Using the Failure Mode and Effect Analysis Tool to Improve the Automatic Stop Order Process

Area of Science:

• Health Informatics
• Medication Safety
• Clinical Workflow Optimization

Background:

• Automatic stop orders (ASOs) in computerized prescription order entry (CPOE) systems are designed to manage treatment duration, potentially improving resource use for certain therapies like empirical antibiotics.
• However, analysis of dose omission errors revealed that ASOs can inappropriately terminate medications without notifying prescribers, highlighting a critical safety concern.

Purpose of the Study:

• To conduct a quality improvement initiative to identify potential failures in medication ASO processes within CPOE systems.
• To develop a new workflow and anticipate implementation challenges to enhance medication safety.

Main Methods:

• A multidisciplinary team conducted a failure mode and effect analysis (FMEA) following Institute of Healthcare Improvement guidance.
• The existing ASO workflow was reviewed to identify failure modes, their effects, and causes, calculating risk priority numbers (RPNs).
• Interventions were proposed, and RPNs for a new workflow were compared to the existing one.

Main Results:

• The analysis identified eight failure modes, 17 effects, and 31 causes across five workflow steps, with a high mean RPN of 365.4.
• Specific, measurable, achievable, realistic, and time-bound interventions were developed.
• The proposed new workflow, assuming all recommendations were implemented, showed a significant reduction in RPNs (mean 117.6, p < 0.05).

Conclusions:

• Failure mode and effect analysis (FMEA) is a valuable tool for identifying and mitigating potential failures in CPOE systems before implementing new processes.
• Proactive identification and intervention can prevent medication errors and improve overall medication safety.
• Continuous audit and monitoring are essential to ensure the sustained effectiveness of implemented changes in ASO workflows.