An optimization model for locating and sizing emergency medical service stations

Area of Science:

• Operations Research
• Public Health Management
• Healthcare Systems Engineering

Background:

• Emergency medical services (EMS) are vital for healthcare quality and performance.
• Effective EMS rely on optimal deployment of resources like vehicles, personnel, and facilities.
• Resource allocation challenges include balancing responsiveness with efficient use of limited budgets.

Purpose of the Study:

• To develop an integer optimization model for EMS station location and sizing.
• To minimize total system costs while meeting service coverage constraints.
• To provide a decision-support tool for enhancing EMS responsiveness and resource utilization.

Main Methods:

• Formulation of an integer optimization model.
• Defining decision variables for station location, type, and service region.
• Incorporating service constraints and cost minimization objectives.

Main Results:

• The model provides optimal solutions for EMS station placement and coverage.
• Demonstrated efficiency in handling large urban areas (up to 130 districts).
• Successfully applied and validated using the Adana metropolitan EMS system in Turkey.

Conclusions:

• The proposed optimization model effectively addresses EMS resource allocation challenges.
• Optimal EMS station configuration can significantly improve system performance and cost-efficiency.
• The model offers a valuable tool for urban planning and emergency service management.