Prevention, role of advanced machine learning systems, safety should be top of mind for next 12 months and beyond
The record number of fentanyl drug overdoses1 has rightfully caused national alarm and heightened awareness of the dangers of these potent drugs. But in 2023, health care organizations also need to pay closer attention to what is happening within their own facilities.
Although health leaders are increasingly aware of the prevalence of substance use disorders (SUDs) in the public domain, drug diversion within hospitals, pharmacies, and physician practices is still a huge concern, according to 96% of health leaders surveyed in a 2021 study by Porter Research and Invistics.2 And because most drug diversion remains undetected, health leaders need to double down on diversion prevention strategies to avoid legal, financial, and clinical repercussions.
This raises several questions, but the biggest is this: Given how financially stretched health care organizations already are, how can they do a better job of lowering their drug diversion risk in 2023?
Here are the 3 biggest drug diversion trends that health leaders will face in 2023, as well as the solutions they will need to embrace to make meaningful progress in alleviating them:
TREND #1: The rise of deadly synthetic opioids and methamphetamines
The Challenge: The drug overdose epidemic is now being driven by illicitly manufactured fentanyl, often in combination with methamphetamine, according to a policy brief released in September 2022 by the American Medical Association.3 The brief also noted that more than 107,000 deaths were reported in the United States between December 2020 and December 2021.3 This means that clinicians are seeing more patients with SUDs in emergent care settings and that SUDs have escalated among everyone—including clinicians themselves.
The Solution: Resources such as the American Hospital Association’s updated guide for opioid stewardship measurement highlight best practices for hospital tracking of opioids, including acute pain management, harm reduction, and identification and treatment of opioid use disorder.4 Such measures help ensure that clinicians, administrators, care partners, patients, and communities are on the same page, and that opioids are distributed in the right way, for the right length of time, to the right patients, thereby minimizing potential harmful effects.
But this is just the beginning. Health leaders will also need to do more to protect their own coworkers, such as ensuring all clinical staff are educated on the signs and symptoms of substance use and know how to report suspected drug diversion incidents. Training sessions with staff should also emphasize anonymous reporting tools within their organization, and why reporting will help the person diverting drugs get the help they need to treat their SUD. Such training can also leverage public databases such as Healthcare Diversion.org, which allows visitors to see just how often drug diversion is happening across the country and the danger it causes to patients, clinicians, health care facilities, and their communities.5
TREND #2: Staffing shortages and travel clinicians are raising safety risks
The Challenge: Severe levels of burnout are pushing physicians and other clinicians to the brink of exhaustion, causing many to leave medicine altogether or significantly cut back their hours. The ongoing “Great Resignation” is leading to more and more staffing shortages and often to an increased use of contract staff such as travel nurses.6 There are concerns that this could raise the risk of diversion if workers are not appropriately vetted with thorough background checks, or if traveling clinicians who are diverting are not detected and reported before they move on to another facility.
The Solution: Machine learning analytics can detect drug diversion effectively and efficiently. These computer systems cull data from multiple IT systems, including electronic health records, medication-dispensing cabinets, employee time clocks, and wholesaler purchasing records, to pick up on patterns associated with drug diversion.
Data from a retrospective study published in February 2022 in the American Journal of Health-System Pharmacy showed that advanced analytics and machine learning technologies detected known diversion cases an average of 160 days faster than existing, non–machine learning detection methods. Additionally, the machine learning model demonstrated a 96.3% accuracy.7
TREND #3: Limited resources for drug diversion detection professionals
The Challenge: Throughout 2021 and 2022, hospitals and health systems continued to use an all-hands-on-deck approach to patient care, as they navigated the ups and downs of health care in a world with endemic COVID- 19. One of the unintended consequences of this shift in priorities was a decline in resources for drug diversion detection.
The Solution: It is time for health leaders to reinvest in hiring dedicated professionals who are experts in medication management, drug safety, and drug diversion, and who can ensure that policies, people, and technology investments support a health care organization’s commitment to safety. As Russ Nix, founder of Aegis RX, noted in an article published by Patient Safety & Quality Healthcare, designating personnel to oversee drug diversion initiatives also shows staff and clinicians that the organization takes the issue seriously.8
“If there’s no one watching, it doesn’t matter what technology solution is in place,” Nix said. “If an organization is wholly focused on COVID-19, [for example], clinicians might sense they’re not being watched and try to get away with diversion.”8
THE TAKEAWAY: Pour More Resources Into Prevention
Although every health care organization faces difficult budgeting decisions, now is not the time to reduce efforts to stop drug diversion from occurring in our facilities. What is needed, right now, is a sustained commitment to not only treat patients with SUDs, but to protect patients and coworkers from the risks of drug diversion by health care workers.
About the Author
Tom Knight, MBA, is founder and CEO of Invistics.