Why the Closest Ambulance Cannot be Dispatched in an Urban Emergency Medical Services System

2008 ◽  
Vol 23 (2) ◽  
pp. 161-165 ◽  
Author(s):  
Stephen F. Dean

AbstractIntroduction:Response time performance is related to increased survival for a relatively small group of patients with critical emergencies. Effectively utilizing current resources is a challenge for all emergency medical services (EMS) systems for reasons of cost-effectiveness and safety.Problem:The objective of this study was to identify opportunities for improving ambulance response-time performance in an urban EMS system using fixed deployment.Methods:This was a qualitative and quantitative case study which consisted of structured interviews with policy makers, managers, and workers in a fire department EMS division, as well as analysis of dispatch data and observation of dispatch operations.Results:The current computer-aided dispatch (CAD) system does not identify the closest ambulance to the emergency, and therefore, dispatchers must guess which unit is closer when units are not within their stations or “first due” areas. There is no means to track how often dispatchers guess correctly or how often the closest ambulance actually is dispatched to the emergency.Temporal and geographic patterns were identified. Opportunities also were identified to improve response time performance through the use of dynamic deployment and peak-load staffing.Conclusions:The results suggest that there were opportunities for improving ambulance response times by implementing strategies such as peak-load staffing and dynamic deployment. However, the most important improvement would be the implementation of a policy to send the closest ambulance to the emergency. More research is needed to identify how prevalent the failure to send the closest ambulance is within EMS systems that use fixeddeployment response strategies and computer-aided dispatch systems that are incapable of tracking unit locations outside of their stations.

2020 ◽  
Vol 17 ◽  
Author(s):  
Ahmed Ramdan M Alanazy ◽  
Stuart Wark ◽  
John Fraser ◽  
Amanda Nagle

Background Response impacts on treatment outcomes, particularly for time-sensitive illnesses, including trauma. This study compares key outcome measures for emergency medical services (EMS) operating in urban versus rural areas in the Riyadh region of Saudi Arabia. Methods A cross-sectional study of EMS users was conducted using a random sampling method. Primary outcome measures were response time, on-scene time, transport time interval and survival rates. Secondary outcomes were the length of stay in the intensive care unit and hospital. Data were compared between the urban and rural groups using the t-test and chi-square test. Results Eight-hundred patients (n=400 urban, n=400 rural) were included in the final analysis. Cases in rural areas had significantly higher response times and duration times (median response 15 vs. 22 minutes, median duration 43 vs. 62 minutes). Response times were significantly longer for rural areas for MVC, industrial accidents, medical incidents and trauma, but there was no significant difference in duration time for industrial accidents. While urban areas had significantly shorter response times for all incident types, there was no difference with rural areas in duration time for chest injury, gastrointestinal, neurological or respiratory problems. Conclusion The findings indicate that response time and duration differs between urban and rural locations in a number of key areas. The factors underlying these differences need to be the subject of specific follow-up research in order to make recommendations as to the best way to improve EMS in Saudi Arabia and to close the gap in rural and urban service delivery.


2021 ◽  
Vol 9 (E) ◽  
pp. 378-381
Author(s):  
Korakot Apiratwarakul ◽  
Phongphat Ruamsuk ◽  
Takaaki Suzuki ◽  
Ismet Celebi ◽  
Somsak Tiamkao ◽  
...  

BACKGROUND: The development of emergency medical services (EMSs) in Thailand is divided into two phases following the enactment of the Emergency Medical Act in 2007 aimed at making the work model more systematic. However, the amount of EMS operations has not been well studied. AIM: The aim of this study was to describe the pattern of EMS operations throughout a 5-year period. METHODS: A retrospective, single-centered study at a medical school hospital in Thailand. Data were gathered from the EMS database at Srinagarind Hospital throughout the years 2016–2020. RESULTS: A total of 10,384 EMS operations were examined over a 5-year period (2016–2020). The mean age of patients in 2016 was 40.2 ± 3.5 years, and 55.3% (n = 1178) were male. Operations were most commonly performed during the afternoon shift (4.00 p.m.–0.00 a.m.) 41.0%, 38.6%, 39.5%, 39.2%, and 50.8%, respectively. The amount of EMS members had a tendency to increase in number throughout the 5 years of study (p = 0.022). The average times from 1669 center call receipt to arrival on scene (response time) for 2016 and 2020 were 8.52 ± 2.20 min and 5.52 ± 3.02 min, respectively (p < 0.001). CONCLUSION: The development of EMS at Srinagarind Hospital took place with an increase in the age of patients, number of operations in the afternoon shift, and EMS members, yet with a decrease in response times.


