06/16/2026
This month, when federal and state officials announced new data-sharing agreements to fight Medicaid fraud, one line from Acting Attorney General Todd Blanche stood out: "You can tell by the data which ones are legitimate."
Fraud detection, payment integrity, and program oversight all rest on a single assumption — that the underlying data is accurate, structured, and trustworthy.
But healthcare data rarely arrives that way. It's fragmented across systems, captured in inconsistent terminology, and full of gaps that make even well-intentioned analysis unreliable.
You can't separate legitimate claims from suspicious ones if the data feeding your models is messy.
This is the work we focus on at IMO Health: turning messy, disconnected clinical documentation into clean, AI-ready data that systems and regulators can trust. Before we ask algorithms to find fraud, surface risk, or validate coding, we have to get the data right.
Integrity starts with the data. Everything else builds on it.
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Ohio and Indiana have new data-sharing agreements with the U.S. Department of Justice and the Centers for Medicare & Medicaid, say acting U.S. Attorney General Todd Blanche and CMS Administrator Dr. Mehmet Oz.
