Emergency Medical Service Stations for Isfahan
Image credit: Reza Mahmoudi
Table of Contents
Overview
CLIENT
City of Isfahan
LOCATION
Isfahan, Iran
Role
Designer, Planner
Markets
Healthcare
Transportation Market
Solutions
Emergency Medical Service Stations
Vehicle Allocation
Routing
Regions
Municipality of Isfahan
Our Client’s Challenge
Isfahan (or Esfahan) is a city in the Central District of Isfahan County, located in Isfahan Province, Iran. It serves as the capital of the province, county, and district. Situated about 440 kilometers (270 miles) south of Tehran, Isfahan has a population of approximately 2.22 million, making it the third most populous city in Iran after Tehran and Mashhad, and the second-largest metropolitan area in the country.
One of the most important criteria for evaluating a city’s emergency medical system (EMS) is response time, which depends on both the availability of ambulances at the time of a request and the time required to reach the incident location.
The Municipality of Isfahan recently allocated new funding to improve its emergency response system by reallocating existing resources and acquiring new ones, including ambulances and portable emergency medical service stations (mobile container).
This project focused on several key objectives:
- Critical Assessment: Evaluating the performance of the existing EMS system, analyzing service requests, response patterns, and ambulance travel times using large historical datasets.
- Scenario Development: Defining a range of possible strategies to enhance the performance of the EMS network in Isfahan.
- Data-Driven location-allocation study: Applying advanced data-driven methods, algorithms, and programming tools to perform a location-allocation analysis addressing the client’s key challenges.
- sophesticated routing framwork: Developing a dynamic routing framework to optimize ambulance dispatch and response operations within each assigned service area.
- Stakeholder Reporting: Presenting analytical results, findings, and strategic recommendations to city managers and other key stakeholders.
Our Solution
In partnership with the Municipality of Isfahan and the Department of Health and Medical Education, and using detailed historical data, our project developed multiple data-driven strategies to address the city’s emergency response challenges. Our team applied innovative analytical methods to carry out the project through three major stages outlined in our proposed project pipeline.
Figure: The location of ambulances in Isfahan in 2017.
Parameter estimation
Determining the optimal locations for EMS stations requires understanding the distribution of medical relief demand across different areas of the city. The demand for emergency medical assistance in each area depends on factors such as population density, residents’ average age, quality of life, and traffic conditions.
In this stage of the project:
- The team defined medical relief demand based on the number of calls that resulted in dispatching an ambulance to the request location.
- The city was divided into small analysis zones, and the hourly, daily, weekly, and monthly relief requests for each zone were calculated using historical data.
- Since each ambulance can respond to only one request within a given time interval (e.g., one hour), it was essential to estimate the probability of multiple requests occurring in the same zone during that time.
- A Poisson distribution function was applied to model the probability of a specific number of requests arising within a defined time slot.
Dynamic routing algorithm and computer programming for ambulances
Location–allocation and routing problems are inherently complex. Therefore, developing efficient models and algorithms was a critical component of this project. Response time for each relief request is directly influenced by the travel time of ambulances to the incident location. To enhance overall system efficiency, in the second stage, our team developed a dynamic routing framework that optimizes ambulance dispatch each time a request is received. The framework is based on selecting the minimum pessimistic travel time among all feasible routes, ensuring that ambulances reach their destinations as quickly and reliably as possible under varying traffic conditions.
Dynamic routing algorithm and computer programming for ambulances
After estimating the necessary parameters and developing the routing algorithm, a comprehensive data-driven approach was implemented to:
- Identify the optimal new locations for existing EMS stations.
- Determine the locations for newly required EMS stations.
- Estimate the number of additional ambulances needed within the system.
- Allocate ambulances efficiently across all stations.
- Estimate the required budget and quantify the expected improvements in service performance.
Outcomes
- Scalable Data-Driven Framework: Developed a replicable, data-driven framework for evaluating multiple scenarios aimed at improving the performance of the EMS, as well as guiding long-term investment and capital planning decisions.
- Near-Optimal Solutions: Designed advanced models and algorithms that achieved close to exact solutions.
- Operational Continuity: Maintained continuous EMS operations during the system assessment and redesign process.
- Huge perfromance improvment: Increased relief request coverage from 77.56% to 95.1%, representing a major success in enhancing the effectiveness of Isfahan’s emergency medical system.
- Strategic Guidance: Provided the City of Isfahan with a clear roadmap for improving EMS performance and practical guidance on applying the developed analytical framework for future planning and evaluation efforts.
