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Building an Adaptable Pediatric Intensive Care Unit Simulation Portfolio: Advancing Efficiency, Flexibility, and
Daniel Loeb1,2, Kelly Ely3, Kelly Collins2
1From the University of Cincinnati College of Medicine, Cincinnati, Ohio.
Introduction:
Simulation-based education enhances patient safety and team performance in high-acuity environments, such as the pediatric intensive care unit (PICU). However, many units struggle to implement scalable, dynamic simulation programs adaptable to fluctuations in patient volume, clinical acuity, and staffing demands. This quality improvement initiative aimed to develop and implement a comprehensive PICU simulation portfolio, integrating predictive analytics, multidisciplinary collaboration, and real-time clinical data to increase the frequency of simulations and training exposures.
Methods:
The PICU simulation portfolio underwent iterative improvement via a structured quality improvement initiative. Guided by a specific, measurable, achievable, relevant, and time-bound aim and key driver diagram, targeted interventions were implemented through iterative plan-do-study-act cycles. These interventions included introducing standardized simulation encounter types, a simulation encounter decision tree informed by real-time predictive analytics, incorporating a multidisciplinary team, centralizing simulation resources, and streamlining the setup process. Primary outcomes included simulation frequency and cancelations. Secondary outcomes included participation, facilitator workload, and safety event monitoring.
Results:
Over the intervention period (July 2022 through June 2024), the simulation program demonstrated increased training capacity, improved efficiency, and heightened participation. Annual simulations increased by 128%, incorporating 1,256 staff, whereas cancelations decreased by 25%. Simulation setup and takedown time were reduced by 58% and 64%, respectively. There were no reported safety events.
Conclusions:
This scalable PICU simulation training model led to measurable gains in efficiency, training capacity, and multidisciplinary collaboration. Its adaptable framework offers a promising approach for other clinical settings aiming to enhance simulation-based education and training to improve patient care outcomes.
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