Healthcare’s hidden crisis: AI’s essential role in combating drug abnormality

By Steve Mok, Pharmd, MBA, BCPS, BCIDP, manager of pharmacy services and Fellowship director for clinical security and compliance, Wolters Kluwer, Health.

Every year, one estimated 37,000 Distraction incidents occur in American healthcare institutions, which probably underestimate the true size of this problem. These incidents are not only numbers; They represent compromised patient safety, colleagues who are confronted with disorders of substance use and organizations that are exposed to considerable financial and reputation risks.

Gaps for resources and hidden risks

In recent years, hospitals have responded to these cases and the observed risk by expanding their distraction teams. Nowadays, most major facilities have three or more full -time staff who focus on diversion programs, a remarkable improvement compared to 2023, when most reported that only one or less employee participated in that work. Despite this increased investment, however, confidence in these programs remains low. Only 32% of the participants in the survey say that they feel “very confident” in their current approaches.

This reliability gap stems from the limitations of traditional detection methods. Routine audits (71%), providing reports (68%) and stock checks (65%) – which are the most used detection methods – require considerable time and attention, but still leave considerable vulnerabilities. As a respondent noted, “can create automated dispensing systems and electronic tracking a false sense of safety, but smart distractors often find ways to bypass, especially in environments with a high volume.”

The chance with AI

With their ability to pars more data than ever humanly possible, artificial intelligence and machine learning offer a path ahead. These technologies can analyze patterns in large data sets in seconds and identify suspicious behavior that clinical teams would last days to discover if they are found at all. Nevertheless, less than 38%of healthcare organizations have implemented AI tools for diversion detection, whereby the adoption figures are even lower in smaller hospitals (32%) compared to larger institutions (48%).

This technological gap creates inequalities in the safety of patients and staff, and organizations acknowledge that AI could help. While 76%of the respondents show interest in AI solutions, there are different barriers: lack of technical expertise (29.6%), insufficient buy-in leadership (27.2%), budget restrictions (19.2%) and insufficient staff (18.4%). Smaller hospitals in particular are confronted with larger obstacles because of their limited personnel and financial resources, so that their patients and staff bring an increased risk.

The need for cooperation and cultural change

In addition to leaning on the power of technology, it requires effective diversion interview cooperation between departments. While pharmacy and nurses usually participate in diversion programs, other critical stakeholders remain under-represented. Only about a third of the respondents report involvement from anaesthesiology, although providers have frequent access to regulated substances. Human Resources is involved in the same way in only 20% of the programs, despite the crucial role of the department in prevention training and rehabilitation.

Organizational culture also plays an important role in preventing diversion. The respondents of the research noted a ‘silence culture’ on this subject with which distraction can remain uncontrolled. As a participant explained, the reluctance to report suspected distraction often arises from fear of retribution, concern about the harm of a colleague’s career, or the conviction that it is not their responsibility. This emphasizes the need for programs that combine advanced technology with cultural change – promoting accountability and enable staff to report worries without fear.

The urgency for action

For those who still weigh the decision, consider the benefits: tasks currently absorb the time of your distraction team – manual audits, report reviews and investigations – can be automated, continuous and accurate. Teams can shift their focus from data evaluation to tackling diversion cases, supporting colleagues in need, spending more time on the bed and strengthening prevention programs.

Working with hospitals throughout the country, I have seen first -hand how drug deviation threatens patient care and the safety of staff. The challenge requires a new standard – one that uses both human insight and the precision of AI. For leaders in the hospital and pharmacy, the question is not whether you can afford to accept AI-driven diversion detection. With patient lives, compliance with the regulations and the reputation of your institution at stake, the real question is: Can you afford it not to do that?