On Friday February 13, 2026, the Department of Government Efficiency (“DOGE”) unit working within the U.S. Department of Health and Human Services (“HHS”) released to the public on https://opendata.hhs.gov/ what it hailed as “the largest Medicaid dataset in department history.”
DOGE has been mining Medicaid and Medicare data for the past year. The newly released dataset aggregates provider-level claims data by billing or servicing provider, procedure code, and month, and covers fee-for-service, managed care, and CHIP claims from 2018-2024.
The release of the Medicaid dataset was heralded as a way to “crowdsource” the routing out of Medicaid fraud, providing broad access to review provider-level billing data in the hopes that everyone from data scientists to amateur sleuths will take an interest in discovering bad actors, and reporting such to both state and federal authorities. While state and federal authorities have been touting their use of data analytics to combat healthcare fraud in recent years, including through the U.S. Department of Justice’s newly created healthcare fraud data Fusion Center, the new Medicaid dataset claims to assist in uncovering fraud by “identify[ing] unusual billing patterns for specific services, states, or providers.”
Publicized first via the DOGE-HHS team’s social media account on X.com (formerly Twitter.com), the media platform owned by Elon Musk, the public release of the Medicaid dataset comes on the heels of the U.S. Department of the Treasury’s Financial Crimes Enforcement Network (“FinCEN”) creation of a website for its Office of the Whistleblower, which was described as a “new dedicated webpage to confidentially accept whistleblower tips on fraud, money laundering, and sanctions violations.” The FinCEN Office of the Whistleblower is focused on incentivizing the public to report, among other things, misuse of federal funding and taxpayer dollars. Both DOGE-HHS’s and the Department of the Treasury’s push to incentivize the public to find and report fraud come after independent journalists loudly called out allegedly rampant Medicaid fraud in child care centers and nonemergency medical transportation companies in Minnesota and alleged widespread fraud in California.
While there are longstanding qui tam provisions of the federal False Claims Act [31 U.S.C. § 3730] that permit private citizens to bring claims for violations of the False Claims Act in return for a portion of the recovered proceeds, the Trump administration’s fresh take on deputizing members of public to act as fraud investigators – particularly through more reliance on data analytics – may be a look into the future of fraud enforcement. Various third party websites analyzing the data have already sprung up. As one example, getmedicaiddata.com connects the DOGE-HHS dataset with the NPI Registry, giving investigators easier access to providers’ addresses and phone numbers, making further follow-up investigation by site visits or phone calls easier. This push toward greater reliance on data analytics has the potential to prematurely label conduct as fraud that may be completely legal. Data analytics are a starting point for health care fraud investigation, but not an endpoint.
As transparency is accelerated by technology, and data analytics are performed by third party websites and others, healthcare providers should use this as a time to ensure their billing and coding procedures (particularly with respect to Medicare, Medicaid and other government payor claims) are in compliance.
Should you have any questions regarding the updated DOGE-HHS dataset and its potential implications to your business, please contact one of the authors or your usual EBG attorney.
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