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Using a discrete-event simulation to balance ambulance availability and demand in static deployment systems.
1From the Department of Transportation & Communication Management Science, National Cheng Kung University, Tainan, Taiwan.
Summary
Optimizing ambulance deployment using discrete-event simulation improves emergency response times. This method helps determine fleet expansion needs and optimal dispatch strategies during demand surges or reduced availability.
Area of Science:
- Operations Research
- Public Health
- Emergency Medical Services
Background:
- Ambulance response time is critical for emergency care, necessitating efficient matching of fleet availability with demand.
- Maintaining a 90% response rate within 9 minutes requires proactive strategies for managing ambulance resources.
- Temporary decreases in ambulance availability due to events can significantly impact response times.
Purpose of the Study:
- To introduce a discrete-event simulation method for improving ambulance response times.
- To estimate the threshold for ambulance fleet expansion based on increased emergency demand.
- To identify optimal dispatching strategies for temporary reductions in ambulance availability.
Main Methods:
- Developed a discrete-event simulation model using literature data and validated it with the Tainan City emergency medical services (EMS) system.
- Modeled the impact of increased call arrival rates on response times.
- Simulated ambulance deployment strategies during mass gatherings (marathons, concerts, New Year's Eve parties) considering varying durations and out-of-service ambulances.
Main Results:
- The simulation model accurately represented the Tainan EMS system.
- A 56% increase in call arrivals was identified as the threshold for fleet expansion to maintain response time standards.
- The Tainan EMS could spare 2-3 ambulances during events, and the model indicated a potential surplus of two ambulances.
Conclusions:
- Capacity management strategies informed by the simulation model effectively improved ambulance response times.
- Increased numbers of ambulances available for optimal deployment strategies enhance overall system performance.
- The model provides a framework for optimizing EMS resource allocation and dispatching.
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