A recent survey sponsored by Wolters Kluwer Health’s Invistics found that healthcare executives believe most drug diversion in hospitals goes undetected, despite acknowledging its occurrence. Drug diversion incidents in the U.S. are estimated to reach at least 37,000 annually, with just 40% of executives feeling very confident in their detection programs. To improve drug diversion detection, hospitals are increasingly turning to AI and machine learning, with 53% of executives using AI tools expressing high confidence in their detection efforts.
What You Should Know:
- Substance use disorder has far-reaching impacts across society, and healthcare workers are not immune. In some cases, healthcare worker addiction can lead them to use prescription drugs intended for patients or steal them to be sold for personal benefit.
- A recent survey sponsored by Invistics, acquired by Wolters Kluwer Health earlier this year, found that despite 98% of healthcare executives agreeing that drug diversion occurs in hospitals, nearly four in five healthcare executives surveyed (79%) believe that most drug diversion goes undetected.
Insights into the Sphere of Drug Diversion in Healthcare
The U.S. experiences a minimum of 37,000 drug diversion incidents yearly, likely underreported. Just 40% of executives are very confident in their detection programs, with 67% planning to strengthen efforts in 2023.
- Improving inconsistent drug diversion processes: Historically, detecting drug diversion has been a labor-intensive process, with 71% of those surveyed spending at least eight hours on each investigation. Hospitals and ambulatory settings face challenges in maintaining consistent detection programs. The COVID-19 pandemic exacerbated these issues, with 69% of respondents attributing the increased difficulty in drug diversion detection to the higher presence of floating staff or contract workers.
“With staff shortages and use of contract workers at an all-time high, hospitals may see inconsistency in their drug diversion detection efforts,” said Karen Kobelski, Vice President and General Manager of Clinical Surveillance Compliance & Data Solutions, Wolters Kluwer, Health. “Given the risks to patient safety and clinical teams, as well as the potential reputational and financial impact on the hospital itself, hospital leadership should consider how sophisticated technology can keep these programs running smoothly. As one of our respondents commented, ‘If you do not have any drug diversion, then you are not looking hard enough.’”
Want to publish your own articles on DistilINFO Publications?
Send us an email, we will get in touch with you.
AI offers a substantial opportunity to enhance drug diversion detection in hospitals and health systems. Through continuous data analysis across various hospital systems, advanced technology-based programs can bolster diversion detection, ultimately leading to improved patient safety.
- Embracing AI for drug diversion detection: Organizations are increasingly embracing AI for diversion detection, with a notable shift since 2019. The use of machine learning to identify diversion patterns and automatically alert potential cases has nearly doubled in hospitals, rising from 29% to 56%. Additionally, facilities employing AI tools express greater confidence in their drug diversion programs, with 53% of executives reporting a high level of confidence in the effectiveness of their detection efforts.
Source: Hit Consultant
