搜索结果：Emergency Medical Services

It has been stated that the Franco-German Emergency Medical Services System (FGS) has considerable drawbacks compared to the Anglo-American Emergency Medical Services System (AAS): 1. The key differences between the AAS and the FGS are that in the AAS, the patients is brought to the doctor, while in the FGS, the doctor is brought to the patient. 2. In the FGS, patients with urgent conditions usually are evaluated and treated by general practitioners in their offices or at the patient's home; initially, very few approach an emergency department. 3. Emergency patients with life-threatening trauma or disease are treated by emergency physicians at the scene and during transport. Paramedics often are first to arrive at the scene, and until the emergency physician arrives at the scene, are allowed to defibrillate, to intubate endotracheally, and to administer life-saving drugs (epinephrine endotracheally, glucose intravenously, etc.). 4. Prehospital emergency physicians treat patients at the scene and during transport. 5. Emergency patients are guaranteed to be reached by an appropriate emergency vehicle and a respective crew within 10 minutes in 80% of the responses and within 15 minutes in 95% of cases. 6. The FGS deploys qualified emergency physicians assisted by qualified paramedics as prehospital intensive care providers; extended immediate care is standard. Total Prehospital Times (TPT) and scene times only are minimally longer than in the AAS. 7. Emergency Medicine is recognized as a supra-specialty to the base specialties. Specific training programs exist for emergency physicians, medical directors of emergency medical services systems (EMSS), and chief emergency physicians (CEP). 8. Resuscitation attempts are carried out not only by anesthesiologists, but also by internists, surgeons, pediatricians, etc. Emergency medicine encompasses cardiopulmonary resuscitation (CPR) and shock cases, and patients with an acute myocardial infarction, stroke, poly-trauma, status asthmaticus, etc. Emergency patients are admitted directly to emergency departments of the hospitals, which, depending upon the size of the hospital. 9. The incidence of life-threatening trauma victims has decreased to <10% in the FGS. Of a total of 830,000 deaths/year, fatal trauma cases ranked the lowest at 4%. 10. Survival figures on cardiac arrest (asystole, ventricular fibrillation/ventricular tachycardia (VF/VT), pulseless electrical activity (PEA, etc.) reported in the German EMSS correspond to those in Europe and the United States. 11. Paramedic training is characterized by a two-year program followed by a theoretical and a practical examination. 12. Paramedics and emergency physicians-in-training are supervised at the scene and during transport. Quality assurance (Q/A) constitutes an integral and legally compulsory part of the EMSS. 13. In the majority of cases, the emergency patients are evaluated and treated by the respective specialties without delays caused by patient transfer to other hospitals. 14. The FGS does not require a greater number of ambulances and/or personnel than does the AAS. 15. The German healthcare system creates less expenses/capita than the does the U.S. system at a similar level of quality of care. 16. Emergency procedures are carried out by anesthesiologists, emergency physicians, surgeons, internists, and other specialists.

This paper describes an online tool for the visualization of medical emergency locations, randomly generated sample paths of medical emergencies, and the animation of ambulance movements under the control of various dispatch methods in response to these emergencies. The tool incorporates statistical models for forecasting emergency locations and call arrival times, the simulation of emergency arrivals and ambulance movement trajectories, and the computation and visualization of performance metrics such as ambulance response time distributions. Data for the Rio de Janeiro Emergency Medical Service are available on the website. A user can upload emergency data for any Emergency Medical Service, and can then use the visualization tool to explore the uploaded data. A user can also use the statistical tools and/or the simulation tool with any of the dispatch methods provided, and can then use the visualization tool to explore the computational output. Future enhancements include the ability of a user to embed additional dispatch algorithms into the simulation; the tool can then be used to visualize the simulation results obtained with the newly embedded algorithms.

