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Senators Push CMS for Better Use of Medicare Fraud Detection System

November 16, 2012
by Gabriel Perna
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Recently Sens. Tom Carper (D-Del.), Tom Coburn (R-Okla.), and Scott Brown (R-Mass.) are highlighting a report from the Government Accountability Office (GAO) that reviews a new data analytics technique used by the Centers for Medicare and Medicaid Services (CMS) to detect and curb Medicare waste and fraud. The system, established as part of the Small Business Act of 2011, is not fully integrated by the CMS, the GAO report found, which recommended it be deployed in total by January.

"Clearly, the new fraud analysis system is a tool with enormous potential for fighting Medicare waste and fraud," Sen. Carper, Chairman of the Subcommittee of Federal Financial Management said in a statement. "Medicare officials have correctly embraced this critical approach for stopping fraud before it happens.”

He goes on to say that because there is a large magnitude of Medicare waste and fraud, the CMS should do more to capitalize on this winning strategy. “Congress directed Medicare officials to utilize this new anti-fraud technology as a way to prevent fraud, not just find out about fraud once it is committed,” he said. “This Government Accountability Office report shows that the new system's preventative abilities are not yet fully deployed, making proper detection and prevention more challenging than it needs to be. I am counting on Medicare officials to get the system fully up and running as promised."

"Unfortunately, GAO has found that even after spending $77 million on the program CMS has no idea whether it is saving money or preventing fraud," Senator Tom Coburn, M.D., said in a statement "It's troubling CMS has no metrics, timeframes, measures or other indicators in place to assess the program's effectiveness." 

According to the report, technology similar to the Fraud Prevention System is employed in the private sector.  The new Medicare anti-fraud system uses "predictive analytics," which relies on models of fraudulent behavior in order to generate automated alerts on specific Medicare claims and providers.

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