Refining ambulance clinical response models: The impact on ambulance response and emergency department presentations

OBJECTIVE

The ambulance service in Victoria, Australia implemented a revised clinical response model (CRM) in 2016 which was designed to increase the diversion of low-acuity Triple Zero (000) calls to secondary telephone triage and reduce emergency ambulance dispatches. The present study evaluates the influence of the revised CRM on emergency ambulance response times and ED presentations.

METHODS

A retrospective study of emergency calls for ambulance between 1 January 2015 and 31 December 2018. Ambulance data were linked with ED presentations occurring up to 48 h after contact. Interrupted time series analyses were used to evaluate the impact of the revised CRM.

RESULTS

A total of 2 365 529 calls were included. The proportion allocated a Code 1 (time-critical, lights/sirens) dispatch decreased from 56.6 to 41.0% after implementation of the revised CRM. The proportion of calls not receiving an emergency ambulance increased from 10.4 to 19.6%. Interrupted time series analyses demonstrated an improvement in Code 1 cases attended within 15 min (Key Performance Indicator). However, for patients with out-of-hospital cardiac arrest or requiring lights and sirens transport to hospital, there was no improvement in response time performance. By the end of the study period, there was also no difference in the proportion of callers presenting to ED when compared with the estimated proportion assuming the revised CRM had not been implemented.

CONCLUSION

The revised CRM was associated with improved Code 1 response time performance. However, there was no improvement in response times for high acuity patients, and no change in the proportion of callers presenting to ED.

Identification of Anterior Large Vessel Occlusion Stroke During the Emergency Call: Protocol for a Controlled, Nonrandomized Trial

BACKGROUND

Endovascular thrombectomy (ET), combined with intravenous thrombolysis if possible, is an effective treatment option for patients with stroke who have confirmed anterior large vessel occlusion (aLVO). However, ET is mainly limited to comprehensive stroke centers (CSCs), resulting in a lack of ET capacity in remote, sparsely populated areas. Most stroke networks use the "Drip and Ship" or "Mothership" strategy, resulting in either delayed ET or intravenous thrombolysis, respectively.

OBJECTIVE

This study protocol introduces the Leitstellen-Basierte Erkennung von Schlaganfall-Patienten für eine Thrombektomie und daraufhin abgestimmte Optimierung der Rettungskette (LESTOR) strategy, developed to optimize the preclinical part of the stroke chain of survival to improve the clinical outcome of patients with suspected aLVO stroke. This involves refining the dispatch strategy for identifying patients with acute aLVO stroke using a phone-based aLVO query. This includes dispatching emergency physicians and emergency medical services (EMS) to urban emergency sites, as well as dispatching helicopter EMS to remote areas. If a highly suspected aLVO is identified after a standardized aLVO score evaluation during a structured examination at the emergency scene, prompt transport to a CSC should be prioritized.

METHODS

The LESTOR study is a controlled, nonrandomized study implementing the LESTOR strategy, with a stepped-wedge, cluster trial design in 6 districts in southwest Germany. In an interprofessional, iterative approach, an aLVO query or dispatch protocol intended for use by dispatchers, followed by a coordinated aLVO examination score for use by EMS, is being developed, evaluated, and pretested in a simulation study. After the training of all participating health care professionals with the corresponding final aLVO query, the LESTOR strategy is being implemented stepwise. Patients otherwise receive usual stroke care in both the control and intervention groups. The primary outcome is the modified Rankin Scale at 90 days in patients with stroke receiving endovascular treatment. We will use a generalized linear mixed model for data analysis. This study is accompanied by a cost-effectiveness analysis and a qualitative process evaluation.

RESULTS

This paper describes and discusses the protocol for this controlled, nonrandomized LESTOR study. Enrollment was completed in June 2023. Data analysis is ongoing and the first results are expected to be submitted for publication in 2024. The project started in April 2020 and will end in February 2024.

CONCLUSIONS

We expect that the intervention will improve the clinical outcome of patients with aLVO stroke, especially outside the catchment areas of CSCs. The results of the accompanying process evaluation and the cost-effectiveness analysis will provide further insights into the implementation process and allow for a better interpretation of the results.

