Implementing Resilience Engineering for Safety Management in Patient-Controlled Analgesia.

Area of Science:

• Healthcare Systems Engineering
• Patient Safety
• Clinical Workflow Analysis

Background:

• Patient-controlled analgesia (PCA) administration is a complex process with inherent risks.
• Understanding functional variability and systemic risks is crucial for improving medication safety.

Purpose of the Study:

• To apply the Functional Resonance Analysis Method (FRAM) and resilience engineering (RE) to identify sources of functional variability and systemic risk in PCA administration.
• To analyze task coupling and performance variability within the PCA workflow.

Main Methods:

• A qualitative case study was conducted at a medical center.
• Focus group interviews with experienced anesthesia nurse specialists (ANSs) were performed.
• Functional mapping using FRAM identified key functional groups and tasks, followed by narrative analysis of variability and coupling.

Main Results:

• Performance variability was identified across all PCA administration stages.
• Critical risks were linked to tightly coupled tasks, high workload, shift changes, and staffing shortages.
• Functional resonance resulted in delays, errors, and increased use of informal coping mechanisms.

Conclusions:

• FRAM effectively identified real-world variability and latent risks in PCA workflows.
• RE offers a framework for developing adaptive safety strategies.
• Integrating FRAM into practice can enhance medication safety and support system redesign.