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.
The International Health Facility Diversion Association estimates that at least 37,000 diversion incidents occur in U.S. facilities each year, and this number is likely underreported.1 According to the Wolters Kluwer Invistics survey, “The State of Drug Diversion 2023 Report,” only 40% of executives are very confident in the efficacy of their drug diversion detection programs, with a majority (67%) of executives planning to strengthen their drug diversion efforts in 2023.
Improving inconsistent drug diversion processes
Drug diversion detection has historically been a manual and time intensive process, with 71% of respondents reporting that their team spends eight or more hours on each investigation. Hospitals and ambulatory settings also struggle with consistency when it comes to managing detection programs. When questioned about the impact of the COVID-19 pandemic on their drug diversion programs, 69% of respondents pointed to the increased presence of floating staff or contract workers as the primary factor that made drug diversion detection more challenging.
“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.’
Artificial intelligence (AI) represents a significant opportunity to improve drug diversion detection efforts across a hospital or health system. By monitoring patterns in data over time and across multiple hospital systems, programs incorporating advanced technologies can support increased hospital detection of diversion and improved patient safety.
Embracing AI for drug diversion detection
Recognizing the significant benefits of AI in diversion detection, more organizations have taken the next step forward in leveraging the latest cutting-edge technology to tackle their institutions’ diversion detection gaps. Since the initial survey in 2019, hospitals that report using machine learning to detect patterns of diversion and automatically flag potential cases have nearly doubled (29% to 56%). These facilities are also more confident in their drug diversion programs, with more than half of executives who use AI tools (53%) reporting they are very confident in the efficacy of their diversion detection efforts.
“Hospitals don’t always have the staff to dedicate to an ongoing diversion detection program as they balance more acute patient needs. AI-powered tools continually running in the background enable healthcare providers and leaders to feel more confident they are able to keep their patients and staff safe from diversion,” Ms. Kobelski continued. “AI-based diversion detection programs can do the hard work of sifting through mountains of data to find suspect cases so resource-strapped hospitals can run an effective program and ensure diversion is detected.”
