Trump administration expands its use of AI to hunt for healthcare fraud across federal programs

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The Department of Health and Human Services announced a new AI-powered initiative to detect fraud and waste in health programs across all 50 states. The AERO program will use ChatGPT and other AI tools to analyze years of audit reports from Medicaid, Medicare, and federal grantees, marking a shift from reactive oversight to real-time screening of billions in federal health spending.

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

The Department of Health and Human Services announced Thursday it is deploying artificial intelligence to intensify oversight of how states and federal fund recipients audit their programs, aiming to combat fraud and waste across billions in healthcare spending

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. The new program, called the Audit Enforcement and Risk Oversight initiative, or AERO, will use ChatGPT and other AI tools to analyze audit reports from all 50 states on an ongoing basis

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. Gustav Chiarello, the assistant secretary for financial resources leading the initiative, explained that the traditional approach has been ineffective: "It's classic big government: Everyone files an audit and it lands with a thud and no one does anything about it. Here, with artificial intelligence, we're able to dig into it"

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Source: AP

Source: AP

Trump Administration Expands Its Use of AI Across Federal Health Programs

The initiative builds on broader efforts by the Trump administration and Vice President JD Vance's anti-fraud task force to crack down on healthcare fraud in the Medicaid and Medicare programs

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. The program covers Medicare, Medicaid, the Children's Health Insurance Programme and the Health Insurance Marketplace, representing a shift from the federal "pay and chase" model to real-time screening of claims before they are paid

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. The scale of the problem is substantial: Medicare's fee-for-service programme alone made an estimated $28.83bn in improper payments in fiscal 2025, with Medicare Part C adding another $23.67bn

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. A 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

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How AI Will Analyze Audit Reports to Detect Fraud

Under federal law, states, local governments, nonprofits, and higher education institutions that spend at least $1 million in federal funds annually are required to submit annual audits

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. The AERO program will review at least five years of audit records of HHS-funded programs, including state Medicaid programs and federal grantees in research, addiction services and more. HHS said hundreds of grantees have not submitted their required audits, with some late by more than two years

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. Recipients that do not file the required reports or resolve problems in them could face a loss of funding, with HHS potentially taking measures such as temporarily withholding payments, cutting off grants entirely, or withholding future funds

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Concerns About AI Errors and Biases in Healthcare Fraud Detection

While AI tools can be a powerful aid in finding patterns or problems across large documents, critics say the government should use them with caution because they frequently make mistakes and can have unintended biases

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. 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

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. 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

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. Rob Weissman, co-president of the consumer rights advocacy group Public Citizen, said he doesn't think the administration is seriously concerned about healthcare fraud, and doesn't trust it to use AI tools in a fair and nonpartisan way

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What This Means for Federal Health Programs and Providers

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

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. Industry groups have already pressed CMS for clear appeal rights and human review thresholds before any AI-flagged denial becomes final, but none of those guardrails have yet been written into rule

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. When asked about safeguards against the AI tools making mistakes, Chiarello noted that officials were evaluating public reports rather than uncovering new information, and said the tools were intended to make grantees better stewards of federal dollars

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. HHS has sent letters to governors and treasurers in all 50 states alerting them to the new initiative, with one letter stating that "HHS will no longer treat chronic audit noncompliance, repeat deficiencies, material weaknesses, or delinquent audit obligations as matters that may remain unresolved through indefinite informal follow-up"

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. Chiarello said he has been in touch with his counterparts in other federal departments in hopes that they follow his lead, noting "it would be fairly easy for the other agencies to use our technology and jump on it"

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