Emergency Medical Service Center Research Articles

Implementation of basic life support education for the lay public in China: barriers, enablers, and possible solutions.

Education for the lay public in basic life support (BLS) is critical for increasing bystander cardiopulmonary resuscitation (CPR) rates and improving survival from out-of-hospital cardiac arrest (OHCA). Despite years of implementation, the BLS training rate in China has remained modest. The aim of this study was to investigate the factors influencing the implementation of BLS training programs in emergency medical service (EMS) centers in China and to identify specific barriers and enablers. Qualitative interviews were conducted with key informants from 40 EMS centers in Chinese cities. The participants included 11 directors/deputy directors, 24 training department leaders, and 5 senior trainers. The interview guide was based on the Exploration, Preparation, Implementation, Sustainment (EPIS) framework. Thematic content analysis was used to identify themes and patterns across the interviews. We identified 16 factors influencing the implementation of BLS training programs encompassing the outer content, inner context, innovation and bridging factors. Some factors acted as either barriers or enablers at different EPIS stages. The main implementation barriers included limited external leadership, insufficient government investment, low public awareness, a shortage of trainers, an absence of incentives, an absence of authoritative courses and guidelines, a lack of qualification to issue certificates, limited academic involvement, and insufficient publicity. The main enablers were found to be supportive government leaders, strong public demand, adequate resources, program champions, available high-quality courses of high fitness within the local context, the involvement of diverse institutions, and effective publicity and promotion. Our findings emphasize the diversity of stakeholders, the complexity of implementation, and the need for localization and co-construction when conducting BLS training for lay public in city EMS centers. Improvements can be made at the national level, city level, and EMS institutional level to boost priority and awareness, promote legislation and policies, raise sustainable resources, and enhance the technology of BLS courses.

A decomposition-based multiobjective evolutionary algorithm using Simulated Annealing for the ambulance dispatching and relocation problem during COVID-19

The outbreak of the COVID-19 epidemic has had a significant impact in increasing the number of emergency calls, which causes significant problems to emergency medical services centers (EMS) in many countries around the world, such as Saudi Arabia, which attracts a huge number of pilgrims during pilgrimage seasons. Among these issues, we address real-time ambulance dispatching and relocation problems (real-time ADRP). This paper proposes an improved MOEA/D algorithm using Simulated Annealing (G-MOEA/D-SA) to handle the real-time ADRP issue. The simulated annealing (SA) seeks to obtain optimal routes for ambulances to cover all emergency COVID-19 calls through the implementation of convergence indicator based dominance relation (CDR). To prevent the loss of good solutions once they are found in the G-MOEA/D-SA algorithm, we employ an external archive population to store the non-dominated solutions using the epsilon dominance relationship. Several experiments are conducted on real data collected from Saudi Arabia during the Covid-19 pandemic to compare our algorithm with three relevant state-of-art algorithms including MOEA/D, MOEA/D-M2M and NSGA-II. Statistical analysis of the comparative results obtained using ANOVA and Wilcoxon test demonstrate the merits and the outperformance of our G-MOEA/D-SA algorithm.

Análisis de una red de atención al IAMCEST: impacto pronóstico del tipo de primer contacto médico

Introduction and objectivesPrognosis in ST-elevation myocardial infarction (STEMI) is determined by delay in primary percutaneous coronary intervention (PPCI). The impact of first medical contact (FMC) facility type on reperfusion delays and mortality remains controversial. MethodsWe performed a prospective registry of primary coronary intervention (PCI)-treated STEMI patients (2010-2020) in the Codi Infart STEMI network. We analyzed 1-year all-cause mortality depending on the FMC facility type: emergency medical service (EMS), community hospital (CH), PCI hospital (PCI-H), or primary care center (PCC). ResultsWe included 18 332 patients (EMS 34.3%; CH 33.5%; PCI-H 12.3%; PCC 20.0%). Patients with Killip-Kimball classes III-IV were: EMS 8.43%, CH 5.54%, PCI-H 7.51%, PCC 3.76% (P <.001). All comorbidities and first medical assistance complications were more frequent in the EMS and PCI-H groups (P <.05) and were less frequent in the PCC group (P <.05 for most variables). The PCI-H group had the shortest FMC-to-PCI delay (median 82 minutes); the EMS group achieved the shortest total ischemic time (median 151 minutes); CH had the longest reperfusion delays (P <.001). In an adjusted logistic regression model, the PCI-H and CH groups were associated with higher 1-year mortality, OR, 1.22 (95%CI, 1.00-1.48; P=.048), and OR, 1.17 (95%CI 1.02-1.36; P=.030), respectively, while the PCC group was associated with lower 1-year mortality than the EMS group, OR, 0.71 (95%CI 0.58-0.86; P <.001). ConclusionsFMC with PCI-H and CH was associated with higher adjusted 1-year mortality than FMC with EMS. The PCC group had a much lower intrinsic risk and was associated with better outcomes despite longer revascularization delays.

