Ambulance Dispatch Research Articles

Intelligent contributions of the artificial orca algorithm for continuous problems and real-time emergency medical services.

The Artificial Orca Algorithm (AOA) is an existing swarm intelligence algorithm, empowered in this paper by two well-known mutation operators and opposition-based learning, yielding the novel methods Deep Self-Learning Artificial Orca Algorithm (DSLAOA), Opposition Deep Self-Learning Artificial Orca Algorithm (ODSLAOA), and Opposition Artificial Orca Learning Algorithm. The DSLAOA and ODSLAOA are based on the Cauchy and Gauss mutation operators. Their effectiveness is evaluated on both continuous and discrete problems. The suggested algorithms are tested and compared to seven recent state-of-the-art metaheuristics in the continuous context. The results demonstrate that, when compared to the other algorithms, DSLAOA based on the Cauchy operator is the most effective technique. After that, a specific real-world scenario involving emergency medical services in a dire situation is tackled. The Ambulance Dispatching and Emergency Calls Covering Problem is the addressed problem, and a mathematical formulation is made to model this issue. AOA, DSLAOAC, and DSLAOAG are tested and contrasted with a successful recent heuristic in this field. The experiments are run on real data, and the results show that the swarm approaches are effective and helpful in determining the resources required in this kind of emergency.

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.

Современные подходы к оказанию первой помощи при отравлениях и меры по повышению эффективности ее оказания

Summary. Investigation purposes – an analysis if modern approaches to the first aid (FA) provision in cases of poisoning; a researching of normative legal regulation of FA provision in the Russian Federation; a determination of measures of first aid provision improvement; creation of the project of universal algorithm of dispatching support of first aid in cases of poisonings. Material and methods of the investigation. Investigation materials – national and international publications about a first aid provision in cases of poisonings; international and national recommendations which characterize modern approaches to the FA provision in cases of poisonings; complexes of practical recommendations/protocols for ambulance dispatchers, including instructions for distance advising of injury witnesses on the provision of FA in cases of poisonings. Investigation results and their analysis. A review of modern principles and approaches to the FA provision is cases of poisonings based on the analysis of national and international FA recommendations was presented; Features of normative legal regulation of FA provision in cases of poisonings in the Russian Federation were analyzed; ways of FA provision effectivity improvement were determined. A practice of distance phone advising by emergency service dispatchers of an unskilled injury witnesses on the provision of FA is discussed as a perspective direction of improvement of FA provision in cases of poisonings; a project if universal Russian language algorithm for dispatcher support of FA in cases of poisonings was presented and now is offered for further discussion.

Urban-suburb disparities in pre-hospital emergency medical resources and response time among patients with out-of-hospital cardiac arrest: A mixed-method cross-sectional study.

To investigate (1) the association between pre-hospital emergency medical resources and pre-hospital emergency medical system (EMS) response time among patients with Out-of-hospital cardiac arrest (OHCA); (2) whether the association differs between urban and suburbs. Densities of ambulances and physicians were independent variables, respectively. Pre-hospital emergency medical system response time was dependent variable. Multivariate linear regression was used to investigate the roles of ambulance density and physician density in pre-hospital EMS response time. Qualitative data were collected and analyzed to explore reasons for the disparities in pre-hospital resources between urban areas and suburbs. Ambulance density and physician density were both negatively associated with call to ambulance dispatch time, with odds ratios (ORs) 0.98 (95% confidence interval [CI] 0.96-0.99; P = 0.001) and 0.97 (95% CI; 0.93-0.99; P < 0.001), respectively. ORs of ambulance density and physician density in association with total response time were 0.99 (95% CI: 0.97-0.99; P = 0.013) and 0.90 (95% CI: 0.86-0.99; P = 0.048). The effect of ambulance density on call to ambulance dispatch time in urban areas was 14% smaller than that in suburb areas and that on total response time in urban areas was 3% smaller than the effect in suburbs. Similar effects were identified for physician density on urban-suburb disparities in call to ambulance dispatch time and total response time. The main reasons summarized from stakeholders for a lack of physicians and ambulances in suburbs included low income, poor personal incentive mechanisms, and inequality in financial distribution of the healthcare system. Improving pre-hospital emergency medical resources allocation can reduce system delay and narrow urban-suburb disparity in EMS response time for OHCA patients.

