Technology can Dramatically Reduce Billions of Dollars in Medicaid, Medi...( System Detects Illegal...),Health

System Detects Illegal Payments and Providers

AUSTIN, Texas, Dec. 12 /PRNewswire/ -- According to the federal government and an NBC News report, U.S. taxpayers are annually defrauded of about $60 billion in Medicare payments to unqualified doctors and health care providers. A new system developed by S3 Matching Technologies of Austin, Texas, however, can make a significant impact on reducing Medicare and Medicaid fraud with algorithmic data matching. Using the company's patented TeraMatch(R) technology, S3's system matches numerous fields from huge databases and finds minute variances that can often reveal fraud by unqualified providers.

"Our technology looks at data in almost the same way a human would," said Jack Holt, CEO of S3. "The data matching algorithms make matches based upon probabilities that two similar things are actually the same thing. This is about as close as you can come to getting a computer to think for you."

According to Holt, S3's Medicaid fraud detection software has already begun to make an impact for Texas Medicaid Healthcare Partners (TMHP). Prior to using TeraMatch(R), TMHP employees had to visually scan five different data lists from state and federal agencies. They used simple, commercial programs like EXCEL or MS ACCESS to search for doctors or providers who are not supposed to be receiving payments. Findings were based on the either-or principles of deterministic matching, which does not allow for subtle differences in data. The work was tedious and difficult until the implementation of TeraMatch(R).

"TMHP tracks hundreds of thousands of providers to make certain the right people are being paid," said Rick Pope, Managing Director of TMHP. "S3 has given us a tool that dramatically reduces risk and can potentially increase the level of confidence that beneficiaries are receiving health care from qualified providers."

TeraMatch(R) takes each bit of information on any kind of data record
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