Building an Adaptable Pediatric Intensive Care Unit Simulation Portfolio: Advancing Efficiency, Flexibility, and...

Area of Science:

• Medical Education
• Healthcare Quality Improvement
• Simulation Technology

Background:

• Simulation-based education is crucial for enhancing patient safety and team performance in high-acuity settings like pediatric intensive care units (PICUs).
• Implementing scalable and dynamic simulation programs that adapt to changing clinical demands remains a significant challenge for many units.
• Existing simulation models often lack the flexibility to accommodate fluctuations in patient volume, clinical acuity, and staffing.

Purpose of the Study:

• To develop and implement a comprehensive PICU simulation portfolio.
• To integrate predictive analytics, multidisciplinary collaboration, and real-time clinical data into simulation training.
• To increase the frequency of simulations and training exposures within the PICU.

Main Methods:

• A quality improvement initiative utilized a specific, measurable, achievable, relevant, and time-bound (SMART) aim and a key driver diagram.
• Iterative plan-do-study-act (PDSA) cycles informed interventions, including standardized simulation types and a decision tree for real-time analytics.
• Key interventions involved multidisciplinary team integration, resource centralization, and process streamlining for simulation setup.

Main Results:

• Annual simulations increased by 128%, engaging 1,256 staff members.
• Simulation cancellations decreased by 25%, indicating improved program reliability.
• Efficiency gains were observed with a 58% reduction in setup time and a 64% reduction in takedown time; no safety events were reported.

Conclusions:

• The developed PICU simulation training model is scalable and adaptable, demonstrating significant improvements in efficiency and training capacity.
• The integration of predictive analytics and multidisciplinary collaboration enhances simulation program effectiveness.
• This innovative framework offers a promising model for other clinical settings seeking to improve simulation-based education and patient care outcomes.