HealthJanuary 27, 2022

Five ways employee drug diversion can be detected by machine learning

Discover how advanced technology is helping hospitals detect and prevent drug diversion among healthcare workers with five real-life scenarios where advanced technology has assisted in uncovering employee drug diversion.

According to the National Council of State Boards of Nursing, approximately 15% of healthcare workers will struggle with drug dependence. While most hospitals are aware that drug diversion is occurring, most go undetected.

With significant negative impacts on quality of care and patient safety, this is a challenge necessary to tackle. Yet, stretched hospital resources struggle to keep up.

This educational webinar covers five cases where advanced technology has helped expose employee drug diversion. We review best practices and case studies for how hospitals can detect when medications are stolen within their facilities.

Key takeaways

  • Explore best practices for detecting drug diversion patterns so you can safeguard employees and patients.
  • Learn about five cases where employee drug diversion was detected by advanced analytics and machine learning.
  • Understand case studies and examples of drug diversion detection to help you determine where to focus your drug diversion efforts.

Request the webinar to learn more

Sentri7 Drug Diversion
Quickly uncover potential diversion from purchase to patient with predictive analytics and actionable dashboards.
Reconciles drug transactions using AI to rapidly and accurately identify patterns of behavior consistent with drug diversion.
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