The Department of Health and Human Services has proposed that state Medicaid agencies use federal funds to help pay for uncovering fraud through the screening and analysis of Medicaid claims data.

Data mining is one of the tools that contributed to the $355 million in court-ordered restitutions, fines and penalties and convictions for fraud against Medicare since 2007.

[See also: Anti-fraud efforts save CMS $4B in 2010.]

Increasing data mining at the state level could enhance the ability of Medicaid fraud control units (MFCU) to counter new and existing fraud schemes by more effectively identifying early fraud indicators.

Data mining electronically sorts Medicaid claims through statistical models and intelligent technologies to expose suspicious patterns and relationships. Tools and methods have advanced significantly and are in wide use.

“Data mining would equip MFCUs with more modern tools that have been shown at the federal level to help increase the numbers of credible investigative leads, pursue recoveries and detect emerging fraud and abuse schemes and trends,” HHS said.

[See also: CMS turns to analytics to fight fraud.]

Until now, HHS has prohibited the use of federal matching funds for data mining by state Medicaid fraud control units, and states have absorbed all the costs for the highly technical practice of identifying fraud, according to a proposed rule published in the March 17 Federal Register.

To support its reversal in payment policy, HHS cited increased use of claims data analysis in Medicare in coordination with the Justice Department for enforcement, including identifying seven “hot spots” based on high indicators of fraud against the Medicare program.
 
To receive federal reimbursement, state Medicaid fraud units would report on data mining activities; the number of cases that the activities generated; the outcome of the cases and the amount of money that was recovered as a result.

The public may comment on the proposed rule through May 16.