Use of an agent-based simulation model to evaluate a mobile-based system for supporting emergency evacuation decision...

Area of Science:

• Emergency Medicine
• Disaster Management
• Health Informatics

Background:

• Mass casualty incidents (MCIs) are increasing in frequency and severity globally.
• Effective emergency response, particularly casualty evacuation, is critical for patient outcomes and resource management.
• Current MCI response relies on experienced commanders and general guidelines, lacking advanced decision-support tools.

Purpose of the Study:

• To develop and validate a mobile-based decision-support system for MCI casualty evacuation.
• To improve the efficiency of medical resource utilization during MCIs.
• To reduce overall mortality rates in mass casualty incidents.

Main Methods:

• Designed a mobile-based system for real-time collection of medical and temporal data during MCI events.
• Developed a decision-making model integrated into the mobile system to generate personalized evacuation suggestions.
• Validated the system's effectiveness using an agent-based simulation model of MCI response.

Main Results:

• The mobile system provides data-driven evacuation suggestions to incident commanders.
• Agent-based simulations demonstrated the system's potential to reduce overall mortality.
• The system enhances the dynamic, real-time decision-making process in MCI management.

Conclusions:

• A mobile-based decision-support system can significantly improve MCI response effectiveness.
• Data-driven evacuation strategies are crucial for optimizing patient care and resource allocation during mass casualty events.
• The developed system offers a scientifically validated tool to aid commanders in high-pressure MCI scenarios.