23-09-2016, 04:43 PM
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Abstract
An important marker of quality emergency medical care is measured by meeting the required paramedic response time. . The nature of some highly time sensitive medical situations such as cardiac arrest and bleeding continues to impose a demand to improve the response time of emergency medical care services. It is widely known that t in the United States, the national average of EMS response time is far above the eight-minute
standard. This is mainly due to the fact that there are time delays occurring in the communication among 911 callers, Public Safety Answering Points (PSAP), First Responders and road traffic uncertainty. Any one of these delays can lead to an increase in response time The current EMS response system is subjected to time delays involved in communication, transportation and uncertainty factors. These various time delays are largely subjected to technical constraints such as unreliable GPS locating of wireless calls and limited level of traffic preemption, and are further worsened by miscommunications and language barriers. The goal of our project is to understand and identify the critical time delays in the EMS dispatch process and to propose a feasible solution that monitors and optimizes these delays. At the beginning of the project, we conducted extensive research about the components of EMS communication system and data on emergency call volumes is collected and analyzed. Then, a mathematical model was constructed to predict and evaluate the response time of an average ambulance specific to the United States, based on which a computer simulation of the mathematical model were produced and analyzed. Finally, these simulations provide us with the opportunity to locate appropriate time delays required to respond to 911 calls. Key factors influencing EMS response time were presented and an improved EMS response system with a reduced ambulance dispatch time was proposed.
1. Introduction
Emergency Medical Services is a system that provides emergency medical care to the sick and injured and also transports patients to hospitals for extended evaluations by a physician or doctor. They provide out-of-hospital medical care and transport to professional medical care facilities. The increase in population in the world over the last few decades has led to anincreasing number of emergency calls. The rising number of emergency calls pertaining to medical situations has resulted in a growing demand of more efficient Emergency Medical Services (EMS). Urgent symptoms such as heart attack, stroke, bleeding and trauma that immediately require first aid could deteriorate into death in a very short period of time. Therefore, quality EMS is imperatively needed and EMS response time is critical to such life-saving practices. However, there still exist gaps in infrastructure due to an uneven distribution of medical resources. As a result, a substantial disparity in EMS response time across regions is present. To meet the growing demand of emergency medical services and to prevent death, it is crucial for EMS care providers to understand the dynamics of the EMS system, to calibrate and reduce the ambulance dispatch time.
The goal of our project is to first understand and improve the EMS system. This includes research into various standards for EMS responders, EMS communication protocols, and EMS equipments. Based on the research, the project locates and classifies the time delays associated with each component of the EMS system. Current EMS dispatch process, EMS traffic preemption and ambulance warning systems are researched. Data of emergency call volumes, information of EMS system in other countries and EMS-associated accidents are collected andanalyzed. To quantify the time delays, a mathematical model is formulated. Using control theory, solutions to mathematical models are derived. The solutions serve as a framework to improve the dispatch and response time. Simulation results are presented to show how the model quantifies the delay factors mentioned above and produces a physically accurate prediction of an average ambulance response time. A communication app is also designed. This app provides an opportunity to reduce communication time delays.
The project report consists of four chapters. Chapter 2 provides an elaboration on background research into ambulance communication technology used by EMS systems. Specifically, current technologies involved in initial 911 call processing, Central Medical Emergency Direction (CMED)-directed communication and ambulance warning devices are addressed. The working mechanism of EMS systems are discussed and compared among different countries in the world including Australia, Canada, China, India and the United Kingdom. Chapter 3 presents solutions and suggestions proposed based on the results of our mathematical models. Two apps are presented to reduce the communication delays identified by the mathematical models. The applications seek to improve the rate of communication between 911 callers and Public Safety Answering Points (PSAP). Simulation results of the mathematical models for EMS respone time in Miami and Massachusetts are shown. The influence of traffic density on ambulance dispatch time is explored and peak traffic densities are identified, along with their respective time delays. The effect of distance on ambulance response time in Eastern Massachusetts is also studied. In Chapter 4, we include concluding remarks on the data analysis and model output presented in Chapter 3. This project extends research into the modeling of communication delays using control theory. Some rising technologies and new ideas associated with reducing ambulance dispatch time are discussed. A summary of the work done in this project is also included.