
FDNY EMS Station geographic placement for optimal coverage.
Suitability correlation between FDNY EMS facility location and hospitals.

Introduction:
In 2018 FDNY EMS responded to 1,862,159 incidents. This is an average of one call every 6 seconds. There are several parts to a 911 call. The initial phone call and time spent on the phone, The time it takes for a unit to respond and treat the patient. The time it takes for the unit to go back into service and become available for the next call.
Study Area:
When a unit responds to an assignment they use equipment. There is only a limited amount of equipment that can safely be stored in the ambulance. In addition too equipment, many patients being treated include some blood borne pathogens. This is especially more concerning with the Covid-19 pandemic. Upon completion of an assignment the unit must restock what they used, and many times go out of service to decontaminate the vehicle or their uniform. This is known as BBP. FDNY EMS stations are strategically placed to provide optimal coverage to the units of NYC but was location proximal to a hospital taken into consideration? I will study location of EMS stations in relationship to the hospital to decrease out-of-service time thus increasing in-service times.
Queens _CFR_EMS_and_hospitals
The area I'm studying is Queens NY. There are 3 levels of pre-hospital care in NYC. Certified First Responders (CFR), Emergency Medical Technician (EMT) and Advanced Life Support (EMT-Paramedic). There are 9 EMS stations with 2 sub-stations. 50 CFR-Engines and 9 hospital in Queens and 2 just over the border in Nassau County. I chose this as I am a Paramedic for the FDNY. There is more than meets the eye when deciding on a location for an essential addition like this.
Question and Hypothesis:

https://www.baruch.cuny.edu/nycdata/population-geography/maps_files/queens_neighborhoods.jpg
What is the most suitable geospatial location for a new FDNY EMS station in Queens N.Y.?
Literature Review (Background Information):
Determining a location for an EMS station is difficult. There are many factors that ned to be taken into consideration, response times and the time it takes to be back in your service area are from the top. After many call the ambulance must return to the station to preform decontamination. I included a short part of a study done in Shanghai which has similar geographical obstacles as NYC as to what factor go into deciding on a new EMS station location. Most early proposed ambulance location models were integer linear formulations. Since these models did not consider the probability that an ambulance might be busy at a given time, they were classified as deterministic. The earliest EMS models have been introduced in the 70s by the articles of Toregas et al. Toregas et al. studied the Location Set Covering Problem (LSCP) which identifies the minimum number of facilities and their locations that cover all demand points within a certain distance. However, the LSCP model cannot cover all demands with limited resources in reality, and one important thing is that once an ambulance is dispatched, some demand points are no longer covered. Due to the fact that LSCP model treats all demand points identically, the solution may require more ambulances than actually needed or underestimate the number of ambulances needed for those locations with relatively heav. To avoid such limits, Church and ReVelle proposed the Maximal Covering Location Problem (MCLP), which locates a fixed number of facilities so as to maximize the amount of demand that is covered by at least one facility.
In each of the above models, a common problem is that coverage may become inadequate when some ambulance vehicles are busy. Hence, to compensate this shortcoming, most literature about the location problem of EMS have followed these two early studies by Toregas et al. (LSCP model) and Church and ReVelle (MCLP model). For example, Daskin and Stern proposed a Hierarchical Objective Set Covering Problem model (HOSC), a hierarchical model for the LSCP, with the objective of minimizing the number of ambulance locations providing full coverage within a distance standard first and then maximizing the number of demand points under multiple coverage. As the HOSC may privilege the congestion of the ambulance, Hogan and ReVelle proposed the Maximal Backup Coverage models BACOP 1 and BACOP 2. These models use two ambulances to cover the demands. Gendreau et al. developed a model known as DSM in which all demands must be covered by ambulance located in a secondary coverage radius of minutes, and in addition, a certain proportion of the demand must be covered in a primary coverage radius of minutes. Liu et al. proposed the service reliability for the demand points to make sure of double coverage. (Liu, Ming, et al.) With the above stated reasons it is important for ambulances to be able to reture back in service in the shortest amount of time and safely.
Method and Data:
I would like to map out EMS station within a 2.5 mile proximity of a hospital. I will then search for a suitable location for an additional station. Queens is a large geographic area and from my preliminary data there seems to be several suitable locations.
I will be using the information we used during week 8 - Perform a ‘Suitability Analysis’ – Use the ‘Overlay Layers’ tool to produce a Union of two or more source layers. Also, you could use the ‘Buffer’ tool as part of your workflow. Query your output layer(s) for specific criteria by creating a multi-step expression in the ‘Find Existing Locations’ tool.
I created a 1- and 3-mile buffer around EMS station and Queens’s hospitals. I then added an addition layer where I created a union and merged them together. Upon comleteion of the layering I will be able to preform an analysis to determine suitable locations.
Map 1 - Basemap
This map shows the location of EMS station and close by hospitals.
FDNY EMS Stations Queens _and_Hospitals
Map 2 - Advanced map
This map a 1 and 3 mile buffer around hospitals and EMS Stations. they map has a slide feature to see the buffers then slide left and you can see the created union.
Left map is with buffers only, right map is the union.
Analysis of Data:
Upon analyzing the data, I was able to detect several locations that fit my criteria that an EMS station is more than 3 miles from the hospital. The locations are in the center by Queens village, Howard Beach, JFK Airport and the Rockaways.
JFK is covered by a private contracted EMS agency. Howard beach sits on the Brooklyn-Queens border and when leaving a queens or Brooklyn hospital they will be in proximity to a EMS facility for BBP and decontamination. The Rockaways is a peninsula, and when leaving the hospital you must pass the EMS facility to make it uptown This leaves the most suitable location to be in Queens Village.
Limitations:
While it looks good on paper it is not always practical. Traffic, construction and other factors are unpredictable. The travel time varies greatly between days and nights. A fair amount of the information is from 2019 and the beginning of 2020. There is enormous amounts of development happening increasing population and congestion.
Future Work:
In the future I would like to also add the location of where the individual ambulance are strategically placed while not on or responding to an assignment. After completion of BBP the unit is available, but how long will it be before they are back in their primary response area?
References (bibliography):
“FIRE DEPARTMENT City of New York Statistics - Citywide Performance Indicators.” Https://www1.Nyc.gov/Site/Fdny/Index.page.
Liu, Ming, et al. “Optimization for the Locations of Ambulances under Two-Stage Life Rescue in the Emergency Medical Service: A Case Study in Shanghai, China.” Mathematical Problems in Engineering, Hindawi, 30 Aug. 2017, www.hindawi.com/journals/mpe/2017/1830480/.