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Medicare Expands Analytic Tools To Fight Fraud

The Centers for Medicare and Medicaid Services will use predictive modeling to identify fraudulent billings before they are paid.

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The Centers for Medicare and Medicaid Services (CMS) will acquire new analytic tools to help identify unusual patterns of payment and track fraudulent behavior as the agency continues its efforts to fight corruption in Medicare, Medicaid, and the Children's Health Insurance Program (CHIP).

Department of Health and Human Services (HHS) secretary Kathleen Sebelius and attorney general Eric Holder made the announcement Thursday at the University of Massachusetts, Boston, at a regional healthcare fraud prevention summit.

As part of the summit, CMS issued a solicitation for state-of-the-art, fraud-fighting analytic tools to help the agency predict and prevent potentially wasteful, abusive, or fraudulent payments before they occur. These tools will integrate many of the agency's pilot programs into the National Fraud Prevention Program and complement the work of the joint HHS and Department of Justice Health Care Fraud Prevention and Enforcement Action Team (HEAT).

"Preventing fraud is more effective than the old 'pay and chase' model of fighting fraud after a sham provider has been paid and disappeared," CMS administrator Donald Berwick said in a statement. "By using new predictive modeling analytic tools we are better able to expand our efforts to save the millions -- and possibly billions -- of dollars wasted on waste, fraud, and abuse."

Predictive modeling tools are used by banks, credit card companies, insurance firms, and other industries to identify potential fraud before it occurs. CMS is actively exploring using similar systems to identify background information on potential fraudulent people and links to questionable affiliations.

This type of information is intended to help prevent bad actors from enrolling as healthcare providers or suppliers for the sole purpose of defrauding the healthcare system. Other tools will track billing patterns and other information to identify real-time aberrant trends that are indicative of fraud, HHS officials said.

"This has been a remarkable year for cracking down on healthcare fraud -- and our success has been built on initiatives like these combining the experience and insight of our law enforcement teams with new resources and cutting-edge technology," Sebelius said in a statement. "Thanks to the new tools and resources provided under the Affordable Care Act, we are more effective at going after the fraudsters that are stealing taxpayer dollars."

CMS, like other healthcare payers, will use the results to take anti-fraud actions before a claim is paid. CMS has already begun to take administrative action to stop payments to "false fronts" in Texas identified through sophisticated predictive modeling. In addition, CMS is implementing new and expanded authority provided in the Affordable Care Act to take such actions, including suspending payments when investigating a credible allegation of fraud.

"Using the most up-to-date technologies and adopting best practices across the nation's healthcare system, we have a better chance of finding fraudulent and abusive providers before they even start billing Medicare or other health insurance," Peter Budetti, director of CMS' Center for Program Integrity, said in a statement.

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