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

BACKGROUND: Urban areas in the US are increasingly focused on mass casualty incident (MCI) response. We simulated pre-hospital triage scenarios and hypothesized that using hospital-based blood product inventories for on-scene triage decisions would minimize time to treatment.

STUDY DESIGN: Discrete event simulations modeled MCI casualty injuries and patient flow after a simulated blast event in Boston, MA. Casualties were divided into moderate (ISS 9-15) and severe (ISS>15) based on injury patterns. Blood product inventories were collected from all hospitals (n=6). The primary endpoint was the proportion of casualties managed with 1:1:1 balanced resuscitation in a target timeframe (moderate, 3.5U RBC in 6 hours; severe, 10U RBC in 1 hour). Three triage scenarios were compared including unimpeded casualty movement to proximate hospitals (Nearest), equal distribution among hospitals (Equal), and blood product inventory-based triage (Supply-Guided).

RESULTS: Simulated MCIs generated a mean +/- SD of 302 +/- 7 casualties including 57 +/- 2 moderate and 15 +/- 2 severe casualties. Nearest triage resulted in significantly fewer overall casualties treated in the target time (55% vs Equal 86% vs Supply-Guided 91%, p<0.001). These differences were principally due to fewer moderate casualties treated whereas there was no difference among strategies for severe casualties.

CONCLUSIONS: In this simulation study comparing different triage strategies including one based upon actual blood product inventories, nearest hospital triage was inferior to equal distribution or a supply-guided strategy. Disaster response leaders in US urban areas should consider modeling different MCI scenarios and casualty numbers to determine optimal triage strategies for their area given hospital numbers and blood product availability.