Abstract WMP47: Low Sensitivity Of Widely Used Emergency Dispatch Algorithm For Thrombectomy Patients - Implications For Mobile Stroke Units

Introduction: Widely used emergency dispatch algorithms such as the Advanced Medical Priority Dispatch System (AMPDS) have limited diagnostic accuracy for prehospital diagnosis of stroke. With advent of mobile stroke units (MSU), this inaccuracy prevents optimal dispatch to patients who may benefit. Expedited endovascular thrombectomy (EVT) is a major contributor to net benefit of MSUs. We assessed the accuracy of AMPDS for recognizing stroke in thrombectomy patients in the Australian state of Victoria. Methods: We included consecutive patients accepted for EVT (direct and secondary transfer) to The Royal Melbourne Hospital from 2007-2021 in whom linked AMPDS dispatch codes could be obtained from Ambulance Victoria. The primary outcome was the proportion of cases dispatched as stroke vs non-stroke with subgroup analyses of the effect of baseline clinical severity, metropolitan vs rural dispatch and time to thrombectomy. Chi square and Mann Whitney tests were used as appropriate. Results: A total of n=618 patients were included with baseline NIHSS 16 (IQR 10-20). Of these, only 62% (95% CI 58-66) were initially dispatched as suspected stroke, with the most common non-stroke diagnoses being “Unconscious/Fainting” (19.2%) and “Falls” (6.9%). Those with a higher baseline severity (NIHSS ≥10) were less likely to be classified as stroke than those with lower severity (59% vs 76%, p&lt;0.001), while no difference was found between metropolitan and rural patients (p=0.066). Overall, no significant time differences were found between stroke and non-stroke dispatches for ambulance dispatch to arterial access (median 208 vs 216 min, p=0.593) or hospital arrival to arterial access (median 42 vs 42 min, p=0.851). However, only 32 patients were treated on the MSU, which commenced operation November 2017. Conclusions: Almost 40% of thrombectomy patients did not receive an initial AMPDS dispatch of suspected stroke and those with higher baseline severity were more likely to be misclassified. Although time to thrombectomy was not significantly different between stroke vs non-stroke dispatches, MSU treatment was under-represented. Our findings have implications for emergency medical services and particularly mobile stroke units which rely on accurate stroke dispatch.

Building a Machine Learning-based Ambulance Dispatch Triage Model for Emergency Medical Services.

In charge of dispatching the ambulances, Emergency Medical Services (EMS) call center specialists often have difficulty deciding the acuity of a case given the information they can gather within a limited time. Although there are protocols to guide their decision-making, observed performance can still lack sensitivity and specificity. Machine learning models have been known to capture complex relationships that are subtle, and well-trained data models can yield accurate predictions in a split of a second. In this study, we proposed a proof-of-concept approach to construct a machine learning model to better predict the acuity of emergency cases. We used more than 360,000 structured emergency call center records of cases received by the national emergency call center in Singapore from 2018 to 2020. Features were created using call records, and multiple machine learning models were trained. A Random Forest model achieved the best performance, reducing the over-triage rate by an absolute margin of 15% compared to the call center specialists while maintaining a similar level of under-triage rate. The model has the potential to be deployed as a decision support tool for dispatchers alongside current protocols to optimize ambulance dispatch triage and the utilization of emergency ambulance resources.

