Enhanced coverage by integrating site interdependencies in capacitated EMS location models.

Area of Science:

• Operations Research
• Healthcare Management
• Public Health

Background:

• Emergency medical services (EMS) networks rely on mathematical models for resource allocation.
• Existing models often simplify by assuming site independence and uniform ambulance busyness.
• Real-world EMS operations involve inter-site call forwarding, making site busyness interdependent.

Purpose of the Study:

• To develop a mathematical model that incorporates site interdependencies into EMS resource allocation.
• To improve upon the standard Maximum Expected Covering Location Problem (MEXCLP) by including site busyness constraints.
• To enhance the accuracy of coverage estimation in EMS networks with varying demand.

Main Methods:

• Integrated site interdependencies into the MEXCLP by introducing site-specific busyness upper bounds.
• Applied the novel mathematical formulation to a real-world EMS provider.
• Utilized discrete event simulation with anonymized call data to evaluate solution quality.

Main Results:

• The proposed model demonstrated improved coverage compared to traditional methods in most scenarios.
• Accounting for site interdependencies led to more accurate estimations of ambulance coverage.
• The simulation-optimization approach validated the benefits of the new formulation.

Conclusions:

• Incorporating site interdependencies into EMS network models is crucial for accurate resource allocation.
• The enhanced MEXCLP formulation leads to better ambulance deployment strategies.
• This approach can significantly improve emergency care response times and overall system efficiency.