CMS launches ‘chili cook-off’ AI competition to tackle Medicare fraud
CMS has rolled out the “Crushing Fraud Chili Cook‑Off Competition,” a market-based research challenge seeking explainable AI and machine learning to detect Medicare fraud, waste and abuse.
The challenge also seeks innovative, scalable technologies that reduce labor-intensive processes “while keeping humans meaningfully in the loop to ensure effective oversight and interpretability.”
CMS said that pattern detection alone is not sufficient to determine fraud, underscoring the need to understand the underlying factors driving suspicious activity.
“By making insights transparent and accessible to program integrity teams, regulators, and policy makers, explainable AI/ML enhances trust in the system, supports human-in-the-loop oversight on critical decisions, and enables fair and accountable enforcement actions,” CMS said. “Ultimately, integrating explainable AI/ML into fraud prevention efforts helps shift Medicare oversight from reactive to proactive—empowering agencies to identify suspicious behavior early and take timely, informed action to protect public resources.
The competition will take place in two phases. In the first, CMS is accepting proposals tailored to Medicare fee-for-service claims through Sept. 19. Ten finalists will be selected to advance. Beginning Oct. 30, those teams will gain access to 2022–2024 Medicare Fee-for-Service hospice, Part B and durable medical equipment claims data through Limited Data Sets. Finalists will apply their models, submit analyses and propose policy recommendations.
CMS said it will publicly recognize the finalists and announce the winner Dec. 15 on its social media channels.
Read more about the challenge here.
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