Performance analysis of a STEMI network: prognostic impact of the type of first medical contact facility

Introduction and objectivesPrognosis in ST-elevation myocardial infarction (STEMI) is determined by delay in primary percutaneous coronary intervention (PPCI). The impact of first medical contact (FMC) facility type on reperfusion delays and mortality remains controversial. MethodsWe performed a prospective registry of primary coronary intervention (PCI)-treated STEMI patients (2010-2020) in the Codi Infart STEMI network. We analyzed 1-year all-cause mortality depending on the FMC facility type: emergency medical service (EMS), community hospital (CH), PCI hospital (PCI-H), or primary care center (PCC). ResultsWe included 18 332 patients (EMS 34.3%; CH 33.5%; PCI-H 12.3%; PCC 20.0%). Patients with Killip-Kimball classes III-IV were: EMS 8.43%, CH 5.54%, PCI-H 7.51%, PCC 3.76% (P <.001). All comorbidities and first medical assistance complications were more frequent in the EMS and PCI-H groups (P <.05) and were less frequent in the PCC group (P <.05 for most variables). The PCI-H group had the shortest FMC-to-PCI delay (median 82 minutes); the EMS group achieved the shortest total ischemic time (median 151 minutes); CH had the longest reperfusion delays (P <.001). In an adjusted logistic regression model, the PCI-H and CH groups were associated with higher 1-year mortality, OR, 1.22 (95%CI, 1.00-1.48; P=.048), and OR, 1.17 (95%CI 1.02-1.36; P=.030), respectively, while the PCC group was associated with lower 1-year mortality than the EMS group, OR, 0.71 (95%CI 0.58-0.86; P <.001). ConclusionsFMC with PCI-H and CH was associated with higher adjusted 1-year mortality than FMC with EMS. The PCC group had a much lower intrinsic risk and was associated with better outcomes despite longer revascularization delays.

Burnout among Japanese emergency medicine physicians: A multicentric questionnaire study.

Burnout negatively affects the wellness and performance of emergency physicians (EPs). This study aimed to clarify the actual prevalence of burnout and its associated factors among Japanese EPs. We conducted a cross-sectional questionnaire study of selected 27 Japanese emergency departments (EDs). We examined the Maslach Burnout Inventory-Human Services Survey score and its associations with ED-level- and EP-level factors in a multivariable analysis. A total of 267 EPs (81.9%) completed survey. Of these, 43 EPs (16.1%) scored severe emotional exhaustion (EE), 53 (19.8%) scored severe depersonalization (DP), and 179 (67.0%) scored severe personal accomplishment (PA), and 24 (8.9%) scored severely in all three domains. In our multivariable analysis, emergency medical service centers were associated with severe PA scores (odds ratio [OR], 10.56; 95% confidence interval [CI], 1.78-62.66; p = 0.009). A 3 to 6 hour-sleep period was associated with severe EE scores (OR, 2.04; 95% CI, 1.04-3.98; p = 0.036), and EPs in their 20s were associated with severe DP scores (OR, 7.37; 95% CI, 1.41-38.38; p = 0.018). Our results suggest that 8.9% of Japanese EPs are in higher degrees of burnout. In particular, Japanese EPs scored more severely on PA. To avoid burnout in Japanese EPs, it is important to improve the working environment by ensuring more than 6 h of sleep, providing more support for young EPs, and taking effective action to combat low EP self-esteem.

Design and implementation of a smart Internet of Things chest pain center based on deep learning.

