NIH-backed startup uses machine learning to catch opioid, drug theft

NIH-backed startup uses machine learning to catch opioid, drug theft

Healthcare inventory visibility and analytics specialist Invistics launched a machine learning-based platform for monitoring drug diversion.


The Drug Enforcement Administration (DEA) compliant software platform provides hospitals with access to the analytics and for detecting and stopping drug diversion.

Backed by the National Institutes of Health, the software helps eliminate paper from controlled substance tracking programs.

“As many as ten percent of healthcare workers divert from their workplace, and most of these instances of theft go unreported,” Tom Knight, CEO of Invistics, said in a statement. “This is a serious issue for our healthcare systems, jeopardizing patient safety, and leading to large DEA fines for non-compliance.”

Knight said the goal is to solve that problem in a scalable way, with machine learning helping to detect drug diversion that would have not otherwise been detected.


The federal government and private sector have both been working to apply technology to the ongoing opioid epidemic, including cutting edge tools such as artificial intelligence, advanced analytics, and policy. 


“This is the first time a drug diversion solution has been offered by a company that doesn’t sell hardware, such as automated dispensing cabinets or surgical kitting equipment, or that doesn’t expect you to buy their hardware,” Knight said. “That is critical when analyzing these big data sets – the more providers we can work with, the more data we can use to establish drug diversion intelligence.”


Invistics’ Flowlytics platform tracks the movement of drugs across the complex supply chain, from the time they are shipped from the wholesaler to a healthcare facility, then each time drugs are moved throughout the hospital and administered to patients.

Invistics also provides inventory visibility for manufacturers, distributers, repackagers and controlled substance registrants. The company’s drug diversion software works with all electronic health records (EHRs) and automated dispensing cabinets.

One pilot hospital for the NIH grant included Piedmont Athens Regional Medical Center in Georgia, which serves as the 11-hospital system’s east hub.

Utilizing Invistics’ technology enabled Piedmont’s drug diversion program to identify drug diversion without false positives, creating a much more effective and efficient program.

“Detecting drug diversion is of the utmost importance here at Piedmont Athens Regional,” Charles Peck, interim CEO of Piedmont Athens Regional, said in a statement.

He explained that by using Invistics the hospital has been able to detect drug diversion at a level they’ve never been able to reach previously.

“The new supervised machine learning capability makes it that much easier for us to detect diversion and better focus on patient care as a result,” he said.

Nathan Eddy is a healthcare and technology freelancer based in Berlin.

Email the writer: [email protected]

Twitter: @dropdeaded209 

Healthcare IT News is a HIMSS Media publication. 

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