Why drug diversion detection remains one of healthcare's most persistent patient safety gap

Drug diversion continues to be a significant and underreported patient safety threat. According to the 2025 State of Drug Diversion Survey, 81% of healthcare leaders believe diversion continues to occur frequently, with many incidents going unreported, exposing patients to harm, clinicians to risk, and organizations to regulatory and reputational consequences.

In this drug diversion report, you will discover:

 

  • How staffing trends are shifting, with more organizations dedicating three or more full-time employees to diversion prevention.
  • The critical role of underrepresented departments like anesthesiology and human resources in tackling high-risk areas and managing incidents.
  • The growing importance of advanced technologies like AI and machine learning (ML) tools in identifying drug diversion with speed and precision.
  • Actionable insights into addressing cultural barriers, such as the "culture of silence," to foster accountability and vigilance.
  • Strategies to engage executive leadership by framing drug diversion prevention as a patient safety, compliance, and financial priority.

Download the 2025 State of Drug Diversion Report

Complete the form to review the full report, including key insights that reveal the state of prevention and detection efforts today.

Key Findings

Key hospital drug diversion statistics on optimizing detection

Hospitals overwhelmingly recognize drug diversion as an ongoing problem, yet confidence in detection remains inconsistent.

Routine audits (71%), dispensing volume and activity reports (68%), inventory checks (66%), and drug screenings (61%) continue to be the most used identification methods, reflecting a strong reliance on manual, retrospective processes.

AI adoption is emerging as a key differentiator. Only 37.5% of respondents currently use AI tools for drug diversion detection, though 76% express interest in adopting AI and machine learning. Budget constraints, leadership buy-in, time, staffing, and technical expertise remain key barriers.

While most leaders agree that technology can strengthen detection, usage remains limited, particularly in smaller hospitals. Larger health systems are leading AI adoption, highlighting disparities tied to resources and infrastructure. These findings reinforce the need for both broader organizational engagement and investment in advanced analytics capable of identifying behavioral patterns earlier and more consistently than traditional methods.

Barriers to AI Adoption for Drug Diversion Persist

29.6% Lack of technology interest, 27.2% Leadership buy-in, 19.2% Budgets constrainsts, 18.4% Lack of time/labor, 5.6% No barriors.

Believe drug diversion continues to occur frequently and goes unreported.

Currently use AI tools for drug diversion detection.

Non-AI users express interest in adopting AI and machine learning.

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Additional Drug Diversion Resources

Sentri7 Drug Diversion Reports

View finding and key trends from prior years.
Drug Diversion Report 2023 (PDF)
Drug Diversion Report 2023 (PDF)
Drug Diversion Report 2021 (PDF)
Drug Diversion Report 2021 (PDF)
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