CMS Launches New Tool to Combat Medical Fraud

The Department of Health and Human Services Centers for Medicare &
Medicaid Services (CMS) recently began using an innovative predictive modeling
technology, similar to those used by various credit card companies, to fight
Medicare fraud.

Predictive modeling helps identify potentially fraudulent Medicare
claims on a nationwide basis and helps stop fraudulent claims before they are

“Predictive modeling is a revolutionary new way to detect fraud and
abuse, while minimizing burden on good actors, by integrating effective and
timely actions with protections and savings for Medicare and taxpayers,”
said Peter Budetti, JD, MD, deputy administrator and director at the Center for
Program Integrity.

According to Budetti, each workday, Medicare pays more than $1 billion
from 4.5 million claims and is required to pay claims within 30 days.

“There is a need for innovative methods that will enable us to
identify suspicious billing patterns before we pay the claims,” Budetti
told O&P Business News.

CMS issued a press release stating that this initiative builds on the
new antifraud 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.

CMS Administrator Donald Berwick, MD, said this announcement is
“bad news for criminals looking to take advantage of our seniors and
defraud Medicare. 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 predictive models. 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,
was selected to develop CMS’s national predictive model technology format
using best practices of both public and private stakeholders. The company 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 “alerts” and “risk scores”
for those claims. These will be reviewed to allow CMS to prioritize claims and
assess the need for investigative or other enforcement actions.

“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,” Budetti said in a press release.

Wendy Beattie, CPO, FAAOP, of Becker Orthopedic
Appliance Co. in Waterford, Mich., and a member of the Government Relations
Committee of the American Academy of Orthotists & Prosthetists, commented
that while this new technology may help CMS from having to pay fraudulent
claims, which all “law-abiding orthotists and prosthetists care providers
applaud,” it is still upsetting that these steps need to be implemented in
the first place because of the rampant fraud of those nontraditional care

Beattie has heard reports that as high as 10% of Medicare payments are

“As we have seen with the recent scandals in Florida and Texas, the
overwhelming majority, if not all, of the fraud perpetrated by
‘O&P’ providers has not been by those licensed or accredited, but
by individuals and groups not in the field, who are bilking the system solely
for personal gain,” she told O&P Business News. “Thus, Medicare
could cut down on fraud by simply not paying nonaccredited providers. This
would also prevent the ‘pay and chase’ scenario.”

Beattie is also concerned about the impact this new predictive
modeling technology may have on legitimate orthotists’ and
prosthetists’ care and its accuracy.

Budetti stands behind this new system, stating that CMS believes it is
great news for licensed and accredited providers.

“It is designed to target suspect characteristics and sets
priorities for further investigation based on the cumulative result of
suspicious patterns,” he said. “Additionally, providers will be
afforded all traditional appeal rights if any administrative actions are
taken.” — by Tara Grassia

For more information:

To read additional information on the predictive modeling, visit:

Disclosure: Beattie has no disclosures to announce.

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