Artificial Intelligence (AI) is increasingly introduced into healthcare settings, yet its integration into fast-paced, high-pressure domains such as Emergency Medical Services (EMS) remains limited. EMS work unfolds across distinct stages, each characterized by different information needs, constraints, and forms of collaboration. Designing effective AI support requires understanding how AI interventions align with, or disrupt, EMS work across its different stages. We conducted semi-structured interviews with 25 EMS clinicians across the United States to examine how existing technologies currently support emergency services workflows and how they envision opportunities for, and concerns about, future AI-based support across different stages of emergency response. Our analysis reveals the cognitive, social, and procedural factors that enable EMS team coordination, which is grounded in situational awareness across distributed roles. EMS clinicians expressed significant concerns about how AI integration threatens this coordination mechanism across multiple dimensions: legal and privacy issues, technical reliability, contextual sensitivity, professional autonomy, and workflow friction.

Emergency medical services (EMS) response times are critical determinants of patient survival, yet existing approaches to spatial coverage analysis rely on discrete distance buffers or ad-hoc geographic information system (GIS) isochrones without theoretical foundation. This paper derives continuous spatial boundaries for emergency response from first principles using fluid dynamics (Navier-Stokes equations), demonstrating that response effectiveness decays exponentially with time: $τ(t) = τ_0 \exp(-κt)$, where $τ_0$ is baseline effectiveness and $κ$ is the temporal decay rate. Using 10,000 simulated emergency incidents from the National Emergency Medical Services Information System (NEMSIS), I estimate decay parameters and calculate critical boundaries $d^*$ where response effectiveness falls below policy-relevant thresholds. The framework reveals substantial demographic heterogeneity: elderly populations (85+) experience 8.40-minute average response times versus 7.83 minutes for younger adults (18-44), with 33.6\% of poor-access incidents affecting elderly populations despite representing 5.2\% of the sample. Non-parametric kernel regression validation confirms exponential decay

Emergency Medical Technicians (EMTs) operate in high-pressure environments, making rapid, life-critical decisions under heavy cognitive and operational loads. We present EMSGlass, a smart-glasses system powered by EMSNet, the first multimodal multitask model for Emergency Medical Services (EMS), and EMSServe, a low-latency multimodal serving framework tailored to EMS scenarios. EMSNet integrates text, vital signs, and scene images to construct a unified real-time understanding of EMS incidents. Trained on real-world multimodal EMS datasets, EMSNet simultaneously supports up to five critical EMS tasks with superior accuracy compared to state-of-the-art unimodal baselines. Built on top of PyTorch, EMSServe introduces a modality-aware model splitter and a feature caching mechanism, achieving adaptive and efficient inference across heterogeneous hardware while addressing the challenge of asynchronous modality arrival in the field. By optimizing multimodal inference execution in EMS scenarios, EMSServe achieves 1.9x -- 11.7x speedup over direct PyTorch multimodal inference. A user study evaluation with six professional EMTs demonstrates that EMSGlass enhances real-time situational aware

Emergency Medical Services (EMS) responders often operate under time-sensitive conditions, facing cognitive overload and inherent risks, requiring essential skills in critical thinking and rapid decision-making. This paper presents CognitiveEMS, an end-to-end wearable cognitive assistant system that can act as a collaborative virtual partner engaging in the real-time acquisition and analysis of multimodal data from an emergency scene and interacting with EMS responders through Augmented Reality (AR) smart glasses. CognitiveEMS processes the continuous streams of data in real-time and leverages edge computing to provide assistance in EMS protocol selection and intervention recognition. We address key technical challenges in real-time cognitive assistance by introducing three novel components: (i) a Speech Recognition model that is fine-tuned for real-world medical emergency conversations using simulated EMS audio recordings, augmented with synthetic data generated by large language models (LLMs); (ii) an EMS Protocol Prediction model that combines state-of-the-art (SOTA) tiny language models with EMS domain knowledge using graph-based attention mechanisms; (iii) an EMS Action Recogn

Minimizing response times to meet legal requirements and serve patients in a timely manner is crucial for Emergency Medical Service (EMS) systems. Achieving this goal necessitates optimizing operational decision-making to efficiently manage ambulances. Against this background, we study a centrally controlled EMS system for which we learn an online ambulance dispatching and redeployment policy that aims at minimizing the mean response time of ambulances within the system by dispatching an ambulance upon receiving an emergency call and redeploying it to a waiting location upon the completion of its service. We propose a novel combinatorial optimization-augmented machine learning pipeline that allows to learn efficient policies for ambulance dispatching and redeployment. In this context, we further show how to solve the underlying full-information problem to generate training data and propose an augmentation scheme that improves our pipeline's generalization performance by mitigating a possible distribution mismatch with respect to the considered state space. Compared to existing methods that rely on augmentation during training, our approach offers substantial runtime savings of up t