Chest pain: a review of current principles and approaches to first aid

Chest pain is a typical manifestation of acute myocardial ischemia. The likelihood of death in myocardial infarction increases significantly as the pain to hospital times increase, Therefore, timely recognition of this symptom as a possible manifestation of ischemia, calling an ambulance and first aid before the arrival of ambulance team can play a vital role in saving lives. A review of modern principles and rules for first aid to patients with chest pain is presented, based on an analysis of international and national guidelines. We demonstrated the need and identified directions for improving the organization of first aid in this condition in Russia, as well as analyzed approaches to remote questioning and provision of instructions on first aid for chest pain by ambulance dispatchers by phone, Based on the comparative analysis of dispatcher guidelines and protocols and international guidelines on first aid for chest pain, a universal Russian-language dispatcher algorithm for remote care for chest pain has been developed, which is proposed for discussion and further testing as a potential component of a unified domestic dispatcher support program for first aid.

Optimizing Operation Time and Travel Distance for Motorcycle Ambulances in Emergency Medical Services.

The motorcycle ambulance is used for quick access to patients. The response time to reach the patient takes less time than with a van ambulance. Moreover, accidents involving ambulances tend to be higher. However, at present, there is no study regarding the appropriate situation used of motorcycle ambulances in Emergency Medical Services (EMS) in Thailand. This study aims to optimize the travel distance and the operation time of motorcycle ambulances used. This study was a prospective, randomized controlled study at the EMS unit of Srinagarind Hospital, Thailand. The data collection period was from November 2021 through May 2022. All data involving dispatch of both ambulances in need were collected. A total of 2,398 cases of EMS operation were examined. The mean age of the patients in the motorcycle ambulance group was 42.5 (SD = 6.5) years, and 51.3% (n = 616) were male. The response time for motorcycle ambulances and van ambulances during the operation time between 6:00am-9:00am was 6.2 minutes and 9.1 minutes, respectively. The response times for motorcycle ambulances and van ambulances regarding distance traveled from 0-5km were 4.2 minutes and 7.5 minutes, respectively (P <.001); distance traveled from 5-10km were 6.3 minutes and 8.2 minutes, respectively (P = .010). The motorcycle ambulance can reach patients faster than the ambulance at the operation time from 6:00am-9:00am and 3:00pm-6:00pm. This study focused on the distance less than 10 kilometers.

Effect modification by temperature on the association between O3 and emergency ambulance dispatches in Japan: A multi-city study

Numerous epidemiological studies have reported that ozone (O3) and temperature are independently associated with health outcomes, but modification of the effects of O3 on health outcomes by temperature, and vice versa, has not been fully described. This study aimed to investigate effect modification by temperature on the association between O3 and emergency ambulance dispatches (EADs) in Japan. Data on daily air pollutants, ambient temperature, and EADs were obtained from eight Japanese cities from 2007 to 2015. A distributed lag non-linear model combined with Poisson regression was performed with temperature as a confounding factor and effect modifier to estimate the effects of O3 on EADs at low (<25th percentile), moderate (25th–75th percentile), and high (>75th percentile) temperature for each city. The estimates obtained from each city were pooled by random-effects meta-analysis. When temperature was entered as a confounder, the estimated effects of O3 on EADs for all acute, cardiovascular, and respiratory illnesses were largest at lag 0 (current-day lag). Therefore, this lag was used to further estimate the effects of O3 on EADs in each temperature category. The estimated effects of O3 on EADs for all acute, cardiovascular, and respiratory illnesses in all eight Japanese cities increased with increasing temperature. Specifically, a 10 ppb increase in O3 was associated with 0.80 % (95 % CI: 0.25 to 1.35), 0.19 % (95 % CI: −0.85 to 1.25), and 1.14 % (95 % CI: −0.01 to 2.31) increases in the risk of EADs for all acute, cardiovascular, and respiratory illnesses, respectively, when city-specific daily temperature exceeded the 75th percentile. Our findings suggest that the association between O3 and EADs for all acute, cardiovascular, and respiratory illnesses is the highest during high temperature. Finding of this study can be used to develop potential mitigation measures against O3 exposure in high temperature environment to reduce its associated adverse health effects.