The data input process for most chest pain centers is not intelligent, requiring a lot of staff to manually input patient information. This leads to problems such as long processing times, high potential for errors, an inability to access patient data in a timely manner and an increasing workload. To address the challenge, an Internet of Things (IoT)-driven chest pain center is designed, which crosses the sensing layer, network layer and application layer. The system enables the construction of intelligent chest pain management through a pre-hospital app, Ultra-Wideband (UWB) positioning, and in-hospital treatment. The pre-hospital app is provided to emergency medical services (EMS) centers, which allows them to record patient information in advance and keep it synchronized with the hospital's database, reducing the time needed for treatment. UWB positioning obtains the patient's hospital information through the zero-dimensional base station and the corresponding calculation engine, and in-hospital treatment involves automatic acquisition of patient information through web and mobile applications. The system also introduces the Bidirectional Long Short-Term Memory (BiLSTM)-Conditional Random Field (CRF)-based algorithm to train electronic medical record information for chest pain patients, extracting the patient's chest pain clinical symptoms. The resulting data are saved in the chest pain patient database and uploaded to the national chest pain center. The system has been used in Liaoning Provincial People's Hospital, and its subsequent assistance to doctors and nurses in collaborative treatment, data feedback and analysis is of great significance.

Modeling and Optimization for Emergency Medical Services Network

Ambulance offload delays have become a challenging concern for emergency healthcare service providers. These delays often occur when the number of patients in the emergency department (ED) exceed the designed capacity such that ED cannot accept an incoming patient immediately, thereby forcing the ambulance and crew to wait with the patient until a bed becomes available. In this paper, we analyze and optimize the emergency medical services network, including ambulance stations and EDs. The objective is to reduce ambulance offload delays and lessen the congestion of EDs. To this end, we first build a continuous-time Markov chain to characterize this network analytically. Next, from the perspectives of both ambulance stations and EDs, we develop resource configuration and optimization models for this network. We investigate the reasons for ED overcapacity and ambulance offload delays. Finally, we design an effective approach to reconfigure the resources in the emergency medical services network, leading to a new and better equilibrium. Note to Practitioners—This article is motivated by our collaborations with the Emergency Medical Service Center (also called 120 Center) and several hospitals in Shanghai, China. The Emergency Medical Service Center and ED of hospitals are the frontlines of healthcare services in Shanghai. They provide medical treatment services for acutely ill and injured patients, so the operation of this system is critical to the health of such patients. Today, the ambulance offloading delay poses a challenge to the Emergency Medical Service Center, as it reduces the usage of ambulances and crews, as well as putting patients at risk. Meanwhile, the EDs sometimes suffer from bed shortages and overcrowding. Emergency Medical Service Centers and hospitals are both striving to improve the performance of this system. We analyze the network, including both the ambulance station (AS) and ED, and formulate a continuous-time Markov chain model to describe the network states. Then, we propose two optimization models from both AS and ED perspectives with a series of approximation methods to overcome computational difficulties. We obtain the equilibrium through joint optimization of AS and ED and demonstrate some valuable insights for managing ambulances and beds in the ED. Methods presented in this article may help decision-makers in emergency medical services systems.

Persistent/Late-Onset Complications of COVID-19 in General Population: A Cross-Sectional Study in Tehran, Iran.

