Some states are turning to data mining, a method of finding patterns in large amounts of data, to prevent whistleblowers from swaying False Claims Act cases, one expert shared last week.

Thomas F. Corcoran, an attorney for the District of Maryland, told attendees at an American Health Lawyers Association conference that some U.S. attorney’s offices were using data mining to “take control” of healthcare fraud cases, Bloomberg BNA reported. Maryland began using data mining since it no longer wanted whistleblowers to “determine the direction of our FCA cases,” he said.

Data mining also helped Maryland authorities hone in on cases in their state alone, instead of whistleblower cases that often stretch across state lines, Corcoran noted. Providers who bill certain codes together, use particular modifiers and have long stretches of time between service and claims are among the red flags looked for by authorities who use data mining.

“The data has been really helpful, and shame on us for not looking at it sooner,” Corcoran said.

At the same conference, officials with the Department of Health and Human Services Office of Inspector General shared their renewed emphasis on pursuing FCA cases where individuals are held accountable for fraud, rather than only obtaining money damages from corporations. That stance was proposed by Deputy Attorney General Sally Quillian Yates in September, in order to encourage providers to self-disclose more and foster collaboration between civil and criminal prosecutors.