A Monte Carlo Simulation Approach to Optimizing Capacity in a High-Volume Congenital Heart Pediatric Surgical Center

Area of Science:

• Cardiovascular Surgery
• Healthcare Operations Management
• Health Systems Engineering

Background:

• Current elective surgery scheduling prioritizes surgeon availability over patient postoperative cardiac intensive care unit (CICU) length of stay.
• High variation in CICU census leads to operational inefficiencies, including admission delays, cancellations, and underutilization of resources.

Purpose of the Study:

• To identify strategies for reducing variability in CICU occupancy levels.
• To minimize late patient surgery cancellations through optimized scheduling.

Main Methods:

• A Monte Carlo simulation study was conducted using historical CICU admission and discharge data from Boston Children's Hospital Heart Center (2009-2019).
• The simulation modeled daily and weekly CICU census based on realistic distributions of patient length of stay, including short and extended durations.

Main Results:

• Strategic scheduling models demonstrated a potential reduction of up to 57% in patient surgical cancellations.
• The proposed scheduling approach is projected to increase the typically low Monday CICU census and decrease higher censuses later in the week (Wednesday and Thursday).

Conclusions:

• Implementing strategic scheduling can significantly improve surgical capacity and reduce annual patient cancellations.
• Balancing CICU census peaks and valleys optimizes system utilization, mitigating both over- and under-capacity issues.