TRIAL REGISTRATION

German Clinical Trials Register DRKS00022152; https://drks.de/search/de/trial/DRKS00022152.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/51683.

Contribution of Live Video to Physicians' Remote Assessment of Suspected COVID-19 Patients in an Emergency Medical Communication Centre: A Retrospective Study and Web-Based Survey

The COVID-19 pandemic had a major impact on emergency medical communication centres (EMCC). A live video facility was made available to second-line physicians in an EMCC with a first-line paramedic to receive emergency calls. The objective of this study was to measure the contribution of live video to remote medical triage. The single-centre retrospective study included all telephone assessments of patients with suspected COVID-19 symptoms from 01.04.2020 to 30.04.2021 in Geneva, Switzerland. The organisation of the EMCC and the characteristics of patients who called the two emergency lines (official emergency number and COVID-19 number) with suspected COVID-19 symptoms were described. A prospective web-based survey of physicians was conducted during the same period to measure the indications, limitations and impact of live video on their decisions. A total of 8957 patients were included, and 2157 (48.0%) of the 4493 patients assessed on the official emergency number had dyspnoea, 4045 (90.6%) of 4464 patients assessed on the COVID-19 number had flu-like symptoms and 1798 (20.1%) patients were reassessed remotely by a physician, including 405 (22.5%) with live video, successfully in 315 (77.8%) attempts. The web-based survey (107 forms) showed that physicians used live video to assess mainly the breathing (81.3%) and general condition (78.5%) of patients. They felt that their decision was modified in 75.7% (n = 81) of cases and caught 7 (7.7%) patients in a life-threatening emergency. Medical triage decisions for suspected COVID-19 patients are strongly influenced by the use of live video.

Monkeypox 2022: A Primer and Identify-Isolate-Inform (3I) Tool for Emergency Medical Services Professionals

Monkeypox 2022 exhibits unprecedented human-to-human transmission and presents with different clinical features than those observed in prior outbreaks. Previously endemic only to West and Central Africa, the monkeypox virus spread rapidly world-wide following confirmation of a case in the United Kingdom on May 7, 2022 of an individual that had traveled to Nigeria. Detection of cases with no travel history confirms on-going community spread. Emergency Medical Services (EMS) professionals will likely encounter patients suspected or confirmed to have monkeypox, previously a rare disease and therefore unfamiliar to most clinicians. Consequently, it is critical for EMS medical directors to immediately implement policies and procedures for EMS teams – including emergency medical dispatchers – to identify potential monkeypox cases. These must include direction on actions EMS professionals should take to protect themselves and others from virus transmission. Monkeypox 2022 may manifest more subtly than it has historically. Presentations include a subclinical prodrome and less dramatic skin lesions – potentially limited to genital or anal body regions – which can be easily confused with dermatologic manifestations of common sexually transmitted infections (STIs). While most readily spread by close contact with infectious skin lesions on a patient, it is also transmissible from fomites, such as bed sheets. Additionally, droplet transmission can occur, and the virus can be spread by aerosolization under certain conditions. The long incubation period could have profound negative consequences on EMS staffing if clinicians are exposed to monkeypox. This report summarizes crucial information needed for EMS professionals to understand and manage the monkeypox 2022 outbreak. It presents an innovative Identify-Isolate-Inform (3I) Tool for use by EMS policymakers, educators, and clinicians on the frontlines who may encounter monkeypox patients. Patients are identified as potentially exposed or infected after an initial assessment of risk factors with associated signs and symptoms. Prehospital workers must immediately don personal protective equipment (PPE) and isolate infectious patients. Also, EMS professionals must report exposures to their agency infection control officer and alert health authorities for non-transported patients. Prehospital professionals play a crucial role in emerging and re-emerging infectious disease mitigation. The monkeypox 2022 3I Tool includes knowledge essential for all clinicians, plus specific information to guide critical actions in the prehospital environment.

