OIG’s chief data officer explains how analytics uncovered a $1B fraud scheme

Special report: Homegrown fraud task forces promote collaboration
The OIG's chief data officer says if analytics doesn't help agents make their case, "then we've failed them."

To hear one Department of Health and Human Services senior official tell it, a $1 billion Medicare fraud scheme was “hiding in the data.” All it took was some targeted analytics to tease it out.

Over the last several years, the Office of Inspector General at HHS—tasked with preserving the integrity of federal health care programs—has been increasingly reliant on data analytics to root out fraud, waste and abuse. That emphasis on analytics paid off when investigators busted open their biggest fraud scheme to date last year, charging three individuals in a scheme worth an estimated $1 billion.

One of those individuals, nursing home tycoon Philip Esformes, made FierceHealthcare’s list of most notorious healthcare executives in 2016. Earlier this year, prosecutors added bribery to his list of charges, accusing Esformes of paying a Florida official to obtain patient complaints and inspection schedules.

RELATED: Special report—11 notorious healthcare leaders in 2016

“It was really about using data analytics and partnering with DOJ and the FBI to uncover money laundering and to understand in the data what was happening,” Caryl Brzymialkiewicz, chief data officer at the HHS OIG said during an event hosted by Cloudera.

The work that went into that massive fraud bust was a moment clarity for Brzymialkiewicz who saw the impact of pairing data analytics with the Centers for Medicare and Medicaid Service’s (CMS) massive payment database to arm fraud prosecutors and investigators with a meaningful tool that could augment field intelligence.

Related: Data drives historic fraud takedown

In that sense, the analytics department at the OIG is highly attuned to the customer experience. In this case, their customers happen to be federal agents and prosecutors.

“If the team is pulling together all this robust analysis and then we’re not figuring out a way to enable agents to talk to prosecutors so they can convince a jury, then we’ve failed them,” she said. “For me, the surprising part was how easily people can look at data in different ways if you give them the right tools and ask the right questions so they can tell that story. All of this is about the ‘so what?’ of the data.”

Now the OIG is focusing on categorizing the massive data sets within CMS to focus on specific concerns, like opioid prescribing, and spotlight areas where program vulnerabilities allow bad actors to take advantage of the system. Brzymialkiewicz said the analytics team is mirroring the approach it used in the $1 billion fraud case by using data to tell a story that helps law enforcement detect drug abuse and diversion.