Using big data to prevent drug diversion
The latest approach to preventing drug diversion in hospitals employs analytical software and big data. Through extensive monitoring, it is possible to identify anomalous behavior, suspected diversion activities and vulnerable areas throughout the chain.
In brief, the vast amount of data utilized enables the software to create a common behavioral profile, any aberrations from which may be cause for further investigation. It breaks this down further by facility, clinical area and profession. By searching the data for patterns and tendencies, the system makes it easier to detect drug diverters that try to hide their illicit behavior within normal workflows.
But, as usual, the solution to the problem is multi-faceted. To combat the issue more efficiently, big data analysis could be combined with access cards, check-in systems for medicine cabinets, monitoring of patient pain levels or systems such as DrugLog® that, by screening the waste returned from the OR, can discover if narcotic substances have been replaced or tampered with.
“- Analyzing huge amounts of data and converting it into information that is visualized through well-designed dashboards are powerful weapons in the fight against drug diversion in hospitals. As diverters are very creative in finding new ways to gain access to controlled substances, modern systems need to look deep into the data to discover suspicious behavior. Measurements performed with DrugLog® will be an additional and important part of the data puzzle that modern analytic tools will need to solve to prevent controlled substances from ending up in the wrong hands or the wrong vein”, says Mats Högberg, CEO of Pharmacolog.
https://www.cdc.gov/drugoverdose/epidemic/index.html, https://www.nytimes.com/interactive/2018/11/29/upshot/fentanyl-drug-overdose-deaths.html, and others