Optimizing Emergency Department Operations: A Simulation Framework for Managerial Decision-Making.

Area of Science:

• Healthcare Operations Research
• Industrial Engineering
• Health Systems Management

Background:

• Emergency departments (EDs) face challenges with fluctuating patient volumes and resource limitations, causing overcrowding and inefficiency.
• Operational inefficiencies in EDs negatively impact patient outcomes and experience.
• Existing optimization methods may not fully address the dynamic nature of ED operations.

Purpose of the Study:

• To present a novel framework combining design thinking and discrete event simulation (DES) for optimizing ED processes.
• To evaluate the impact of different resource configurations on key performance indicators (KPIs) within EDs.
• To provide actionable insights for improving ED operational productivity and patient flow.

Main Methods:

• A hybrid approach integrating design thinking principles with discrete event simulation (DES) was employed.
• A digital twin model was developed using design of experiments to simulate various ED scenarios.
• Key performance indicators, including patient length of stay (LOS), were analyzed to identify bottlenecks and evaluate interventions.

Main Results:

• The simulation model successfully identified critical resource bottlenecks within the ED.
• Targeted adjustments in nurse staffing and bed management demonstrated significant improvements in operational productivity.
• A notable reduction in patient length of stay (LOS) was achieved through the implemented optimizations.

Conclusions:

• The combined design thinking and DES framework offers a practical approach to optimizing ED operations.
• This methodology provides valuable data for hospital administrators to enhance resource allocation and streamline patient flow.
• The study highlights the potential for significant improvements in ED efficiency and patient experience, particularly in resource-constrained environments.