HHS deploys ChatGPT and AI tools to hunt healthcare fraud across all 50 states

The Trump administration expands its use of AI in the hunt for healthcare fraud

NEW YORK (AP) -- The U.S. Department of Health and Human Services on Thursday announced it is supercharging its use of artificial intelligence to police how states and other recipients of federal health dollars are auditing their programs. The move is intended to tamp down risks of fraud and save the government money. The department will use ChatGPT and other AI tools to analyze audit reports from all 50 states on an ongoing basis, said Gustav Chiarello, the assistant secretary for financial resources who is leading the new program. "It's classic big government: Everyone files an audit and it lands with a thud and no one does anything about it," Chiarello said in an interview. "Here, with AI, we're able to dig into it." The move builds on the department's embrace of generative AI for investigating state Medicaid programs, automating administrative tasks and editing text. AI tools can be a powerful aid in finding patterns or problems across large documents, but critics say the government should use them with caution because they frequently make mistakes and can have unintended biases. The Trump administration and Vice President JD Vance's anti-fraud task force have spent recent months promoting efforts to crack down on fraud in the Medicaid and Medicare programs as well as in student loan applications and other areas. Those efforts have also involved using AI technology to flag likely fraud, Federal Trade Commission Chairman Andrew Ferguson said recently on Fox News. States, local governments, nonprofits and higher education institutions that spend at least $1 million in federal money a year are required to submit annual audits. The new initiative will use AI to analyze those audits from HHS-funded programs, including state Medicaid programs and federal grantees in research, addiction services and more, Chiarello said. Recipients that do not file the required reports or resolve problems in them could face a loss of money. Critics have blasted the administration's anti-fraud efforts, noting most have been targeted at Democratic states and at times have reflected a tendency to attack first and gather the facts later. On at least one occasion, the administration acknowledged to The Associated Press that it made a major mistake in data it had used to help justify a New York Medicaid fraud investigation. Asked about safeguards against the AI tools making mistakes, Chiarello noted that officials were evaluating public reports rather than uncovering new information. He said the tools were intended to make grantees better stewards of federal dollars. The department said it has sent letters to governors and treasurers in all 50 states alerting them to the new initiative. The program was first reported by The Wall Street Journal. Chiarello said he has been in touch with his counterparts in other federal departments in hopes that they follow his lead. "It would be fairly easy for the other agencies to use our technology and jump on it," he said.

HHS launches AI initiative to detect fraud and waste in federal health programmes

The Department of Health and Human Services is moving from "pay and chase" to real-time AI screening across Medicare, Medicaid, CHIP and the Marketplace. The US Department of Health and Human Services has launched an artificial intelligence initiative aimed at detecting fraud and waste across federal health programmes, building on a strategy first outlined in February that promises to replace the federal "pay and chase" model with real-time screening of claims before they are paid. Reuters reported the development on Wednesday. The programme covers Medicare, Medicaid, the Children's Health Insurance Programme and the Health Insurance Marketplace, according to the joint HHS announcement from earlier this year. In that February rollout, HHS Secretary Robert F. Kennedy Jr, Vice President JD Vance and CMS Administrator Mehmet Oz framed the shift as moving from a decades-old approach of paying claims first and investigating later to what the agency calls a "detect and deploy" model, using AI tools to flag suspicious claims at the point of adjudication. The numbers behind the push are large enough to explain the urgency. Medicare's fee-for-service programme alone made an estimated $28.83bn in improper payments in fiscal 2025, according to a CMS fact sheet; Medicare Part C added another $23.67bn. A separate Government Accountability Office report in April put government-wide improper payments at roughly $186bn for the year, with the bulk concentrated in five programmes, including Medicare and Medicaid. The regulatory vehicle behind the initiative is a formal Request for Information that HHS and CMS opened in late February, soliciting industry input on analytics methodologies, AI tooling and data-sharing approaches. The RFI closed on 30 March and feeds into a planned proposed rule that CMS has been calling CRUSH, for "Comprehensive Regulations to Uncover Suspicious Healthcare". The May initiative appears to be the operational step that follows from that consultation, although neither HHS nor CMS has yet published the full vendor list or technical architecture behind it. Pilots have been running in parallel. The HHS Office of Inspector General has tested a machine-learning model that scores providers for billing behaviour statistically associated with fraud and abuse, and CMS reported that total Medicare programme-integrity savings rose 59% in fiscal 2025, from $26.3bn the previous year to $41.9bn. The agency attributes part of that jump to enhanced screening of new enrolees, including a six-month nationwide moratorium on new home health and hospice enrolments that took effect on 13 May. The substantive risk in moving from post-payment review to pre-payment AI screening is what false positives do to providers. A flagged claim that delays payment to a legitimate practice, particularly a small one, is a material liquidity event. Industry groups have already pressed CMS, through the RFI process, for clear appeal rights and human review thresholds before any AI-flagged denial becomes final. None of those guardrails have yet been written into rule. What HHS has not disclosed: which model vendors are being used, whether the system will operate on de-identified or fully identifiable claims data, and how the agency will audit the models' own error rates. The CRUSH rulemaking is the document those answers will eventually have to live in. For now, the initiative goes live against a backdrop of unusually large improper-payment numbers and a federal appetite for AI in compliance that is, by recent standards, unusually high.