Author(s):  
Vipul Mishra ◽  
Richa Ahuja ◽  
N. Nezamuddin ◽  
Geetam Tiwari ◽  
Kavi Bhalla

International standards recommend provision of one ambulance for every 50,000 people to fulfill demand for transporting patients to definitive care facilities in low and middle income countries (LMICs). Governments’ consistent attempt to build capacity of emergency medical services (EMS) in LMICs has been financially demanding. This study is an attempt to assess the feasibility of capacity building of existing EMS in Delhi, India by using taxis as an alternative mode of transport for emergency transportation of road traffic crash victims to enable improvement in response time for road traffic crashes where time criticality is deemed important. Performance of the proposed system is evaluated based on response time, coverage and distance. The system models the performance and quantifies the taxi–ambulance configuration for achieving EMS performance within international standards.


1997 ◽  
Vol 12 (1) ◽  
pp. 22-29 ◽  
Author(s):  
Stephan G. Reissman

AbstractIntroduction:Osborne and Gaebler's Reinventing Government has sparked discussion amongst elected officials, civil servants, the media, and the general public regarding advantages of privatizing government services. Its support stems from an effort to provide services to municipalities while reducing taxpayer expenditure. Many echo the sentiment of former New York Governor Mario Cuomo, who said, “It is not government's obligation to provide services, but to see that they're provided.” Even in the area of public safety, privatization has found a “market.”In many localities, privatizing Emergency Medical Services (EMS) is a popular and successful method for providing ambulance services. Privately owned ambulance services staff and respond to medical emergencies in a given community as part of the 9–1–1 emergency response system. Regulations for acceptable response times, equipment, and other essential components of EMS systems are specified by contract. This allows the municipality oversight of the service provided, but it does not provide the service directly. As will be discussed, this “contracting-out” model has many benefits.Privatizing EMS services is a decision based not only on cost-savings, but on accountability. A thorough evaluation must be utilized in the selection process. Issues of efficiency, effectiveness, quality, customer service, responsiveness, and equity must be considered by the government, in addition to cost of service.The uncertain future of health care in the United States has led those in EMS to look beyond the field's internal market to explore additional opportunities for expanding and redefining its roles beyond emergency care. It is important, however, to consider how emergency medical care, the original role of EMS, can be best delivered. Responding to emergencies is not just one of the functions involved in this field, it is the principal function from which public perception of EMS is formed, and from which support for entering other markets can be fostered.The purpose of this paper is to present several important concepts and considerations that public officials, medical directors, and the public must be aware of when contemplating the possibility of privatizing their Emergency Medical Services. A review of the general concepts of privatization and issues of accountability will be presented, referencing policy experts, followed by an examination of how advocates of privatization might see these issues as they relate to providing EMS. The conclusion will present prescriptions for both municipal and commercial ambulance providers.


2016 ◽  
Vol 31 (6) ◽  
pp. 608-613 ◽  
Author(s):  
Bruno Schnegg ◽  
Mathieu Pasquier ◽  
Pierre-Nicolas Carron ◽  
Bertrand Yersin ◽  
Fabrice Dami

AbstractIntroductionThe concept of response time with minimal interval is intimately related to the practice of emergency medicine. The factors influencing this time interval are poorly understood.ProblemIn a process of improvement of response time, the impact of the patient’s age on ambulance departure intervals was investigated.MethodThis was a 3-year observational study. Departure intervals of ambulances, according to age of patients, were analyzed and a multivariate analysis, according to time of day and suspected medical problem, was performed.ResultsA total of 44,113 missions were included, 2,417 (5.5%) in the pediatric group. Mean departure delay for the adult group was 152.9 seconds, whereas it was 149.3 seconds for the pediatric group (P =.018).ConclusionA statistically significant departure interval difference between missions for children and adults was found. The difference, however, probably was not significant from a clinical point of view (four seconds).SchneggB, PasquierM, CarronPN, YersinB, DamiF. Prehospital Emergency Medical Services departure interval: does patient age matter?Prehosp Disaster Med. 2016;31(6):608–613.


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