ABSTRACTBackground: After recovery from acute phase of the COVID-19, some patients suffer from persistent/late-onset complications. The main objective of this study was to investigate the prevalence of such complications in a large scale of COVID-19 patients in Tehran, Iran.Methods: In this cross-sectional study, those patients who called Tehran emergency medical services center and were visited by the emergency medical technicians from 20 March 2020 until 21 September 2020 and diagnosed as a confirmed COVID-19 case were enrolled. The minimum required sample size was estimated 385 cases, and they were selected randomly. The patients were interviewed by phone at least 4 weeks since initiation of their symptoms. Using a pre-prepared checklist, made by an expert panel who were involved in management of COVID-19 patients, data were collected on the types and duration of the complications, clinical information, and factors which could interfere with developing the complications. All analyses were performed using STATA 16 software. The association of the prevalence of each complication with independent factor was assessed using Chi-square test (or Fisher’s exact test) for categorical variable, and the mean difference of numerical variables in the two groups (with and without complication) was assessed using independent t-test. Statistical significance was accepted at P value<0.05.Results: Four-hundred forty-seven patients participated in the study. Among our total population, 345 (77.2%) patients experienced at least one of the persistent/late-onset complications. Cardiopulmonary and then skin-related symptom categories were reported in 179 (40.0%) and 173 (38.7%) patients, respectively, and were the most prevalent persistent/late-onset complications. The associations of long term persistent/late-onset complications with older ages (P=0.04), female (P<0.001), psychological stress (P=0.01), and inadequate rest after illness (P<0.001) were significant.Conclusion: The findings of this study indicate that a significant number of patients will experience persistent/late-onset complications, both physically and mentally, after recovering from acute phase of COVID-19. Thus, physicians should have adequate resources and support to care for the patients to help them cope with the condition.

A mathematical optimization model for location Emergency Medical Service (EMS) centers using contour lines

Despite extensive research and efforts to optimize Emergency Medical Service (EMS) during the last four decades, there are still critical and fundamental challenges to study. Operational problems experienced during implementation of the proposed models result in the emergence of new concerns and the development of other models. This research examines the optimal location of emergency medical centers in order to offer faster and more efficient care. The purpose of this study is to offer a mathematical model for locating emergency medical centers with the goal of increasing both the quantity and quality of demand coverage. Then, by defining numerical examples, the behavior of the model is analyzed. The model is first solved in small dimensions using GAMS, and due to the np-hard nature of the model, it is then studied in large dimensions using a meta-heuristic algorithm, which uses a Genetic Algorithm (GA) in this paper. Finally, the graphs’ results are compared to each other. Our findings indicate that as the dimensions of the problem increase, GAMS loses its ability to solve the problem and the solution time by GA decreases compared to GAMS. Ultimately, in a numerical example, we used contour lines to analyze the data. EMS potential points follow these lines and serve as demand points. Given the model’s accuracy has been proven with various parameters, the proposed model can be used to both meet demand for emergency medical services and determine the optimal location of emergency medical care facilities.

Infection Control for a Carbapenem-Resistant Enterobacteriaceae Outbreak in an Advanced Emergency Medical Services Center

Background: A carbapenem-resistant Enterobacteriaceae (CRE) outbreak occurred in an advanced emergency medical service center [hereafter referred to as the intensive care unit (ICU)] between 2016 and 2017. Aim: Our objective was to evaluate the infection control measures for CRE outbreaks. Methods: CRE strains were detected in 16 inpatients located at multiple sites. Environmental cultures were performed and CRE strains were detected in 3 of 38 sites tested. Pulsed-field gel electrophoresis (PFGE), multilocus sequence typing (MLST), and detection of β-lactamase genes were performed against 25 CRE strains. Findings: Molecular typing showed the PFGE patterns of two of four Klebsiella pneumoniae strains were closely related and the same MLST (ST2388), and four of five Enterobacter cloacae strains were closely related and same MLST (ST252). Twenty-three of 25 CRE strains harbored the IMP-1 β-lactamase gene and 15 of 23 CRE strains possessed IncFIIA replicon regions. Despite interventions by the infection control team, new inpatients with the CRE strain continued to appear. Therefore, the ICU was partially closed and the inpatients with CRE were isolated, and the ICU staff was divided into two groups between inpatients with CRE and non-CRE strains to avoid cross-contamination. Although the occurrence of new cases dissipated quickly after the partial closure, a few months were required to eradicate the CRE outbreak. Conclusion: Our data suggest that the various and combined measures that were used for infection control were essential in stopping this CRE outbreak. In particular, partial closure to isolate the ICU and division of the ICU staff were effective.

Changes in COVID-19 IgM and IgG antibodies in emergency medical technicians (EMTs).

