Combining spatial information and optimization for locating emergency medical service stations: A case study for...

Area of Science:

• Operations Research
• Public Health
• Spatial Analysis

Background:

• Effective emergency medical services (EMS) are crucial for patient outcomes, reducing hospital stays, and lowering costs.
• Restructuring EMS locations is a complex challenge, often constrained by economic factors.
• Optimizing EMS deployment is vital for ensuring timely and efficient emergency care.

Purpose of the Study:

• To develop an integrated spatial and integer optimization approach for EMS location planning.
• To address economic constraints in stationing emergency care physicians.
• To improve resident coverage and analyze daytime population distribution.

Main Methods:

• Utilized maximum coverage linear programs to determine optimal physician placement.
• Incorporated constraints on physician stationing and calculated travel distances using a digital road graph.
• Analyzed coverage for both resident and daytime populations using a cell grid for demand aggregation.

Main Results:

• Demonstrated that fewer emergency care physicians can achieve broader resident coverage, particularly beneficial for low-population areas.
• Found minimal variance between the top solutions, indicating robust placement strategies.
• Showed that daytime population coverage generally exceeds resident coverage due to commuting patterns.

Conclusions:

• The proposed optimization method provides superior resident coverage with fewer emergency care physicians compared to the existing system.
• The approach offers a data-driven strategy for enhancing EMS efficiency and accessibility.
• The findings have significant implications for public health policy and resource allocation in emergency services.