Using Discrete Event Simulation to predict KPI's at a Projected Emergency Room.

Area of Science:

• Healthcare Operations Research
• Clinical Informatics
• Systems Engineering

Background:

• Discrete Event Simulation (DES) is crucial for designing and adapting clinical facilities.
• Achieving Key Performance Indicators (KPIs) like reduced waiting and stay times is a primary goal in healthcare facility management.
• Computational modeling offers a robust approach to analyzing and optimizing healthcare processes.

Purpose of the Study:

• To develop and validate a Discrete Event Simulation (DES) model for clinical facility design.
• To identify specific modifications within the DES model that can significantly improve patient throughput and efficiency.
• To quantify the impact of proposed changes on key performance indicators (KPIs) such as patient cycle time.

Main Methods:

• A computational model was constructed using Discrete Event Simulation (DES) principles.
• Model validation was performed through expert judgment and analysis of supporting statistical data.
• Specific scenarios were simulated, focusing on adjustments to the patient's attention model.

Main Results:

• The validated DES model accurately reflected clinical facility operations.
• One simulated scenario resulted in a significant 50% decrease in the average patient cycle time compared to the baseline model.
• Modifications to the patient's attention model were identified as the primary driver for the observed efficiency gains.

Conclusions:

• Discrete Event Simulation (DES) is an effective tool for optimizing clinical facility design and performance.
• Targeted adjustments, particularly to patient flow and attention models, can yield substantial improvements in operational efficiency.
• The validated DES model provides a reliable framework for future facility planning and adaptation to meet performance targets.