Optimizing Mass Casualty Triage: Using Discrete Event Simulation to Minimize Time to Resuscitation

Area of Science:

• Emergency Medicine
• Disaster Response
• Health Systems Research

Background:

• Urban emergency medical services increasingly focus on mass casualty incident (MCI) response.
• Prehospital triage strategies are critical for effective MCI management.
• Optimizing patient flow and treatment initiation is a key challenge.

Purpose of the Study:

• To simulate prehospital triage scenarios in a mass casualty incident (MCI).
• To evaluate if using hospital blood product inventories for on-scene triage decisions minimizes time to treatment.
• To compare the effectiveness of different triage strategies.

Main Methods:

• Discrete event simulations modeled MCI casualty injury and patient flow after a simulated blast event.
• Casualties were categorized as moderate (Injury Severity Score 9-15) or severe (Injury Severity Score >15).
• Three triage scenarios were compared: Nearest, Equal distribution, and Supply-Guided (using blood inventories).

Main Results:

• Simulated MCIs generated an average of 302 casualties, including 57 moderate and 15 severe.
• The Supply-Guided strategy (91%) and Equal distribution (86%) significantly outperformed Nearest triage (55%) in treating casualties within target timeframes (p < 0.001).
• Differences were primarily driven by moderate casualties; severe casualty treatment times were similar across strategies.

Conclusions:

• Nearest hospital triage is inferior to equal distribution or a Supply-Guided strategy in MCI simulations.
• Disaster response leaders should model MCI scenarios considering hospital capacity and blood product availability.
• Supply-Guided triage, informed by real-time inventory, offers a superior approach to optimizing patient care during mass casualty events.