IntroductionSerologic testing can provide a safe and fast approach for assessing SARS-CoV-2 antibodies. These tests can be utilized as a complementary method in diagnosis and patients' follow-up, and can also be helpful in epidemiological studies. This study aimed to describe temporal changes in the incidence of COVID-19 IgM and IgG antibodies in emergency medical technicians (EMTs) within a specified time period.MethodsAll EMTs working for Tehran Emergency Medical Service (EMS) center during May to September 2020 were eligible for this study. Those EMTs who were suspected/probable/confirmed cases of COVID-19, based on WHO defined criteria and were willing to participate, entered the study. The EMTs underwent serology testing four weeks after the occurrence of exposure (in suspected cases) or onset of their symptoms (in probable/confirmed cases). Cases were further confirmed by RT-PCR and/or lung CT, and antibody testing was performed for the second and third time with 12-week intervals. Finger-stick blood sampling was utilized for the specimen collection in three different phases. Samples were then analyzed by a commercial immunochromatography-based kit for qualitative measurement of serum IgM and IgG antibodies against the COVID-19 S-protein antigen.ResultsTwo hundred eighty-four participants met the inclusion criteria; their mean age was 35.9 (SD = 7.6) years and consisted of 244 (85.9%) males. COVID-19 was confirmed in 169 out of 284 participants. Subsequently, 142 and 122 participants were included in phases 2 and 3 of the study, respectively. The number of seronegative patients exceeded seropositive ones in all three phases. At baseline, 162 (57%) patients were seronegative, 27 (9.5%) were only positive for IgG, 3 (1.1%) were only positive for IgM, and 92 (32.4%) were positive for both antibodies; Seventy-eight (54.9%) were seronegative, and 31 (21.8%) were positive for both antibodies in the second phase; These values were 85 (69.6%) and 8 (6.6%) for the third phase, respectively. Among the people who were positive IgG in the first phase (80 people), 56.3% were still positive in the second phase and 27.5% in both subsequent phases.ConclusionThe results of our study show that there is a significant reduction in COVID-19 antibody seropositivity over time.

Emergency Medical Technicians' Experiences of the Challenges of Prehospital Care Delivery During the COVID-19 Pandemic: A Qualitative Study.

Exploring emergency medical technicians' (EMTs) experiences of COVID-19 epidemic, help to identify the challenges they face in their daily work and develop strategies that address these challenges. This study aimed to explore EMTs' experiences of the challenges of prehospital care delivery during the COVID-19 pandemic. This qualitative study was conducted in March-July 2020 using conventional content analysis approach. Fifteen EMTs were purposively selected from the Emergency Medical Services (EMS) Center in Qom, Iran. For data collection, semi-structured interviews were conducted until data saturation was reached. EMTs' experiences of the challenges of prehospital care delivery during the COVID-19 pandemic were classified into three main categories including "restless society", "difficult care delivery conditions", and "unprepared organization". The emergent subcategories were "need for information", "limited perception of the COVID-19 risk", "obsessive use of disinfectants", "fear over the transmission of COVID-19 to self and others", "burnout due to heavy workload", "altered communication with hospital staff", "ethical conflicts", "lack of a definite treatment plan", "lack of protective equipment", "staff shortage due to the affliction of EMTs by COVID-19", and "inadequate support by authorities". During COVID-19 pandemics, EMTs face many challenges including emotional and occupational stress, social strains, risk of affliction by infections, heavy workload, and ethical conflicts and hence, experience difficulties in quality care delivery. Developing appropriate strategies, guidelines, and policies are needed to effectively manage these challenges and improve the quality of prehospital care delivery in COVID-19 epidemic.

Assessment of ambulance services performance by queuing theory, at the Center for Disaster and Emergency Management: A descriptive-analytical study.

The emergency departments of the hospitals and emergency medical services (EMSs) centers have a critical role for providing urgent medical care for patients. The statistical data of the present study were provided by the EMS headquarters of the city of Isfahan, from August to November 2017. The findings showed that on average, 210 missions were accomplished each day by the emergency call center, with an average duration of about 53 minutes, for each mission. In addition, the average time for response time (the time between a call and dispatch of the ambulance) was less than 3 minutes, and the average time for arrival time (the time between request of ambulance and the arrival to the scene) was 8.1 minutes. Adequacy of current number of ambulances and staff is evaluated. Considering an average of 8.1 minutes for arrival time, we conclude that the EMS of Isfahan is within an acceptable range, compared to the international standards. In fact, it is shown that the infrastructures of EMS system including ambulance fleets, staff, and equipment are sufficient, and as an effective step for reducing the total time of the mission, the EMS has to operate seamlessly with the patient's admission process in hospitals. Information such as workload hours, availability of resources and staff, etc. ought to be shared between the EMS and the hospital.

