The US Department of Justice (DOJ) recently announced the Fraud Oversight through Careful Use of Statistics (FOCUS) initiative to address the growing number of False Claims Act (FCA) qui tam complaints filed by “data miners,” defined as individuals or organizations that use publicly available government data rather than traditional insider information to identify patterns that may indicate fraud.
While FOCUS is not limited to healthcare, the announcement should be on the radar of healthcare and life sciences organizations. It reflects DOJ’s continued investment in data-driven enforcement and the growing role of external relators who may never have worked for, contracted with, or otherwise interacted with the target organization.
For healthcare organizations, this means FCA risk may increasingly arise from patterns that can be identified in public claims, payment, enrollment, ownership, quality, or other publicly available program data.
Key Takeaways
- DOJ’s new FOCUS initiative is designed to help identify and prioritize stronger FCA qui tam complaints filed by data miners.
- The initiative reflects the growing role of public data analysis, statistics, and artificial intelligence (AI) in FCA enforcement.
- Organizations should anticipate heightened FCA scrutiny of publicly available data and should proactively review compliance practices in light of DOJ’s evolving partnership with data miners.
From Insiders to Data Miners
The FCA allows private relators to bring actions on behalf of the United States and share in any recovery. These qui tam relators have historically included current or former employees, contractors, competitors, billing personnel, clinicians, and others with access to nonpublic information about an organization’s practices.
“Data-mining” relators are not insiders but rather outside individuals or organizations who search public datasets for outliers, anomalies, or correlations to identify patterns that could reflect false claims. According to DOJ, this model is driving a significant portion of recent qui tam activity, especially in the advent of the massive spending programs implemented in response to the COVID-19 pandemic.
DOJ received 980 qui tam complaints in fiscal year 2024, nearly 1,300 in fiscal year 2025, and more than 780 in fiscal year 2026 thus far. Data miners have accounted for more than 45% of all qui tam complaints since fiscal year 2024.
The FOCUS Initiative
Through FOCUS, DOJ seeks to identify, prioritize, and collaborate with data miners whose analyses provide strong evidence of potential FCA violations. DOJ has invited data miners to meet with the Civil Fraud Section to discuss their capabilities and explain why their data signals reliably correlate with fraudulent conduct. These meetings are not a prefiling requirement, but DOJ has indicated that it will prioritize data miners who demonstrate prefiling diligence, analytical rigor, familiarity with program rules, and legally sufficient allegations.
The FOCUS announcement reflects that DOJ will not endorse every data-driven theory of fraud it receives. In fact, DOJ’s guidance emphasizes that the strength of a data-mining case depends on both the quality of the underlying data and the rigor of the analysis. DOJ pointed to pandemic-relief cases as one example, noting that the public release of Small Business Administration (SBA) loan data contributed to a surge in qui tam complaints.
The announcement notes that more than three-fourths of approximately 840 SBA pandemic-relief settlements and judgments were DOJ-initiated FCA cases, highlighting a comparatively lower success rate for data miner–initiated actions.
Why This Development Matters for Healthcare and Life Sciences Organizations
Healthcare remains a central focus of FCA enforcement, and the FOCUS initiative arrives at a time of broader coordination between DOJ and the US Department of Health and Human Services (HHS). DOJ and HHS have identified several healthcare enforcement priorities, including Medicare Advantage, drug and device pricing, barriers to patient access and network adequacy, kickbacks involving federally reimbursed items and services, defective medical devices, and manipulation of electronic health records (EHR) systems to drive inappropriate utilization.
DOJ and HHS have emphasized the use of enhanced data mining and HHS Office of Inspector General findings to identify new leads in these areas of enforcement focus. Indeed, in recent comments, Deputy Assistant Attorney General Brenna Jenny has said that “data” may be a company’s “next whistleblower.”
The practical implication for healthcare and life sciences organizations is the need for increased internal oversight and analysis of internal data. If the government has solicited data-mining relators to share their data analysis, these organizations should consider increasing resources to stay proactive.
Relators may look for unusual billing or coding patterns, high utilization of particular services or products, referral patterns that appear to correlate with financial relationships, Medicare Advantage risk-adjustment trends, quality-reporting anomalies, network adequacy concerns, or EHR configurations that suggest inappropriate ordering or documentation.
These patterns and subsequent analyses, even if incomplete or wrong, may still draw government attention. It is incumbent upon organizations to know their own data better than outside actors in order to quickly combat assertions of fraud in the event of a government request for information.
Implications and Recommendations: What Can You Do?
Healthcare and life sciences organizations should consider taking steps to analyze their own data from the perspective of an external data miner. This may include assessing whether particular providers, facilities, business units, service lines, products, or billing practices appear as statistical outliers and whether the organization can document legitimate explanations for those patterns.
Organizations should consider updating their compliance programs, internal controls, and data governance practices to ensure alignment with relevant program eligibility and regulatory requirements. This effort may involve considerations for the implementation of tools such as AI large language models and sophisticated data analytics algorithms.
Organizations should prepare for the possibility that a data-driven allegation may lead to a civil investigative demand, subpoena, audit, or request for information. Early response efforts should include preserving relevant data, identifying the public or internal datasets that may have generated the allegation, testing the methodology behind any alleged anomaly, and developing the factual and legal context necessary to respond.
Conclusion
The FOCUS initiative underscores DOJ’s increasing reliance on private data analysis to direct FCA enforcement. For healthcare and life sciences organizations, the initiative is another reminder that FCA risk may arise not only from insider allegations but also from how an organization’s data appears to external reviewers. Proactive data review, strong documentation, and coordinated compliance oversight can help organizations identify potential issues, explain legitimate outliers, and respond effectively to data-driven FCA scrutiny.
How We Can Help
Morgan Lewis advises healthcare and life sciences organizations on FCA risk assessments, internal investigations, data-driven compliance reviews, program integrity audits, and responses to civil investigative demands, subpoenas, audits, and other government inquiries. We will continue to monitor DOJ’s FOCUS initiative, the DOJ-HHS False Claims Act Working Group, and broader developments in data-driven healthcare enforcement.