The Trump Administration Expands Its Use of AI in the Hunt for Healthcare Fraud

NEW YORK (AP) -- The U.S. Department of Health and Human Services on Thursday announced it is supercharging its use of artificial intelligence to police how states and other recipients of federal health dollars are auditing their programs. The move is intended to tamp down risks of fraud and save the government money. The department will use ChatGPT and other AI tools to analyze audit reports from all 50 states on an ongoing basis, said Gustav Chiarello, the assistant secretary for financial resources who is leading the new program. "It's classic big government: Everyone files an audit and it lands with a thud and no one does anything about it," Chiarello said in an interview. "Here, with AI, we're able to dig into it." The move builds on the department's embrace of generative AI for investigating state Medicaid programs, automating administrative tasks and editing text. AI tools can be a powerful aid in finding patterns or problems across large documents, but critics say the government should use them with caution because they frequently make mistakes and can have unintended biases. The Trump administration and Vice President JD Vance's anti-fraud task force have spent recent months promoting efforts to crack down on fraud in the Medicaid and Medicare programs as well as in student loan applications and other areas. Those efforts have also involved using AI technology to flag likely fraud, Federal Trade Commission Chairman Andrew Ferguson said recently on Fox News. States, local governments, nonprofits and higher education institutions that spend at least $1 million in federal money a year are required to submit annual audits. The new initiative will use AI to analyze those audits from HHS-funded programs, including state Medicaid programs and federal grantees in research, addiction services and more, Chiarello said. Recipients that do not file the required reports or resolve problems in them could face a loss of money. Critics have blasted the administration's anti-fraud efforts, noting most have been targeted at Democratic states and at times have reflected a tendency to attack first and gather the facts later. On at least one occasion, the administration acknowledged to The Associated Press that it made a major mistake in data it had used to help justify a New York Medicaid fraud investigation. Asked about safeguards against the AI tools making mistakes, Chiarello noted that officials were evaluating public reports rather than uncovering new information. He said the tools were intended to make grantees better stewards of federal dollars. The department said it has sent letters to governors and treasurers in all 50 states alerting them to the new initiative. The program was first reported by The Wall Street Journal. Chiarello said he has been in touch with his counterparts in other federal departments in hopes that they follow his lead. "It would be fairly easy for the other agencies to use our technology and jump on it," he said.

US HHS Launches AI Initiative to Detect Fraud and Waste in Health Programs

May 21 (Reuters) - The U.S. Department ⁠of ⁠Health and Human Services ⁠said on Thursday it has launched a new AI-led initiative to review annual audits to strengthen oversight across federally funded health programs amid concerns around widespread fraud. The program, called ⁠the Audit ⁠Enforcement and Risk Oversight initiative, or AERO, will review at least five years of audit records of HHS-funded programs across all 50 states, the department said. The move comes after the Trump administration in March launched a national anti-fraud ⁠task ⁠force led by Vice ⁠President JD Vance that aims to crack down on healthcare scams. The administration said earlier ⁠this month it will block new home healthcare and hospice providers from enrolling in Medicare for at least the next six months, citing concerns about fraudulent practices. HHS ⁠said hundreds of grantees have not submitted their required audits, ⁠with some late by more than two years. The agency said it will work collaboratively with states and grantees to address audit findings and strengthen internal controls, and may take measures such as temporarily withholding payments, cutting off grants entirely, or withholding future funds from recipients that fail to resolve ⁠the issues. Under federal law, non-federal entities, including states, local governments, nonprofits, and higher education institutions, that spend at least $1 million annually in federal funds are subject to audit requirements. (Reporting by Padmanabhan Ananthan in Bengaluru; Editing by Shailesh Kuber)