Machine Learning-Based Text Analysis to Predict Severely Injured Patients in Emergency Medical Dispatch: Model Development and Validation

Background

Early recognition of severely injured patients in prehospital settings is of paramount importance for timely treatment and transportation of patients to further treatment facilities. The dispatching accuracy has seldom been addressed in previous studies.

Objective

In this study, we aimed to build a machine learning–based model through text mining of emergency calls for the automated identification of severely injured patients after a road accident.

Methods

Audio recordings of road accidents in Taipei City, Taiwan, in 2018 were obtained and randomly sampled. Data on call transfers or non-Mandarin speeches were excluded. To predict cases of severe trauma identified on-site by emergency medical technicians, all included cases were evaluated by both humans (6 dispatchers) and a machine learning model, that is, a prehospital-activated major trauma (PAMT) model. The PAMT model was developed using term frequency–inverse document frequency, rule-based classification, and a Bernoulli naïve Bayes classifier. Repeated random subsampling cross-validation was applied to evaluate the robustness of the model. The prediction performance of dispatchers and the PAMT model, in severe cases, was compared. Performance was indicated by sensitivity, specificity, positive predictive value, negative predictive value, and accuracy.

Results

Although the mean sensitivity and negative predictive value obtained by the PAMT model were higher than those of dispatchers, they obtained higher mean specificity, positive predictive value, and accuracy. The mean accuracy of the PAMT model, from certainty level 0 (lowest certainty) to level 6 (highest certainty), was higher except for levels 5 and 6. The overall performances of the dispatchers and the PAMT model were similar; however, the PAMT model had higher accuracy in cases where the dispatchers were less certain of their judgments.

Conclusions

A machine learning–based model, called the PAMT model, was developed to predict severe road accident trauma. The results of our study suggest that the accuracy of the PAMT model is not superior to that of the participating dispatchers; however, it may assist dispatchers when they lack confidence while making a judgment.

Discovering Key Topics in Emergency Medical Dispatch from Free Text Dispatcher Observations

The objective of this work was to discover key topics latent in free text dispatcher observations registered during emergency medical calls. We used a total of 1374931 independent retrospective cases from the Valencian emergency medical dispatch service in Spain, from 2014 to 2019. Text fields were preprocessed to reduce vocabulary size and filter noise, removing accent and punctuation marks, along with uninformative and infrequent words. Key topics were inferred from the multinomial probabilities over words conditioned on each topic from a Latent Dirichlet Allocation model, trained following an online mini-batch variational approach. The optimal number of topics was set analyzing the values of a topic coherence measure, based on the normalized pointwise mutual information, across multiple validation K-folds. Our results support the presence of 15 key topics latent in free text dispatcher observations, related with: ambulance request; chest pain and heart attack; respiratory distress; head falls and blows; fever, chills, vomiting and diarrhea; heart failure; syncope; limb injuries; public service body request; thoracic and abdominal pain; stroke and blood pressure abnormalities; pill intake; diabetes; bleeding; consciousness. The discovery of these topics implies the automatic characterization of a huge volume of complex unstructured data containing relevant information linked to emergency medical call incidents. Hence, results from this work could lead to the update of structured emergency triage algorithms to directly include this latent information in the triage process, resulting in a positive impact in patient wellbeing and health services sustainability.

The Utility of Ambulance Dispatch Call Syndromic Surveillance for Detecting and Assessing the Health Impact of Extreme Weather Events in England

Extreme weather events present significant global threats to health. The National Ambulance Syndromic Surveillance System collects data on 18 syndromes through chief presenting complaint (CPC) codes. We aimed to determine the utility of ambulance data to monitor extreme temperature events for action. Daily total calls were observed between 01/01/2018−30/04/2019. Median daily ’Heat/Cold’ CPC calls during “known extreme temperature” (identified a priori), “extreme temperature”; (within 5th or 95th temperature percentiles for central England) and meteorological alert periods were compared to all other days using Wilcoxon signed-rank test. During the study period, 12,585,084 calls were recorded. In 2018, median daily “Heat/Cold” calls were higher during periods of known extreme temperature: heatwave (16/day, 736 total) and extreme cold weather events (28/day, 339 total) compared to all other days in 2018 (6/day, 1672 total). Median daily “Heat/Cold” calls during extreme temperature periods (16/day) were significantly higher than non-extreme temperature periods (5/day, p < 0.001). Ambulance data can be used to identify adverse impacts during periods of extreme temperature. Ambulance data are a low resource, rapid and flexible option providing real-time data on a range of indicators. We recommend ambulance data are used for the surveillance of presentations to healthcare related to extreme temperature events.