Effect of a Mobile App on Prehospital Medication Errors During Simulated Pediatric Resuscitation

Medication errors are a leading cause of injury and avoidable harm, affecting millions of people worldwide each year. Children are particularly susceptible to medication errors, but innovative interventions for the prevention of these errors in prehospital emergency care are lacking. To assess the efficacy of an evidence-based mobile app in reducing the occurrence of medication errors compared with conventional preparation methods during simulated pediatric out-of-hospital cardiac arrest scenarios. This nationwide, open-label, multicenter, randomized clinical trial was conducted at 14 emergency medical services centers in Switzerland from September 3, 2019, to January 21, 2020. The participants were 150 advanced paramedics with drug preparation autonomy. Each participant was exposed to a 20-minute, standardized, fully video-recorded, realistic pediatric out-of-hospital cardiac arrest cardiopulmonary resuscitation scenario concerning an 18-month-old child. Participants were tested on sequential preparations of 4 intravenous emergency drugs of varying degrees of preparation difficulty (epinephrine, midazolam, 10% dextrose, and sodium bicarbonate). Participants were randomized (1:1 ratio) to the support of an app designed to assist with pediatric drug preparation (intervention; n = 74) or to follow conventional drug preparation methods without assistance (control; n = 76). The primary outcome was the rate of medication errors, defined as a failure in drug preparation according to predefined, expert consensus-based criteria. Logistic regression models with mixed effects were used to assess the effect of the app on binary outcomes. Secondary outcomes included times to drug preparation and delivery, assessed with linear regression models with mixed effects. In total, 150 advanced paramedics (mean [SD] age, 35.6 [7.2] years; 101 men [67.3%]; mean [SD] time since paramedic certification, 8.0 [6.2] years) participated in the study and completed 600 drug preparations. Of 304 preparations delivered using the conventional method, 191 (62.8%; 95% CI, 57.1%-68.3%) were associated with medication errors compared with 17 of 296 preparations delivered using the app (5.7%; 95% CI, 3.4%-9.0%). When accounting for repeated measures, with the app, the proportion of medication errors decreased in absolute terms by 66.5% (95% CI, 32.6%-83.8%; P < .001), the mean time to drug preparation decreased by 40 seconds (95% CI, 23-57 seconds; P < .001), and the mean time to drug delivery decreased by 47 seconds (95% CI, 27-66 seconds; P < .001). The risk of medication errors varied across drugs with conventional methods (19.7%-100%) when compared with the app (4.1%-6.8%). Compared with conventional methods, the use of a mobile app significantly decreased the rate of medication errors and time to drug delivery for emergency drug preparation in a prehospital setting. Dedicated mobile apps have the potential to improve medication safety and change practices in pediatric emergency medicine. ClinicalTrials.gov Identifier: NCT03921346.

AMBtalk: A Cardiovascular IoT Device for Ambulance Applications.

Acute Coronary Syndrome (ACS) and other heart emergency events require immediate chest pain identification in the ambulance. Specifically, early identification and triage is required so that patients with chest pain can be quickly sent to a hospital with appropriate care facilities for treatment. In the traditional approach, ambulance personnel often use symptom checklists to examine the patient and make a quick decision for the target hospital. However, not every hospital has specialist facilities to handle such emergency cases. If the result of the subsequent cardiac enzyme test performed at the target hospital strongly suggests the occurrence of myocardial infarction, the patient may need to be sent to another hospital with specialist facilities, such as Percutaneous Coronary Intervention. The standard procedure is time consuming, which may result in delayed treatment and reduce patent survival rate. To resolve this issue, we propose AMBtalk (Ambulance Talk) for accurate, early ACS identification in an ambulance. AMBtalk provides real-time connection to hospital resources, which reduces the elapsed time for treatment, and therefore, improves the patient survival rate. The key to success for AMBtalk is the development of the AllCheck® Internet of Things (IoT) device, which can accurately and quickly provide cardiovascular parameter values for early ACS identification. The interactions between the AllCheck® IoT device, the emergency medical service center, the ambulance personnel and the hospital are achieved through the AMBtalk IoT server in the cloud network. AllCheck® outperforms the existing cardiovascular IoT device solutions for ambulance applications. The testing results of the AllCheck® device show 99% correlation with the results of the hospital reports. Due to its excellent performance in quick ACS identification, the AllCheck® device was awarded the 17th Taiwan Innovators Award in 2020.

