Drug diversion in healthcare facilities has many victims: patients, organizations, communities, and even the people diverting drugs developing a substance use disorder.
There has been tremendous innovation in drug diversion detection software in the last few years. Healthcare facilities and their regulators can detect diversion much earlier than older traditional monthly reports, saving many hours of manual investigation. This new software uses artificial intelligence and machine learning to find known patterns of diversion in datasets already available to most healthcare facilities, such as electronic health records (EHRs) and automated dispensing cabinets (ADCs).
Watch this educational webinar summarizing what’s new in drug diversion detection for state regulators, licensure boards, law enforcement, and payers.
Research reported in this webinar was funded by the National Institute on Drug Abuse (NIDA) within the National Institutes of Health (NIH) under award number R44DA044083.
What you'll learn
- Why old software fails to detect most drug diversion and has so many false positives.
- Why new software, utilizing machine learning and consolidated data sets, detects drug diversion sooner, with significantly fewer false positives.
- How hospitals using newer software have detected diversion on average 160 days faster.
- How audience members can learn more about this new technology and share it with healthcare leaders in their states/jurisdictions.
