GOP senators call on CMS to provide Fraud Prevention System data

A calculator up close

Underscoring concerns that the government still isn’t doing enough to prevent improper Medicare payments, seven GOP senators have requested detailed information on the types of fraud cases referred to investigators through the Fraud Prevention System (FPS).

In a letter addressed to Centers for Medicare & Medicaid Services Acting Administrator Andrew Slavitt, the senators--all of whom chair various committees and subcommittees--requested a categorized list of fraud schemes referred to Zone Program Integrity Contractors by the FPS system over the last three years. They specifically requested data related to the type of fraud schemes uncovered or assisted by FPS, along with detailed dollar amounts and actions taken against providers.

The group also requested CMS calculate the percentage of investigations that were initiated or supported by FPS leads, any subsequent claim edits that were implemented to prevent future fraudulent claims and a description of how CMS reviews the effectiveness of FPS models. The legislators requested the information by Sept. 26. 

“We remain supportive of CMS’ efforts to implement the FPS, but are concerned that the FPS continues to rely primarily on outdated ‘pay and chase’ activities rather than focusing on preventing potentially fraudulent dollars from going out in the first place,” the letter states.

As of last year, Medicare’s improper payment rate stood at 12.1 percent exceeding the Department of Health and Human Services’ goal of less than 10 percent.

However, FPS statistics have varied. Earlier this year, CMS said the system saved more than $1 billion in the last two years, bringing its total to $1.5 billion over three years, and that overall fraud prevention efforts had saved $42 billion over a two-year period.  But an Office of Inspector General review attributed just $133 million in actual and projected savings to the FPS in 2014, echoing concerns about how cost-savings data is attributed to the new predictive analytics system.

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