Study of prehospital video telehealth for callers with mental health-related complaints

BackgroundPatients with mental health-related complaints are a key driver of increasing emergency medical service (EMS) demand; however, they require minimal intervention by EMS personnel. We describe the outcomes of a...

Ten Years of the Nepal Ambulance Service: Successful and Sustainable Efforts.

We describe the evolution of the nonprofit Nepal Ambulance Service (NAS) in a narrative of its 10-y history, presenting geographical, social, cultural, and financial considerations that permeated the development of NAS. We gathered narrative information from the NAS leadership and partners to detail key organizational considerations regarding the implementation and maintenance of the prehospital system in Nepal. We describe the response of NAS to the 2015 earthquake and summarize transport data for 6 mo before and 6 mo after the event. The data collected included the date and time of calls received, time to ambulance dispatch, on-scene time, time to arrival at the hospital, time until the ambulance crew was back in service, patient age and sex, chief complaints, and work shift time of the ambulance crew. To characterize the time to response and transport after the 2015 earthquake, we present the means and standard deviations of the time intervals. There was an overall increase in calls and, specifically, trauma-related calls after the 2015 earthquake. The time from a call placed to dispatch was stable, approximately 2 min, throughout the period, whereas the time from dispatch to the scene and arrival at the scene varied widely. We discuss the response to coronavirus disease 2019 (COVID-19). The NAS provided care to 1230 patients with COVID-19. The descriptive data show how well NAS responded to a major national disaster and the recent pandemic.

Medical emergency calls and calls for central nervous system symptoms during the COVID-19 outbreak in Hangzhou, China.

Since January 2020, the continuous and severe COVID-19 epidemic has ravaged various countries around the world and affected their emergency medical systems (EMS). The total number of emergency calls and the number of emergency calls for central nervous system (CNS) symptoms during the 2020 COVID-19 outbreak in Hangzhou, China (January 20-March 20) were investigated, and it was investigated whether these numbers had decreased as compared with the corresponding period in 2019. The number of daily emergency calls, ambulance dispatches, and rescues at the Hangzhou Emergency Center (HEC) was counted. The CNS symptoms considered in this study included those of cerebrovascular diseases, mental and behavioral disorders, and other neurological diseases. It was found that, during the 2020 study period, the number of emergency calls was 33,563, a decrease of 19.83% (95% CI: 14.02-25.41%) as compared to the 41,863 emergency calls in 2019 (P < 0.01). The number of ambulances dispatched was 10,510, a decrease of 25.55% (95 %CI: 18.52-35.11%) as compared to the 14,117 ambulances dispatched in 2019 (P < 0.01). The number of rescues was 7,638, a decrease of 19.67% (95% CI: 16.12-23.18%) as compared with the 9,499 rescues in 2019 (P < 0.01). It was also found that the number of emergency calls related to CNS symptoms, including symptoms of cerebrovascular diseases, mental and behavioral disorders, and other neurological diseases, was significantly reduced (P < 0.01). The total number of medical emergency calls and the number of emergency calls for CNS symptoms occurring in a large city in China decreased significantly during the COVID-19 epidemic.

Utility of prehospital call center ambulance dispatch data for COVID-19 cluster surveillance: A retrospective analysis.

