Healthcare’s Hidden Crisis: AI’s Essential Role in Combating Drug Diversion

By Steve Mok, PharmD, MBA, BCPS, BCIDP, Manager of Pharmacy Services and Fellowship Director for Clinical Surveillance and Compliance, Wolters Kluwer, Health.

Each year, an estimated 37,000 diversion incidents occur in U.S. healthcare facilities, which likely understates the true extent of this problem. These incidents are not just numbers; they represent compromised patient safety, colleagues facing substance use disorder and organizations exposed to significant financial and reputational risks.

Resource Gaps and Hidden Risks

Over recent years, hospitals have responded to these cases and the perceived risk by expanding their diversion teams. Today, most large facilities employ three or more full-time staff dedicated to diversion programs, a notable improvement from 2023, when most reported only one or fewer staff member being engaged in that work. However, despite this increased investment, confidence in these programs remains low. Just 32% of survey participants say they feel “very confident” in their current approaches.

This confidence gap stems from the limitations of traditional detection methods. Routine audits (71%), dispensing reports (68%), and inventory checks (65%) – which are the most used detection methods – require significant time and attention, yet still leave considerable vulnerabilities. As one respondent noted, “Automated dispensing systems and electronic tracking can create a false sense of security, but shrewd diverters often find ways to bypass, especially in high-volume environments.”

The Opportunity with AI

With their ability to parse through more data than would ever be humanly possible, artificial intelligence and machine learning offer a path forward. These technologies can analyze patterns across large data sets in seconds, identifying suspicious behaviors that would take clinical teams days to uncover, if they are found at all. Despite this, fewer than 38% of healthcare organizations have implemented AI tools for diversion detection, with adoption rates even lower in smaller hospitals (32%) compared to larger institutions (48%).

This technological gap creates disparities in patient and staff safety, and organizations recognize AI could help. While 76% of respondents express interest in AI solutions, several barriers remain: lack of technical expertise (29.6%), insufficient leadership buy-in (27.2%), budget constraints (19.2%), and inadequate staffing (18.4%). Smaller hospitals, in particular, face greater obstacles due to their limited personnel and financial resources, placing their patients and staff at increased risk.

The Need for Collaboration & Culture Change

Beyond leaning on the power of technology, effective diversion prevention requires collaboration across departments. While pharmacy and nursing teams typically participate in diversion programs, other critical stakeholders remain underrepresented. Only about one-third of respondents report engagement from anesthesiology, even though providers have frequent access to controlled substances. Human resources is similarly involved in just 20% of programs, despite the department’s critical role in prevention training and rehabilitation.

Organizational culture also plays a significant role in diversion prevention. Survey respondents noted a “culture of silence” around this topic that enables diversion to continue unchecked. As one participant explained, reluctance to report suspected diversion often stems from fear of retaliation, concerns about harming a colleague’s career, or the belief that it is not their responsibility. This highlights the need for programs that combine advanced technology with cultural change—fostering accountability and empowering staff to report concerns without fear.

The Urgency for Action

For those still weighing the decision, consider the benefits: tasks that currently absorb your diversion team’s time – manual audits, report reviews and investigations – could be automated, continuous and more accurate. Teams could shift their focus from data review to addressing diversion cases, supporting colleagues in need, spending more time at the bedside and strengthening prevention programs.

Working with hospitals across the country, I have seen firsthand how drug diversion threatens patient care and staff safety. The challenge calls for a new standard—one that leverages both human insight and the precision of AI. For hospital and pharmacy leaders, the question is not whether you can afford to adopt AI-powered diversion detection. With patient lives, regulatory compliance, and your institution’s reputation at stake, the real question is: Can you afford not to?