A Geographic Simulation Model for the Treatment of Trauma Patients in Disasters

Area of Science:

• Disaster medicine
• Public health preparedness
• Health systems research

Background:

• The US civilian trauma care system lacks a strategy for quantifying mass-casualty disaster surge demands.
• Effective disaster response requires hospital emergency management and regional planner integration.
• Current systems do not adequately prepare for surges in trauma care needs during mass-casualty events.

Purpose of the Study:

• To present a proof-of-concept model for estimating patient geographic distribution, trauma center resource usage, and mortality rates.
• To assess varying disaster sizes in and around the 25 largest US cities.
• To create a scalable model adaptable to different locales and mass-casualty event types.

Main Methods:

• A hybrid of geographic information systems and dynamic simulation-optimization was used.
• Simulated fast-onset disaster epicenters were randomly located near population centers in 25 major US cities.
• Patient transport to trauma centers was simulated over 48 hours for 100 to 10,000 casualties.

Main Results:

• Mean mortality rates increased from 26.3% to 41.9% with larger disaster scenarios.
• Out-of-hospital mortality rose, while in-hospital mortality decreased as casualty numbers increased.
• Geographically isolated cities with concentrated trauma centers showed lower mortality rates.

Conclusions:

• The simulation model provides insights for realistic mass-casualty event planning.
• Longer transport times in mass-casualty events correlate with increased mortality and resource consumption.
• A systems-based approach to trauma care during disasters is crucial due to overwhelmed local networks.