On April 30, 2026, the U.S. Department of Justice launched the Fraud Oversight through Careful Use of Statistics (FOCUS) Initiative to strengthen the Department’s coordination with a rising wave of “data miner” whistleblowers who use publicly available data to bring cases under the False Claims Act. Unlike traditional qui tam relators, who are often company insiders with firsthand knowledge of alleged misconduct, data miners analyze publicly available government data to identify alleged patterns of fraud against federal programs. FOCUS signals the new National Fraud Enforcement Division’s commitment to data-driven enforcement, including through the use of artificial intelligence. Healthcare companies and other businesses that receive federal funds should review their public data footprint as part of their routine compliance program and monitor the legal developments that will determine the reach of data-mined fraud claims.
A New Wave of Data Miner Whistleblowers
The rise of data miner whistleblowers coincides with an unprecedented enforcement environment under the False Claims Act. In fiscal year 2025, the DOJ reported $6.89 billion in FCA settlements and judgments, marking the highest single-year total in the statute’s history. Healthcare defendants bore the brunt of that exposure, accounting for $5.7 billion, or 83 percent, of the total. Not surprisingly, the volume of qui tam filings has surged during this time. Relators submitted 980 complaints in fiscal year 2024, a record at the time, only to shatter that mark the following year with nearly 1,300 complaints. With over 780 complaints already filed in fiscal year 2026, the Department is on track for yet another record.
Driving much of this growth is the emergence of the data miner as a qui tam relator. Since fiscal year 2024, data miners have accounted for more than 45 percent of all qui tam complaints, which is a striking figure given that these filers have no insider access to the defendants they target and rely instead on patterns detected in publicly available government data. Commentators have noted that professional data miner relators are often backed by litigation funding to support both their data analysis and private investigation activities. The proliferation of agentic AI tools designed to detect fraud will only accelerate that trend.
The DOJ has been tracking this shifting landscape. In January 2026, at the American Conference Institute’s 13th Annual Advanced Forum on False Claims and Qui Tam Enforcement, the Deputy Assistant Attorney General for the Commercial Litigation Branch of the Civil Division warned, “your next whistleblower could be your data.” FOCUS reflects the Department’s recognition of the new reality of data-driven enforcement.
The FOCUS Initiative
The surge in data miner qui tam filings presents a double-edged problem for the DOJ. Each new complaint, however marginal, triggers a mandatory review obligation that strains the Department’s resources. At the same time, the most rigorous data miners, armed with private funding and AI-assisted analytics, represent a force multiplier that the DOJ is plainly reluctant to forgo. As the Department put it in the FOCUS announcement, “the 342 million American citizens play an important role in amplifying the Department’s resources and helping to identify potential fraud that might otherwise go undetected.”
FOCUS is designed to resolve that tension by directing the Department’s attention toward the most meritorious submissions. The stated goal is “to improve the Department’s ability to prioritize working with the most successful data miners.” To that end, the DOJ has articulated a set of best practices for would-be relators, directing them to: (1) provide “valuable leads through high-quality, reliable, and predictive data analyses and signals and a thorough understanding of the relevant legal obligations”; (2) plead the circumstances of fraud with particularity; (3) “articulate how the data, in combination with other available evidence, suggests both scienter and falsity,” as opposed to innocent explanations; and (4) “adequately understand program eligibility requirements and relevant regulatory frameworks.”
To implement these priorities, the Department has invited data miners to meet directly with FOCUS representatives so that the Civil Fraud Section can identify and engage with those who have demonstrated analytical rigor, familiarity with program rules and applicable law, and sophisticated technological capabilities. The Department has made clear that it “will prioritize high-quality data miner qui tam actions” in allocating its enforcement resources.
Takeaways and What to Watch
Proactive Data Review. Compliance programs must account for external data mining. Because data miners use information that is already publicly available, organizations can and should conduct their own rigorous audits of claims, billing, and government-reported data before an outside party does it for them. That exercise serves two purposes: identifying compliance gaps that warrant remediation, and anticipating whether the organization’s public data profile could support a plausible qui tam complaint.
