Using Analytics to Root Out Fraud
The Office of Inspector General at HHS is responsible for preserving the integrity of federal healthcare programmes. To help root out fraud and abuse in relation to these programmes, the OIG has increasingly relied on data analytics.
With the use of analytics, investigators were able to uncover their biggest fraud scheme to date last year, charging three individuals in a scheme worth an estimated $1 billion. One of those individuals is nursing home tycoon Philip Esformes. 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.
“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,” said Caryl Brzymialkiewicz, chief data officer at the HHS OIG.
Pairing data analytics with the Centers for Medicare and Medicaid Service’s (CMS) massive payment database provides arm fraud prosecutors and investigators with a meaningful tool that could augment field intelligence.
“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,” Brzymialkiewicz pointed out.
Now the OIG is working on categorising the massive data sets within CMS to focus on specific concerns, like opioid prescribing, and spotlight areas where programme vulnerabilities allow bad actors to take advantage of the system. The analytics team at the OIG, Brzymialkiewicz said, 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.
Source: Fierce Healthcare
Image Credit: Pixabay
Published on : Tue, 2 May 2017
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