Cluster surveillance, identification, and containment are primary outbreak management techniques; however, adapting these for low- and middle-income countries is an ongoing challenge. We aimed to evaluate the utility of prehospital call center ambulance dispatch (CCAD) data for surveillance by examining the correlation between influenza-like illness (ILI)-related dispatch calls and COVID-19 cases. We performed a retrospective analysis of state-level CCAD and COVID-19 data recorded between January 1 and April 30, 2020, in Telangana, India. The primary outcome was a time series correlation between ILI calls in CCAD and COVID-19 case counts. Secondarily, we looked for a year-to-year correlation of ILI calls in the same period over 2018, 2019, and 2020. On average, ILI calls comprised 12.9% (95% CI 11.7%-14.1%) of total daily calls in 2020, compared to 7.8% (95% CI 7.6%-8.0%) in 2018, and 7.7% (95% CI 7.5%-7.7%) in 2019. ILI call counts from 2018, 2019, and 2020 aligned closely until March 19, when 2020 ILI calls increased, representing 16% of all calls by March 23 and 27.5% by April 7. In contrast to the significant correlation observed between 2020 and previous years' January-February calls (2020 and 2019-Durbin-Watson test statistic [DW]=0.749, p < 0.001; 2020 and 2018-DW=1.232, p < 0.001), no correlation was observed for March-April calls (2020 and 2019-DW=2.012, p=0.476; 2020 and 2018-DW=1.820, p=0.208). In March-April 2020, the daily reported COVID-19 cases by time series significantly correlated with the ILI calls (DW=0.977, p < 0.001). The ILI calls on a specific day significantly correlated with the COVID-19 cases reported 6 days prior and up to 14 days after (cross-correlation > 0.251, the 95% upper confidence limit). The statistically significant time series correlation between ILI calls and COVID-19 cases suggests prehospital CCAD can be part of early warning systems aiding outbreak cluster surveillance, identification, and containment.

Ambulance dispatch prioritisation for traffic crashes using machine learning: A natural language approach

IntroductionDemand for emergency ambulances is increasing, therefore it is important that ambulance dispatch is prioritised appropriately. This means accurately identifying which incidents require a lights and sirens (L&S) response and those that do not. For traffic crashes, it can be difficult to identify the needs of patients based on bystander reports during the emergency phone call; as traffic crashes are complex events, often with multiple patients at the same crash with varying medical needs. This study aims to determine how well the text sent to paramedics en-route to the traffic crash scene by the emergency medical dispatcher (EMD), in combination with dispatch codes, can predict the need for a L&S ambulance response to traffic crashes. Methods: A retrospective cohort study was conducted using data from 2014 to 2016 traffic crashes attended by emergency ambulances in Perth, Western Australia. Machine learning algorithms were used to predict the need for a L&S response or not. The features were the Medical Priority Dispatch System (MPDS) determinant codes and EMD text. EMD text was converted for computation using natural language processing (Bag of Words approach). Machine learning algorithms were used to predict the need for a L&S response, defined as where one or more patients (a) died before hospital admission, (b) received L&S transport to hospital, or (c) had one or more high-acuity indicators (based on an a priori list of medications, interventions or observations. Results: There were 11,971 traffic crashes attended by ambulances during the study period, of which 22.3 % were retrospectively determined to have required a L&S response. The model with the highest accuracy was using an Ensemble machine learning algorithm with a score of 0.980 (95 % CI 0.976–0.984). This model predicted the need for an L&S response using both MPDS determinant codes and EMD text. Discussion: We found that a combination of EMD text and MPDS determinate codes can predict which traffic crashes do and do not require a lights and sirens ambulance response to the scene with a high degree of accuracy. Emergency medical services could deploy machine learning algorithms to improve the accuracy of dispatch to traffic crashes, which has the potential to result in improved system efficiency.

Reorganization of an Emergency Medical System in a Mixed Urban-Rural Area.

The reorganization of an emergency medical system means that we look for new locations of ambulance stations with the aim of improving the accessibility of the service. We applied two tools that are well known in the operations research community, namely mathematical programming, and computer simulation. Using the hierarchical pq-median model, we proposed optimal locations of the stations throughout the country and within large towns. Several solutions have been calculated that differ in the number of stations that are supposed to be relocated to new positions. The locations proposed by the mathematical programming model were evaluated via computer simulation. The approach was demonstrated under the conditions of the Slovak Republic using real historical data on ambulance dispatches. We have concluded that (i) the distribution of the stations proposed by the hierarchical pq-median model overcomes the current distribution; the performance of the system has significantly improved even if only 10% of the stations are relocated to new municipalities; (ii) the variant that relocates 40% of the stations is a reasonable compromise between the benefits and induced costs; (iii) optimizing station locations in big towns can significantly improve the local as well as the nationwide performance indicators; the response times in two regional capitals has reduced by more than 4 min.

