CMS snags $42 billion in Medicare and Medicaid fraud with predictive analytics

The agency used advanced analytics, partnered with law enforcement, instituted more stringent screening practices and moved away from its so-called pay-and-chase method to save billion of dollars. 
By Jack McCarthy
12:29 PM
CMS fraud analytics

The Centers for Medicare and Medicaid reported that it has saved nearly $42 billion in fraudulent and improper Medicare and Medicaid payments.

The savings amount to an average of $12.40 for each dollar spent on Medicare program integrity activities, Shantanu Agrawal, MD, Deputy Administrator and Director, Center for Program Integrity, wrote in a CMS blog.

To attain these savings, CMS acted on several fronts, ranging from instituting increased provider enrollment and screening standards, partnering with law enforcement authorities, and using advanced analytics, such as predictive modeling.

[Also: Buyers Guide to intrusion detection and prevention tools]

To enhance its effectiveness at preventing potentially fraudulent and improper payments, CMS has moved away from the “pay-and-chase” method of recovering payments after they had already been made. 

In fiscal year 2013, savings from prevention activities represented about 68 percent of total savings. In fiscal year 2014, the portion of savings from preventing potentially fraudulent and improper payments rose to nearly 74 percent. 

“This means that all our efforts – making sure health care providers enrolled in our programs are properly screened; using predictive analytics to prevent fraud, waste, and abuse; and  coordinating our anti-fraud efforts with our federal and external partners – have resulted in billions of dollars saved in Medicare and Medicaid over the two-year period,” Agrawal wrote.

CMS is assisted by contractors, state Medicaid agencies, and law enforcement partners.

Twitter: @HealthITNews


Like Healthcare IT News on Facebook and LinkedIn

Want to get more stories like this one? Get daily news updates from Healthcare IT News.
Your subscription has been saved.
Something went wrong. Please try again.