Predicting EMS Response Time using Geographic Zones' Socio-Economic Indicators

• Published in: 2023 IEEE 18th International Conference on Computer Science and Information Technologies (CSIT) pp. 1 - 6
• Main Authors: Ottah, Alice Nneka, Caramancion, Kevin Matthe
• Format: Conference Proceeding
• Language: English
• Published: IEEE 19.10.2023
• Subjects: Computational modeling; Computer science; emergency management; Emergency services; EMS; geographic factors; Hospitals; Medical services; predictive modeling; Predictive models; socioeconomic factors; Time factors
• ISSN: 2766-3639
• DOI: 10.1109/CSIT61576.2023.10324143

Emergency Medical Services (EMS), also known as prehospital care, is a time-sensitive and integral public service [1]. In this paper, we present a usually overlooked, but nonetheless crucial, set of factors that predicts the EMS response time for a community-its geographic socio-economic conditions. EMS response time is an essential factor in the success of prehospital care [2] which is the time from the notification of an occurrence (by dispatch) to the arrival of a response unit at the scene of an emergency. In life-threatening incidents that require getting the patient to care where medical professionals can perform vital procedures, shorter out-of-hospital EMS time intervals are vital for survival. A variety of factors influence EMS response time, such as the unavailability of ambulances at centers closest to a call, triage process, call location, and the distance from the scene to the nearest hospital [3]. Although other factors have been investigated more frequently, research on the environmental and socio-demographic factors that affect EMS response time remains limited. The effective and timely provision of emergency services is an issue that all countries struggle with, and variations across socio-demographic differences (such as poverty level) can contribute to the continued social inequities within the United States.