Improving Safety Recommendations Before Implementation: A Simulation-Based Event Analysis to Optimize Interventions Designed to Prevent Recurrence of Adverse Events

INTRODUCTION: Pediatric inpatients are at high risk of adverse events (AE). Traditionally, root cause analysis was used to analyze AEs and identify recommendations for change. Simulation-based event analysis (SBEA) is a protocol that systematically reviews AEs by recreating them using in situ simulated patients, to understand clinician decision making, improve error discovery, and, through guided sequential debriefing, recommend interventions for error prevention. Studies suggest that these interventions are rarely tested before dissemination. This study investigates the use of simulation to optimize recommendations generated from SBEA before implementation. METHODS: Recommendations and interventions developed through SBEA of 2 hospital-based AEs (event A: error of commission; event B: error of detection) were tested using in situ simulation. Each scenario was repeated 8 times. Interventions were modified based on participant feedback until the error stopped occurring and data saturation was reached. RESULTS: Data saturation was reached after 6 simulations for both scenarios. For scenario A, a critical error was repeated during the first 2 scenarios using the initial interventions. After modifications, errors were corrected or mitigated in the remaining 6 scenarios. For scenario B, 1 intervention, the nursing checklist, had the highest impact, decreasing average time to error detection to 6 minutes. Based on feedback from participants, changes were made to all but one of the original proposed interventions. CONCLUSIONS: Even interventions developed through improved analysis techniques, like SBEA, require testing and modification. Simulation optimizes interventions and provides opportunity to assess efficacy in real-life settings with clinicians before widespread implementation.