A model for medication safety event detection.

Area of Science:

• Healthcare Quality and Safety
• Patient Safety Research
• Medication Management Systems

Background:

• Traditional hospital medication safety relies on self-reported adverse drug events (ADEs), which are rare and capture only a fraction of actual events.
• A system-focused approach is recommended to identify broader medication system deficits and prevent future patient risk.
• Current methods offer limited insight into patient harm and overall medication safety.

Purpose of the Study:

• To describe a system-focused model for hospital medication safety event detection.
• To present a case study illustrating the application of this system-focused approach.
• To evaluate the effectiveness of different detection strategies in identifying medication safety events.

Main Methods:

• A three-level medication safety event detection model was employed, ranging from harm-focused to system-focused.
• A Level 3 system-focused methodology integrated voluntary and non-voluntary event detection strategies.
• The approach was applied across 17 critical care, intermediate care, and medical-surgical units in two hospitals.

Main Results:

• A total of 431 medication safety events were detected, including 78 (18.1%) adverse drug events (ADEs) and 353 (81.9%) potential ADEs (PADEs).
• A significant majority of detected events (302, 70.0%) were non-intercepted PADEs, indicating system failures.
• Non-voluntary detection methods were highly effective, yielding the majority of detected events (367, 85.1%).

Conclusions:

• The low incidence of ADEs compared to non-intercepted PADEs highlights significant medication safety system failures.
• These failures place patients at risk for potential harm, underscoring the need for system-level improvements.
• Non-voluntary detection methods proved substantially more effective than traditional self-report methods for identifying medication safety events.