Ambulance response time in a Brazilian emergency medical service

Research efforts on ambulance response times for Emergency Medical Services (EMS) calls have been made for decades, especially in developed countries, using different techniques and with varying objectives. In Brazil, a developing country, the scarce scientific production on this vital indicator prioritizes scenarios for EMS in cities with more than one million inhabitants. This shows the importance of extending research to the reality of small and medium-sized cities. This paper presents SAMU, the Brazilian EMS that follows the Franco-German emergency medicine model, compiling numbers related to service at the national level. The use of quantile regression allows the identification of the RT for the EMS and helps to explain the effects of factors at the system level, at the patient level, and specific factors on response time intervals of Southwest Paraná SAMU. This specific EMS, characterized as an inter-municipal consortium of prehospital services, is responsible for prehospital emergency care for an approximate population of 635,000 inhabitants in 42 small towns in the State of Paraná in southern Brazil. From the analysis of the records of 12,050 ambulance dispatches, it was possible to identify the average ambulance response time of 14 min and 25 s. The regression model was able to explain the influence of the independent variables at the system level (presumed severity of the emergency, ambulance dispatch time, and ambulance travel time), at the patient level (age, gender, and characteristic of the emergency) and specific variables of the emergency (day of the week and time of day) on the dependent variable response time over the quantiles, showing that the dispatch time, travel time, time of day, service to male patients and critical cases influence the ambulance response time. This work contributes to deepening the understanding of the management of EMS operations in a developing country, allows the comparison of the RT identified in relation to other countries, and identifies factors that impact the RT for other actors directly or indirectly involved. The practical implications are also presented, as well as how the study impacts the decision-making and management process of the EMS in the short, medium and long term.

Back to the Control Room: Managing Artistic Work

Control rooms have long been a key domain of investigation in HCI and CSCW as sites for understanding distributed work and fragmented settings, as well as the role and design of digital technologies in that work. Although research has tended to focus mainly on ‘command and control’ configurations, such as rail transport, ambulance dispatch, air traffic and CCTV rooms, centres of coordination shaped by artistic and performative concerns have much to contribute. Our study examines how a professional team of artists and volunteers stage manage and direct the performance of a mixed reality game from a central control room, with remote runners performing live video streaming from the streets nearby to online players. We focus on the work undertaken by team members to bring this about, exploring three key elements that enable it. First, we detail how team members oriented to the work as an artistic performance produced for an audience, how they produced compelling, varied content for online players, and how the quality of the work was ongoingly assessed. Second, we unpack the organisational hierarchy in the control room’s division of labour, and how this was designed to manage the challenges of restricted informational visibility there. Third, we explore the interactional accomplishment of the performance by looking at the role of radio announcements from the event’s director to orchestrate how the performance developed over time. Announcements were used to resolve trouble and provide instructions for avoiding future performative problems; but more centrally, to give artistic direction to runners in order to shape the performance itself. To close we discuss how this study of a performance impacts CSCW’s understandings of control room work, how the problem of ‘diffuse’ tasks like artistic work is co-ordinated, and how orientations towards quality as an artistic concern is manifest in / as control room practices. We also reflect on hierarchical and horizontal control room arrangements, and the role of video as both collaborative resource and product.Graphical abstract

Systematic Approaches for Telemedicine and Data Coordination for COVID-19 in Baja California, Mexico