Emergency numbers accessibility for disabled peoples’: Case of the Islamic Republic of Iran

An emergency is a serious, unexpected situation which may lead to injury, loss of life and damage to property and often needs urgent interventions. Emergency calls can bring urgent life-saving intervention in such situations. Although access to emergency lines for all persons of a society is one of the effectiveness indexes of this critical service, in most countries, these lines are not accessible for disabled people. This study examined the issue of emergency number accessibility for disabled people in the I.R. of Iran. Two persons who had been poisoned by carbon monoxide died because their deaf-mute father could not communicate with the Emergency Medical Service Center (EMSC). This led to the Emergency Medical Service Management Center (EMSMC), in collaboration with Iranian Society of Deaf People Family (ISDPF), developing a system that is a combination of short message system (SMS) and location-based information (LBI) to facilitate the communication of such disabled persons with EMSMCs. The system did not receive any emergency message until this report is provided. Because emergency call service has not been available for disabled people in Iran until now, emergency service organizations should take a proactive approach in developing a reliable and easy to use a method with the current technologies. These organizations should also provide information about the installed systems for end-users.

Relationship Between Nurses' Decision-Making Style and Their Disaster Response Competencies.

Nurses are the first respondents to the critical situations and therefore must be able to effectively manage the critical situations using their competencies. Given that the decision-making style under the stressful critical situations is an important component of the care process in these situations, this study was conducted with the aim of determining the relationship between decision-making style and nurses' disaster response competencies.This descriptive, analytical study was conducted in Shahr-e Kord city in 2018. A total of 300 nurses were selected from Ayatollah Kashani and Hajar hospitals by multistage sampling and from the Emergency Medical Services Center by the census method. Data were collected using the Disaster Nursing Competence Assessment and the decision-making style questionnaires and analyzed with SPSS 21 (IBM Corp, Armonk, NY).Most of the nurses used the intuitive decision-making style and the total score of disaster nursing competencies was 162.58 ± 22.70. Pearson's correlation coefficient indicated that there was a positive relation between decision-making style and nurses' disaster response competencies.The results show that decision-making style affects nurses' competencies for disaster response and provides evidence for the development of educational policies in disaster nursing education.

Factors, influencing medication errors in prehospital care: A retrospective observational study.

To determine the frequency of medication errors in prehospital care and to investigate the influencing factors – diagnostic agreement (DA), the medical educational status, the specialty, the approval for emergency medicine of the prehospital emergency physician, the patient age and sex and the time of deployment.We retrospectively reviewed 708 patients from 2013 to 2015, treated by the prehospital emergency physicians of the emergency medical service center Bad Belzig, Germany. The medication appropriateness was determined by a systematic comparison of the administered medication in prehospital deployments with the discharge diagnosis, according to current guidelines. The influencing factors were examined by univariate analysis of medication appropriateness (MA), using the χ2, the Mann–Whtiney U and the Welch tests. We calculated a cut-off value with the Youden index to predict absent MA, according to patients age. The significance level was P = .05.MA was absent in 220 of 708 patients (31.1%). In the case of present DA, MA was absent in 103 of 491 patients (20.9%). In the case of absent DA, MA was absent in 117 of 217 patients (53.9%) (P = .01). MA was absent in 82 of 227 patients (36.1%), treated by specialist and in 138 of 481 patients (28.7%), treated by resident physicians (P = .04). The calculated cut-off value to predict absent MA was 75.5 years. MA was absent in 100 of 375 patients (26.7%) of the younger patient age group (≤75.5 years), MA was absent 120 of 333 patients (36.0%) of the older patient age group (>75.5 years) (P = .01). Absent MA showed peak values (46.7%–60%) at night from 3 to 6 AM (P = .01) The other investigated factors had no influence on MA.The correctness of medication as a quality feature in prehospital care shows a necessity for improvement with a proportion of 31.1% medication errors. The correct diagnosis by the prehospital emergency physician and his rapid accumulation of experience had an impact on the correctness of medication in prehospital care. Elderly patients (75+ years) and nighttime prehospital deployments (3–6 AM) were identified as high risk for medication errors by the emergency physicians.