Effectiveness of a Dispatcher-Assisted Cardiopulmonary Resuscitation Program Developed by the Thailand National Institute of Emergency Medicine (NIEMS)

BACKGROUND

Out-of-hospital cardiac arrest (OHCA) is a life-threatening condition with an overall survival rate that generally does not exceed 10%. Several factors play essential roles in increasing survival among patients experiencing cardiac arrest outside the hospital. Previous studies have reported that implementing a dispatcher-assisted cardiopulmonary resuscitation (DA-CPR) program increases bystander CPR, quality of chest compressions, and patient survival. This study aimed to assess the effectiveness of a DA-CPR program developed by the Thailand National Institute for Emergency Medicine (NIEMS).

METHODS

This was an experimental study using a manikin model. The participants comprised both health care providers and non-health care providers aged 18 to 60 years. They were randomly assigned to either the DA-CPR group or the uninstructed CPR (U-CPR) group and performed chest compressions on a manikin model for two minutes. The sequentially numbered, opaque, sealed envelope method was used for randomization in blocks of four with a ratio of 1:1.

RESULTS

There were 100 participants in this study (49 in the DA-CPR group and 51 in the U-CPR group). Time to initiate chest compressions was statistically significantly longer in the DA-CPR group than in the U-CPR group (85.82 [SD = 32.54] seconds versus 23.94 [SD = 16.70] seconds; P <.001). However, the CPR instruction did not translate into better performance or quality of chest compressions for the overall sample or for health care or non-health care providers.

CONCLUSION

Those in the CPR-trained group applied chest compressions (initiated CPR) more quickly than those who initiated CPR based upon dispatch-based CPR instructions.

Better safe than sorry: Registered nurses' strategies for handling difficult calls to emergency medical dispatch centres - An interview study

AIMS AND OBJECTIVES

To describe strategies employed by registered nurses for handling difficult calls to emergency medical dispatch centres.

BACKGROUND

At emergency medical dispatch centres, registered nurses encounter a range of difficult calls in their clinical practice. They often use clinical decision support systems, but these may be of limited help if the caller is for instance abusive or has limited language proficiency. Much can be learnt from strategies developed by registered nurses for handling difficult calls.

DESIGN

A descriptive qualitative study was conducted.

METHODS

A purposeful sample of 24 registered nurses from three different emergency medical dispatch centres were interviewed. The transcribed interviews were analysed using qualitative content analysis. The COREQ checklist was applied.

RESULTS

An overarching theme was established: "Using one's nursing competence and available resources for a safe outcome", based on three sub-themes: Use one's own professional and personal resources, Use resources within the organisation and Use external resources. The themes in turn consist of ten categories.

CONCLUSIONS

Registered nurses employed a range of strategies to deal with difficult calls, often in combination. They used their personal resources, resources within their own organisation, and collaboration partners to make safe triage decisions and use resources wisely. The effectiveness of these strategies, however, remains unknown. When registered nurses were unable to rule out a high-acuity condition, they used safety-netting and sent an ambulance. Evaluating current strategies and making strategies explicit could further improve the ability of nurses to handle difficult calls.

RELEVANCE TO CLINICAL PRACTICE

The strategies described by registered nurses for handling difficult calls to EMDCs included using a consecutive set of strategies. Some of the strategies seemed to be used deliberately, while others seemed tacit and applied in a routinised way. These strategies could potentially be useful for RNs working with telephone triage in different contexts.

