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

Abstract

Automatic stop orders (ASOs) in computerized prescription order entry (CPOE) systems predefine the length of treatment. This can improve resource use for select therapies (e.g., empirical antibiotics). However, root cause analysis of dose omission errors identified inappropriate ASO-directed termination of medications without prescriber notification. This quality improvement initiative aimed to identify potential failures of the medication ASO processes to develop a new workflow and anticipate issues that may arise after implementation. A failure mode and effect analysis (FMEA) was conducted following Institute of Healthcare Improvement guidance. A multidisciplinary ASO-FMEA team reviewed the existing workflow. Failure modes, risk priority numbers (RPNs), and interventions were identified and assessed. The RPNs calculated for the proposed new workflow (assuming all recommendations were implemented) were compared with those of the existing workflow. Eight failure modes, 17 effects, and 31 causes were identified in the five workflow steps (mean RPN 365.4; median 280). Specific, measurable, achievable, realistic, and time-bound interventions were proposed. Assuming successful implementation of all recommendations, the RPNs of the proposed workflow (mean 117.6; median 112) were significantly lower (p < 0.05). When modifying existing CPOE systems, FMEA may identify possible failures that can be addressed before the implementation of a new process. This may prevent errors, improving medication safety. Regardless, continuous audit and monitoring are required to ensure the effectiveness of implemented changes.