A Spatiotemporal Analysis of Heroin-Related Calls for Emergency Medical Services and Community-Health Centers in Boston, Massachusetts

Using a combination of data derived from the U.S. Census Bureau, the Substance Abuse and Mental Health Service Administration’s Behavioral Health Systems Locator and the Boston Police Department’s Incident Reports, this study examines the spatio-temporal distribution of calls for medical assistance following a heroin-related injury between 2015 and 2018. As well, an examination is conducted regarding the accessibility of Health Care Centers (HCCs) in relation to individuals in need of medical assistance. Distance-based measures of spatial association, including nearest neighbor and K-function analysis, were used to determine the clustering of calls at various spatial scales. Structural neighborhood characteristics (i.e., distance to the closest HCC) and physical and social vulnerability were used to predict the rate of calls for a heroin-related injury per 1,000 persons in the city of Boston using a spatial autoregressive model. HCC catchment areas for the set of medical emergency calls were created using Voronoi tessellations. Results showed that the average nearest neighbor distance (NND) of each call for medical assistance was approximately 187 m or .12 miles. Calls for assistance became more probable and increasingly more spatially concentrated over the study period. The K-function analysis revealed that the calls clustered at different spatial scales and in proximity to HCCs. Average distance to the nearest HCC and Household/Disability vulnerability were significantly associated with the census tract call rate per 1,000 persons. The average travel distance between the calls for medical assistance and the nearest HCC was 941 m, or just over a half-mile. Policy implications for the provision, through HCCs, of a focused and comprehensive community-based support system in a large urban city for individuals with serious drug problems are discussed in context.

Epidemiological Features of Injured Patients Examined by Tehran Emergency Medical Service Technicians.

Introduction:Knowledge of epidemiological aspects can be a useful guide in determining the resources for better prevention and management of injuries. There are some performed studies on this topic in Iran, based on the limited hospital database. However, to the best of our knowledge, there is not any survey based on the pre-hospital databaseObjective:The purpose of this study was to assess baseline characteristics of the traumatic patients according to the records of Tehran Emergency Medical Service (EMS) Center to present descriptive statistics of their epidemiological features.Method:This cross-sectional study was conducted retrospectively, using Tehran EMS center data registry. All traumatic patients examined by EMS in Tehran, Iran following call to emergency medical dispatcher were included. By reviewing the EMS technicians’ mission forms, required data were extracted. The mission form contains information such as age, sex, injured location, damage mechanism, accident location (home, workplace, street), time of call, the outcome of the patient’s ambulance mission and the results of the assessment of the technician, etc.Results:Totally, 56612 injured cases with the mean age of 33.1±15.6 years were examined by EMS during one-year study period of whom 80.4% were male. Crude Incidence Rate was 10.5 and 2.5 per 1000 in male and female, respectively. Traffic accident and then fall were the two most prevalent mechanism of injuries. All types of injuries were significantly more prevalent in males (P<0.001). Most injuries were in winter season with 15570 cases (27.5%). Car accident was prevalent in winter and other injuries were significantly prevalent in spring (P<0.001). The most frequent places of injuries occurred on main roads and streets (55.7%). All of the road-related injuries was prevalent in winter, whereas injuries in other places were prevalent in spring (P<0.001). Most of the cases (78.3%) were transferred to the health centers, but 20.7% did not consent to treatment and transmission. Only 222 cases (0.4%) died, that 95% was due to traffic accident. there was a significant relationship between the number of injured organs and the death; So that the highest death rate occurred for those with more than 5 injured organs (P <0.001).Conclusion:Based on the findings, traffic accident was the most frequent cause of trauma that led to visiting a traumatic patient by an EMS technician in Tehran, Iran. Injuries in all age groups were more prevalent in males, and the involvement of 5 or more injured organ had a significant relationship with mortality.