The Feasibility of Using Machine Learning to Classify Calls to South African Emergency Dispatch Centres According to Prehospital Diagnosis, by Utilising Caller Descriptions of the Incident

This paper presents the application of machine learning for classifying time-critical conditions namely sepsis, myocardial infarction and cardiac arrest, based off transcriptions of emergency calls from emergency services dispatch centers in South Africa. In this study we present results from the application of four multi-class classification algorithms: Support Vector Machine (SVM), Logistic Regression, Random Forest and K-Nearest Neighbor (kNN). The application of machine learning for classifying time-critical diseases may allow for earlier identification, adequate telephonic triage, and quicker response times of the appropriate cadre of emergency care personnel. The data set consisted of an original data set of 93 examples which was further expanded through the use of data augmentation. Two feature extraction techniques were investigated namely; TF-IDF and handcrafted features. The results were further improved using hyper-parameter tuning and feature selection. In our work, within the limitations of a limited data set, classification results yielded an accuracy of up to 100% when training with 10-fold cross validation, and 95% accuracy when predicted on unseen data. The results are encouraging and show that automated diagnosis based on emergency dispatch centre transcriptions is feasible. When implemented in real time, this can have multiple utilities, e.g. enabling the call-takers to take the right action with the right priority.

Utility of Emergency Medical Dispatch (EMD) Telephone Screening in Identifying COVID-19 Positive Patients

Background: In response to the COVID-19 pandemic, Emergency Medical Services (EMS) systems have received guidelines as part of coordinated response efforts aimed at mitigating exposures and ensuring occupational wellbeing, including recommendations of Personal Protective Equipment (PPE) utilization, and modifications of Emergency Medical Dispatch (EMD) caller queries. The aim of the study was to estimate the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of an EMD telephone screening process for the identification of hospital diagnosed COVID-19 positive patients. Methods: A retrospective cohort study was conducted of adult EMS encounters presenting to hospitals within a large health system from March 16-June 30, 2020. EMD telephone screening status was defined as either "positive" or "negative" and was collected from prehospital medical records. COVID-19 positive patients were confirmed via hospital laboratory diagnosis and were matched to their prehospital medical record data. Patient demographics and EMS encounter level data, such as Dispatch Code and Priority level, were also collected. Estimations of sensitivity, specificity, PPV and NPV were made. Emergency telephone screening status was stratified by COVID-19 diagnosis to describe discordant pairs. Results: Of the 3,443 total encounters screened, there were 652 patients who were subsequently COVID-19 positive per hospital diagnosis (18.9%). Approximately 5.0% of all encounters did not screen positive on EMD screening but were later COVID-19 positive. Conversely, 44.2% of encounters screened positive for COVID-19, but were subsequently negative. Sensitivity of the EMD telephonic screening was estimated as 75.0% (95% CI 71.7%, 78.3%) and specificity was 45.5% (95% CI 43.7%, 47.4%). The PPV was 24.3% (95% CI 22.5%, 26.0%), and NPV 88.6% (95% CI 87.0%, 90.3%). Conclusions: The sensitivity of the EMD telephonic screening process was moderately able to identify COVID-19 positive patients. There is a need to reevaluate and revise guidelines and recommendations, specifically modified caller queries, as part of ongoing pandemic emergency response efforts in order to reduce transmissions and maximize patient and provider safety.

Registered nurses' understandings of emergency medical dispatch center work: A qualitative phenomenographic interview study

Non-urgent and urgent telephone nursing services are increasing globally, and phenomenographic research has shown that how work is understood may influence work performance. This descriptive study makes a qualitative inductive investigation of understandings of emergency medical dispatch center work among registered nurses. Twenty-four registered nurses at three mid Swedish emergency medical dispatch centers were interviewed. Analysis based on phenomenographic principles identified five categories in the interviews: (i) Assess, prioritize, direct, or refer; (ii) Facilitate ambulance nursing work; (iii) Perform nursing care; (iv) Always be available for the public; and (v) Have the person behind the patient in mind. The first constitutes the basis of the work. The second emphasizes cooperation with and support for the ambulance staff. The third entails remotely providing nursing care, whilst the fourth stresses serving the entire population. The fifth and most comprehensive way of understanding work involves having a holistic view of the person in need, including person-centered care. Provision of high-quality emergency medical dispatch center work involves all categories. Combined, they constitute a "work map," valuable for reflection, competence development, and introduction of new staff.