CONTEXT: Helicopter emergency medical services and their possible effect on outcomes for traumatically injured patients remain a subject of debate. Because helicopter services are a limited and expensive resource, a methodologically rigorous investigation of its effectiveness compared with ground emergency medical services is warranted. OBJECTIVE: To assess the association between the use of helicopter vs ground services and survival among adults with serious traumatic injuries. DESIGN, SETTING, AND PARTICIPANTS: Retrospective cohort study involving 223,475 patients older than 15 years, having an injury severity score higher than 15, and sustaining blunt or penetrating trauma that required transport to US level I or II trauma centers and whose data were recorded in the 2007-2009 versions of the American College of Surgeons National Trauma Data Bank. INTERVENTIONS: Transport by helicopter or ground emergency services to level I or level II trauma centers. MAIN OUTCOME MEASURES: Survival to hospital discharge and discharge disposition. RESULTS: A total of 61,909 patients were transported by helicopter and 161,566 patients were transported by ground. Overall, 7813 patients (12.6%) transported by helicopter died compared with 17,775 patients (11%) transported by ground services. Before propensity score matching, patients transported by helicopter to level I and level II trauma centers had higher Injury Severity Scores. In the propensity score-matched multivariable regression model, for patients transported to level I trauma centers, helicopter transport was associated with an improved odds of survival compared with ground transport (odds ratio [OR], 1.16; 95% CI, 1.14-1.17; P < .001; absolute risk reduction [ARR], 1.5%). For patients transported to level II trauma centers, helicopter transport was associated with an improved odds of survival (OR, 1.15; 95% CI, 1.13-1.17; P < .001; ARR, 1.4%). A greater proportion (18.2%) of those transported to level I trauma centers by helicopter were discharged to rehabilitation compared with 12.7% transported by ground services (P < .001), and 9.3% transported by helicopter were discharged to intermediate facilities compared with 6.5% by ground services (P < .001). Fewer patients transported by helicopter left level II trauma centers against medical advice (0.5% vs 1.0%, P < .001). CONCLUSION: Among patients with major trauma admitted to level I or level II trauma centers, transport by helicopter compared with ground services was associated with improved survival to hospital discharge after controlling for multiple known confounders.

In 2020, California required San Francisco to consider equity in access to resources such as housing, transportation, and emergency services as it re-opened its economy post-pandemic. Using a public dataset maintained by the San Francisco Fire Department of every call received related to emergency response from January 2003 to April 2021, we calculated the response times and distances to the closest of 48 fire stations and 14 local emergency rooms. We used logistic regression to determine the probability of meeting the averages of response time, distance from a fire station, and distance to an emergency room based on the median income bracket of a ZIP code based on IRS statement of income data. ZIP codes in the lowest bracket ($25,000-$50,000 annually) consistently had the lowest probability of meeting average response metrics. This was most notable for distances to emergency rooms, where calls from ZIP codes in the lowest income bracket had an 11.5% chance of being within the city's average distance (1 mile) of an emergency room, while the next lowest probability (for the income bracket of $100,000-$200,000 annually) was 75.9%. As San Francisco considers equity as a part of Califo

