On January 14, 2026, the Department of Justice announced that five Kaiser Permanente affiliates had agreed to pay $556 million to resolve False Claims Act allegations that they submitted unsupported diagnosis codes for Medicare Advantage enrollees to inflate reimbursements from the federal government. The settlement is the largest False Claims Act resolution involving Medicare Advantage risk adjustment fraud in history. Whistleblowers who brought the case received a share of the recovery.
The conduct at the center of the Kaiser case involved using data mining tools and algorithmic record queries to surface diagnoses that were never clinically established. The Department of Justice has identified this type of fraud as one of its top enforcement priorities. As artificial intelligence becomes a standard part of healthcare operations, it is also becoming a vehicle for fraud.
How Medicare Advantage Risk Adjustment Works, and How It Gets Abused
Medicare Advantage is the privatized version of Medicare, through which the federal government pays private insurance companies a fixed monthly amount to manage the care of enrolled beneficiaries. That payment is adjusted based on how sick each enrollee is; the more severe and complex a member’s documented diagnoses, the higher the monthly payment the plan receives from the Centers for Medicare and Medicaid Services (CMS).
This payment structure creates a financial incentive for plans to find and report as many diagnoses as possible for their members. The practice of exaggerating a member’s health status to receive a higher risk-adjusted payment is known as upcoding, which results in billions of dollars in overpayments annually.
What the Kaiser Permanente Case Alleged
The government alleged that Kaiser developed automated mechanisms to identify diagnoses that had not been previously submitted and then sent queries to physicians encouraging them to add those diagnoses to patient records, sometimes months or more than a year after the actual patient visit. According to the DOJ, these practices generated approximately $1 billion in unsupported payments from CMS associated with nearly 500,000 diagnoses added through record addenda.
The case began as a series of qui tam lawsuits filed under the False Claims Act. The DOJ partially intervened in 2021, and the parties reached the $556 million settlement in January 2026 after years of litigation.
The Kaiser settlement did not stand alone. In 2025, Aetna paid $117.7 million to resolve allegations that it submitted inaccurate diagnosis codes for Medicare Advantage enrollees, including morbid obesity diagnoses that coders and auditors knew were not supported by the clinical record. That case also arose from a whistleblower. Earlier in 2025, Independent Health paid $98 million to settle similar allegations, with the government accusing the plan of using a coding subsidiary that was paid a percentage of any additional reimbursement it was able to generate by identifying additional unsupported diagnoses.
How AI Is Being Used to Commit Healthcare Fraud
As AI capabilities have expanded across the healthcare industry, everyone should recognize that AI-assisted fraud carries the same False Claims Act exposure as any other form of Medicare fraud. The DOJ and HHS have jointly flagged the manipulation of electronic health record systems, including prompts generated by AI algorithms, as a priority enforcement area.
AI-enabled fraud patterns the government has been tracking include the following:
- AI-driven diagnosis mining: Plans and their vendors use algorithms to comb through electronic health records to find additional diagnoses not identified or documented by the treating physician, then submit those codes to CMS for higher payments. If those diagnoses are not properly documented and supported by the clinical record, the resulting submissions are false claims.
- Automated upcoding: Natural language processing tools can scan medical records and assign billing codes without adequate physician review. When those tools select codes that overstate the severity of a patient’s condition, the claims submitted to Medicare are false.
- AI-generated prompts to physicians: Some platforms generate automated prompts within the electronic health record, directing physicians to add diagnoses or document conditions in ways that trigger higher reimbursements. When those prompts are designed to generate revenue rather than reflect genuine clinical judgment, the resulting submissions may violate the False Claims Act.
- Retrospective chart reviews without correction: Plans that commission retrospective chart reviews to find additional diagnoses, but fail to delete unsupported codes identified through those reviews, are engaging in the one-way conduct the government has repeatedly pursued in enforcement actions. Failure to delete identified unsupported diagnosis codes within the risk adjustment system may violate the False Claims Act.
Who Should Report AI-Assisted Medicare Fraud?
Medicare fraud enabled by AI tools is not always visible from the outside. The people most likely to recognize it are those working inside the organizations that deploy these systems. This could include:
- Coding auditors and risk adjustment specialists who know that diagnosis codes are being added or retained without adequate clinical support.
- Physicians and clinical staff who receive AI-generated prompts to add diagnoses they did not establish and have not verified.
- Compliance officers, data scientists, and technology staff who understand how an AI tool is configured and can see the gap between what the tool is designed to do and what the medical record actually supports.
- Employees at third-party coding vendors or chart review companies who see their work being used to inflate risk scores rather than ensure accuracy.
The whistleblowers in the Kaiser and Aetna cases were healthcare insiders who had direct knowledge of what was happening at their organizations. Under the False Claims Act‘s qui tam provisions, they were able to file lawsuits on behalf of the government and receive a portion of what the government recovered.
Speak with a Whistleblower Attorney
If you have knowledge of an employer or business partner using AI tools to inflate Medicare diagnoses, manipulate risk scores, or submit unsupported billing codes to CMS, you may be entitled to file a qui tam complaint and receive a portion of the government’s recovery. Federal law protects you from retaliation for coming forward.
The whistleblower attorneys at Keller Grover represent clients in False Claims Act cases involving healthcare fraud and Medicare billing misconduct. Contact our legal team today for a free, confidential consultation to discuss what you know and understand your rights as a potential whistleblower.