Background In 2019, the State of Baja California had a total population of 3,682,063 inhabitants; in the city of Tijuana, there were only 13 Red Cross ambulances and 1 fire department ambulance to attend to the prehospital emergencies of almost 2 million inhabitants. Objective This study aimed to provide information to the public; evaluate COVID-19 in real time; and track regional, municipal, and state-wide data in real time that inform supply chains and resource allocation with the anticipation of a surge in COVID-19 cases. Methods Our model is based on human-centric design factors and cross-disciplinary collaborations for the scalable, data-driven enablement of smartphone teleconsultation technologies to link hospitals, clinics, and emergency medical services for point-of-care assessments of COVID-19 testing and subsequent treatment and quarantine decisions. Results The Telehealth System handled 28,964 telephone calls in the period from April 1, 2020, to January 30, 2022, and accumulated 20,287 working hours. In total, 13,721 follow-up calls were made to quarantined patients, providing medical and psychological counseling, and 12,643 calls were received and transferred from the 911 system, of which 4964 calls from patients with respiratory symptoms required urgent ambulance dispatch. Conclusions Telehealth offers capabilities for remote detection, care, and treatment to help with supervision, surveillance, discovery, and prevention, as well as to mitigate the effects of health care indirectly related to COVID-19.

Canceled Air Ambulance Trauma Scene Calls: A Prospective Observational Study of Causes and Outcomes of Trauma Auto-launch Cancellations

ObjectiveDirect transport, occasionally by helicopter, to a trauma hospital for severely injured patients is associated with decreased mortality. This study sought to determine causes for air ambulance trauma response cancellations and secondarily to identify patients who underwent secondary transfer to a trauma center after a canceled air ambulance dispatch. MethodsThis prospective cohort study used administrative databases from August 2020 to August 2021 to collect data related to canceled trauma calls. Frequencies of cancellation reasons and transferred patients were summarized, and the estimated delay to trauma center arrival was calculated. Subsequent probabilistic matching was performed to identify patients who underwent secondary transfer. ResultsOf 3,232 trauma calls, 1,924 were canceled for reasons including the trauma bypass criteria not being met, patient brought to trauma center, and patient refused transfer. Of the 1,117 patients for whom an air ambulance was canceled because they did not meet the trauma bypass criteria, 184 (16.5%) were later transferred to a lead trauma hospital, with a median delay of 4.12 hours (interquartile range = 2.57-7.35 hours). ConclusionsMost scene call cancellations were due to patients not meeting the trauma bypass criteria; yet, 16.5% of these patients were later transported to a trauma center. Interventions are needed in education, adherence, and modification of the trauma bypass criteria.

Paramedic management of back pain: a scoping review

BackgroundResearch examining paramedic care of back pain is limited.ObjectiveTo describe ambulance service use and usual paramedic care for back pain, the effectiveness and safety of paramedic care of back pain, and the characteristics of people with back pain who seek care from paramedics.MethodsWe included published peer-reviewed studies of people with back pain who received any type of paramedic care on-scene and/or during transport to hospital. We searched MEDLINE, EMBASE, CINAHL, Web of Science and SciELO from inception to July 2022. Two authors independently screened and selected the studies, performed data extraction, and assessed the methodological quality using the PEDro, AMSTAR 2 and Hawker tools. This review followed the JBI methodological guidance for scoping reviews and PRISMA extension for scoping reviews.ResultsFrom 1987 articles we included 26 articles (25 unique studies) consisting of 22 observational studies, three randomised controlled trials and one review. Back pain is frequently in the top 3 reasons for calls to an ambulance service with more than two thirds of cases receiving ambulance dispatch. It takes ~ 8 min from time of call to an ambulance being dispatched and 16% of calls for back pain receive transport to hospital. Pharmacological management of back pain includes benzodiazepines, NSAIDs, opioids, nitrous oxide, and paracetamol. Non-pharmacological care is poorly reported and includes referral to alternate health service, counselling and behavioural interventions and self-care advice. Only three trials have evaluated effectiveness of paramedic treatments (TENS, active warming, and administration of opioids) and no studies provided safety or costing data.ConclusionParamedics are frequently responding to people with back pain. Use of pain medicines is common but varies according to the type of back pain and setting, while non-pharmacological care is poorly reported. There is a lack of research evaluating the effectiveness and safety of paramedic care for back pain.