NEW TECHNOLOGY TO HELP FIGHT MEDICARE FRAUD
Technology is Similar to Tools Used by Credit Card Companies, Builds on White House Campaign to Cut Waste
On the heels of the White House launch of the Campaign to Cut Waste - an administration wide initiative to crack down on waste, fraud and abuse, the Centers for Medicare & Medicaid Services (CMS) announced today that starting July 1, it will begin using innovative predictive modeling technology to fight Medicare fraud. Similar to technology used by credit card companies, predictive modeling helps identify potentially fraudulent Medicare claims on a nationwide basis, and help stop fraudulent claims before they are paid. This initiative builds on the new anti-fraud tools and resources provided by the Affordable Care Act that are helping move CMS beyond its former “pay & chase” recovery operations to an approach that focuses on preventing fraud and abuse before payment is made.
“President Obama is committed to hunting down and eliminating waste, fraud and abuse throughout the federal government,” said HHS Secretary Kathleen Sebelius. “Our work to fight Medicare fraud is an important part of the Obama Administration’s effort to root out wasteful spending and change the way government does business.”
“Today’s announcement is bad news for criminals looking to take advantage of our seniors and defraud Medicare,” said CMS Administrator Donald Berwick, M.D. “This new technology will help us better identify and prevent fraud and abuse before it happens and helps to ensure the solvency of the Medicare Trust Fund.”
Original Medicare claims will be analyzed using innovative risk scoring technology that applies effective predictive models, an approach similar to that used by the private sector to successfully identify fraud. For the first time, CMS will have the ability to use real-time data to spot suspect claims and providers and take action to stop fraudulent payments before they are paid.
Northrop Grumman, a global provider of advanced information solutions, has been selected through a competitive procurement to develop CMS’ national predictive model technology format using best practices of both public and private stakeholders. Northrop Grumman has partnered with National Government Services (NGS) and Federal Network Systems, LLC, a Verizon company (FNS), to leverage the wealth of claims data and its information to fight health care fraud. CMS used industry guidance, innovative ideas from private and provider entities and related data in developing the scope of work for this national fraud prevention program. Given the importance of this contract to CMS’ overall anti-fraud efforts, this contract is being implemented nationally and ahead of schedule.
“CMS has worked with public and private stakeholders throughout the process of developing this program, and the key insight they shared on their successes and innovations have helped ensure it will significantly help us address fraud in the Medicare program,” said Peter Budetti, M.D, J.D., director of CMS’ Center for Program Integrity (CPI).
Northrop Grumman, through the use of proven predictive models and other advanced analytics, will move rapidly to implement the new technology. Northrop Grumman will deploy algorithms and an analytical process that looks at CMS claims – by beneficiary, provider, service origin or other patterns — to identify potential problems and assign an “alert” and assign “risk scores” for those claims. These problem alerts will be further reviewed to allow CMS to both prioritize claims for additional review and assess the need for investigative or other enforcement actions.
“Predictive modeling is a revolutionary new way to detect fraud and abuse, integrating effective and timely actions with protections and savings for Medicare and taxpayers,” Dr. Budetti said.
More information on the predictive modeling and HHS’ effort to detect fraud and abuse are available www.HealthCare.gov/news/factsheets/fraud03152011a.html and through its news portal at www.HealthCare.gov, made available by the US Department of Health and Human Services.