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North Carolina uses predictive analytics to identify millions in Medicaid fraud

North Carolina's Dept. of Health and Human Services has been investigating Medicaid fraud using IBM's predictive analytics software, and in the first phase of the initiative has already turned up $6.2M in potentially fraudulent payments, as well as another $191M of "unusual" Medicaid charges.

The state is using IBM Fraud and Abuse Management System (FAMS) and IBM InfoSphere Identify Insight to find suspicious billing patterns in claims from nearly 2 million Medicaid patients filed by 60,000 providers.

As shared in eWeek:

"The beauty of this system is that it recognizes patterns of billing behavior that don't fit in with the norm—and then takes it a step further by looking for relationships among providers that can point us to a Web of suspicious accounts," Al Delia, North Carolina DHHS acting secretary, wrote in an IBM blog post.

Meanwhile, InfoSphere Identity Insight allows organizations to resolve identity conflicts and determine if providers are using different names on billing statements, said [IBM's Shaun] Barry.

Similar to the Watson computer that competed on Jeopardy last year, the fraud detection application is able to "learn" as it goes, allowing it to increase the effectiveness of its detection as more data is analyzed.  "As cases and data are processed, the system is storing certain patterns of behavior that have a high probability of fraud," said Barry. "This improves its ability to find similar cases as new data is fed to the system."

As for results, they are looking pretty impressive already:

DHHS searched three years of claims data during the first phase of its inquiry, the state reported. It has completed 10 investigations of outpatient behavioral health, and it discovered $6.2 million in potentially fraudulent payments, according to DHHS.

In addition, 206 outpatient behavioral health providers across the state may have charged "unusual" Medicaid billing worth up to $191 million, the state reported.