Medicare waste, fraud being detected by FAU computers

Oct. 31--Researchers from Florida Atlantic University in Boca Raton are teaching computers to detect Medicare waste and fraud.

In a recently published study, FAU's College of Engineering and Computer Science examined Medicare Part B data sets, a total of 37 million cases from 2012 to 2015. Researchers identified a process to map fraudulent activities, which include patient abuse or neglect as well as billing for services not rendered.

The 37 million cases were aggregated down to about 3.7 million cases. Out of those, 1,400 physicians were classified as fraudulent by the government.

"If we can predict a physician's specialty accurately based on our statistical analyses, then we could potentially find unusual physician behaviors and flag these as possible fraud for further investigation," said Taghi Khoshgoftaar, co-author of the study and Motorola professor in FAU's Department of Computer and Electrical Engineering and Computer Science.

Richard Bauder, a doctoral candidate at FAU and a data scientist at Florida Power & Light Co. who also co-authored the study, said it can be difficult for human auditors to distinguish fraud from other elements such as clerical error.

"Our goal is to enable machine learners to cull through all of this data and flag anything suspicious. Then, we can alert investigators and auditors who will only have to focus on 50 cases instead of 500 cases or more," Bauder said.

Matthew Herland, doctorate student in FAU's Department of Computer and Electrical Engineering and Computer Science, also contributed to the study, which was published in the journal, "Health Information Science and Systems."

Medicare serves about 56 million people, including those age 65 and older and disabled people of any age. The improper payment rate was 10 percent in 2016, which comes to $16.2 billion, according to a 2017 story by Kaiser Health News, a nonprofit health news organization.

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