Introduction Little is known about the existence, distribution, and characteristics of Emergency Medical Services (EMS) systems in Africa, or the corresponding epidemiology of prehospital illness and injury. METHODS: A survey was conducted between 2013 and 2014 by distributing a detailed EMS system questionnaire to experts in paper and electronic versions. The questionnaire ascertained EMS systems' jurisdiction, operations, finance, clinical care, resources, and regulatory environment. The discovery of respondents with requisite expertise occurred in multiple phases, including snowball sampling, a review of published scientific literature, and a rigorous search of the Internet. RESULTS: The survey response rate was 46%, and data represented 49 of 54 (91%) African countries. Twenty-five EMS systems were identified and distributed among 16 countries (30% of African countries). There was no evidence of EMS systems in 33 (61%) countries. A total of 98,574,731 (8.7%) of the African population were serviced by at least one EMS system in 2012. The leading causes of EMS transport were (in order of decreasing frequency): injury, obstetric, respiratory, cardiovascular, and gastrointestinal complaints. Nineteen percent of African countries had government-financed EMS systems and 26% had a toll-free public access telephone number. Basic emergency medical technicians (EMTs) and Basic Life Support (BLS)-equipped ambulances were the most common cadre of provider and ambulance level, respectively (84% each). CONCLUSION: Emergency Medical Services systems exist in one-third of African countries. Injury and obstetric complaints are the leading African prehospital conditions. Only a minority (<9.0%) of Africans have coverage by an EMS system. Most systems were predominantly BLS, government operated, and fee-for-service. Mould-Millman NK , Dixon JM , Sefa N , Yancey A , Hollong BG , Hagahmed M , Ginde AA , Wallis LA . The state of Emergency Medical Services (EMS) systems in Africa. Prehosp Disaster Med. 2017;32(3):273-283.

How can we meet the special needs of children for emergency medical services (EMS) when today's EMS systems are often unprepared for the challenge? This comprehensive overview of EMS for children (EMS-C) provides an answer by presenting a vision for tomorrow's EMS-C system and practical recommendations for attaining it. Drawing on many studies and examples, the volume explores why emergency care for children--from infants through adolescents--must differ from that for adults and describes what seriously ill or injured children generally experience in today's EMS systems. The book points the way to integrating EMS-C into current emergency programs and into broader aspects of health care for children. It gives recommendations for ensuring access to emergency care through the 9-1-1 system; training health professionals, from paramedics to physicians; educating the public; providing proper equipment, protocols, and referral systems; improving communications among EMS-C providers; enhancing data resources and expanding research efforts; and stimulating and supporting leadership in EMS-C at the federal and state levels. For those already deeply involved in EMS efforts, this volume is a convenient, up-to-date, and comprehensive source of information and ideas. More importantly, for anyone interested in improving the emergency services available to children--emergency care professionals from emergency medical technicians to nurses to physicians, hospital and EMS administrators, public officials, health educators, children's advocacy groups, concerned parents and other responsible adults--this timely volume provides a realistic plan for action to link EMS-C system components into a workable structure that will better serve all of the nation's children.

OBJECTIVE: To evaluate the impact of adding first-responder defibrillation by fire-fighters to an existing advanced life-support emergency medical services system. DESIGN: Nonrandomized, controlled clinical trial with periodic crossover. SETTING: Memphis, Tenn, a city of 610,337 people, which is served by a fire department-based emergency medical services system. All city ambulances provide advanced life support. PATIENTS: Adult victims of out-of-hospital cardiac arrest due to heart disease. INTERVENTION: Twenty of 40 participating engine companies were equipped with an automated external defibrillator and ordered to apply it immediately in all cases of cardiac arrest. The other 20 companies were ordered to start cardiopulmonary resuscitation (CPR) immediately and wait for paramedics to arrive. Every 75 days, group roles were reversed. Care otherwise proceeded according to 1986 American Heart Association guidelines. MAIN OUTCOME MEASURES: Return of spontaneous circulation in the field, survival to hospital admission, survival to hospital discharge, and neurological status at discharge. RESULTS: During the 39-month study interval, 879 patients were treated by a project engine company. Four hundred thirty-one (49%) of these were found in ventricular fibrillation. Bystander CPR was started in only 12% of cases. Overall, firefighters reached the scene a mean of 2.5 minutes faster than simultaneously dispatched paramedics. Although our automated external defibrillators proved to be reliable and efficacious for terminating ventricular fibrillation and pulseless ventricular tachycardia, patients treated by an automated external defibrillator-equipped engine company were no more likely than CPR-treated controls to be resuscitated (32% vs 34%, respectively), to survive to hospital admission (31% vs 29%), or to survive to hospital discharge (14% vs 10%). Neurological outcomes were also similar in the two treatment groups. CONCLUSIONS: In a fast-response, urban emergency medical services system served by paramedics, the impact of adding first-responder defibrillation appears to be small. Early defibrillation alone cannot overcome low community rates of bystander CPR. Careful attention to every link in the "chain of survival" is needed to achieve optimal rates of survival after cardiac arrest.