For healthcare organizations in particular, the available datasets are extensive. The richest vein comes from CMS, which publishes detailed provider billing and utilization data, hospital financial and operational data through HCRIS, and provider enrollment and exclusion information through PECOS and the OIG’s LEIE. Earlier this year, HHS released provider-level Medicaid billing data for the first time, covering January 2018 through December 2024. A sophisticated data miner cross-referencing these sources can construct a detailed, provider-specific portrait of potential fraud without ever setting foot inside an organization.
Legal Developments. Several cases have already begun to test the viability of data-driven qui tam complaints, and organizations should monitor how courts apply core FCA doctrines to data-mined allegations.
To survive dismissal, a qui tam complaint must satisfy both the plausibility standard under Rule 8 and the heightened fraud pleading standard under Rule 9(b), including the who, what, where, and when. A claim is not plausible if the facts pleaded are equally consistent with lawful conduct and an “obvious alternative explanation.” These standards were applied to data-mined allegations in United States ex rel. Integra Med Analytics LLC v. Baylor Scott & White Health, 816 F. App’x 892 (5th Cir. 2020). There, a Texas-based data forensics firm alleged that Baylor Scott & White used inflated codes to falsely bill Medicare, relying primarily on statistical analysis of the hospital’s billing patterns. The Fifth Circuit affirmed dismissal, holding that statistical billing anomalies can support FCA claims “when paired with particular details” under Rule 9(b), but cannot carry the complaint if they are equally consistent with a lawful and obvious alternative explanation. The Ninth Circuit reached the same conclusion in United States ex rel. Integra Med Analytics LLC v. Providence Health & Services, 854 F. App’x 840 (9th Cir. 2021), holding that outlier billing patterns standing alone were insufficient to satisfy the plausibility standard.
Data miner relators must also navigate the FCA’s public disclosure bar, which requires dismissal of a qui tam action if “substantially the same” allegations or transactions were previously disclosed in a federal proceeding or report, or through the news media — unless the action is brought by the Attorney General or the relator qualifies as an original source. This provision poses a particular challenge for data miners who rely solely on information published by the federal government. In United States ex rel. Relator LLC v. Howard D. Kootstra and Golden Empire Mortgage, Inc., Case No. 1:22-cv-00924-TLN-CDB, 2024 WL 3666470, at *4 (E.D. Cal. Aug. 6, 2024), the district court granted a motion to dismiss an FCA complaint alleging PPP fraud on the ground that the complaint was based on information contained in a “federal report” — specifically, data published on the federal website PandemicOversight.gov. Other courts have reached the same conclusion. United States ex rel. Relator LLC v. Sunshine, No. 8:23-CV-00134-JVS-ADS, 2025 WL 2428470, at *4 (C.D. Cal. June 30, 2025); United States ex rel. Relator LLC v. Erskine, No. 22CV1158-LL-AHG, 2025 WL 796621, at *5 (S.D. Cal. Feb. 25, 2025). It remains to be seen whether the collaboration under FOCUS will prompt the DOJ to either intervene more frequently in data miner cases or to invoke its authority more aggressively to block dismissals under the public disclosure bar.
Conclusion
FOCUS confirms that data-driven FCA enforcement is here to stay. With data miners filing nearly half of all qui tam complaints, the DOJ has chosen to embrace this new class of relators rather than limit them. For healthcare organizations and other government contractors, the message is straightforward: audit your own publicly available data before an outside algorithm does it for you, and monitor the legal developments that will determine the viability of data-mined complaints in the future.
Leech Tishman has extensive experience advising organizations on False Claims Act, government enforcement, and compliance-related matters. Our team is prepared to help clients assess how the DOJ’s FOCUS Initiative and the growing use of data-mined qui tam complaints may affect their litigation risk, compliance programs, public data footprint, or response strategy. For assistance or additional information, please contact David H. Chao at dchao@leechtishman.com or Harry J. Nelson at hnelson@leechtishman.com, Partners in Leech Tishman’s Healthcare and Litigation Practice Groups.