr. Feliciano Serrano, who was billing Medicare for stent and atherectomy procedures at roughly 30 times the national average. The underlying conduct, as alleged, was striking. One patient received approximately 42 stents over seven years, and another received 16 atherectomies in his legs. The case settled for more than $6.73 million, with Lincoln Analytics receiving nearly $976,000 as its share.
The second case involved Integra Med Analytics, which identified three affiliated Illinois skilled nursing facilities (SNFs) billing Medicare for rehabilitation services at inflated reimbursement levels, without regard to patients’ actual clinical needs. That case settled for $300,000.
Both cases closed within days of the FOCUS announcement, illustrating exactly the kind of rigorous, analytically grounded work the initiative is designed to encourage.