Optimizing Emergency Medical Service Structures Using a Rule-Based Discrete Event Simulation-A Practitioner's Point of View

Many studies in research deal with optimizing emergency medical services (EMS) on both the operational and the strategic level. It is the purpose of this method-oriented article to explain the major features of “rule-based discrete event simulation” (rule-based DES), which we developed independently in Germany and Switzerland. Our rule-based DES addresses questions concerning the location and relocation of ambulances, dispatching and routing policies, and EMS interplay with other players in prehospital care. We highlight three typical use cases from a practitioner’s perspective and go into different countries’ peculiarities. We show how research results are applied to EMS and healthcare organizations to simulate and optimize specific regions in Germany and Switzerland with their strong federal structures. The rule-based DES serves as basis for decision support to improve regional emergency services’ efficiency without increasing cost. Finally, all simulation-based methods suggest normative solutions and optimize EMS’ performance within given healthcare system structures. We argue that interactions between EMS, emergency departments, and public healthcare agencies are crucial to further improving effectiveness, efficiency, and quality.

Improving the Appropriateness of Advanced Life Support Teams' Dispatch: A Before-After Study

BACKGROUND AND IMPORTANCE

The dispatch of Advanced Life Support (ALS) teams in Emergency Medical Services (EMS) is still a hardly studied aspect of prehospital emergency logistics. In 2015, the dispatch algorithm of Emilia Est Emergency Operation Centre (EE-EOC) was implemented and the dispatch of ALS teams was changed from primary to secondary based on triage of dispatched vehicles for high-priority interventions when teams with Immediate Life Support (ILS) skills were dispatched.

OBJECTIVES

This study aimed to evaluate the effects on the appropriateness of ALS teams' intervention and their employment time, and to compare sensitivity and specificity of the algorithm implementation.

DESIGN

This was a retrospective before-after observational study.

SETTINGS AND PARTICIPANTS

Primary dispatches managed by EE-EOC involving ambulances and/or ALS teams were included. Two groups were created on the basis of the years of intervention (2013-2014 versus 2017-2018).

INTERVENTION

A switch from primary to secondary dispatch of ALS teams in case of high-priority dispatches managed by ILS teams was implemented.

OUTCOMES

Appropriateness of ALS team intervention, total task time of ALS vehicles, and sensitivity and specificity of the algorithm were reviewed.

RESULTS

The study included 242,501 emergency calls that generated 56,567 red code dispatches. The new algorithm significantly increased global sensitivity and specificity of the system in terms of recognition of potential need of ALS intervention and the specificity of primary ALS dispatch. The appropriateness of ALS intervention was significantly increased; total tasking time per day for ALS and the number of critical dispatches without ALS available were reduced.

CONCLUSION

The revision of the dispatch criteria and the extension of the two-tiered dispatch for ALS teams significantly increased the appropriateness of ALS intervention and reduced both the global tasking time and the number of high-priority dispatches without ALS teams available.

First Description of a Helicopter-Borne ECPR Team for Remote Refractory Out-of-Hospital Cardiac Arrest

Introduction: Access time to extracorporeal cardiopulmonary resuscitation (ECPR) refractory out of hospital cardiac arrest (OHCA) is a crucial factor. In our region, some patients are not eligible to this treatment due to the impossibility to reach the hospital with reasonable delay (ideally 60 min). In order to increase accessibility for patients far from ECPR centers, we developed a helicopter-borne ECPR-team which is sent out to the patient for ECPR implementation on the scene of the OHCA.Methods: We conducted a retrospective monocentric study to evaluate this strategy. The team is triggered by the local emergency medical service and heliborne on the site of the OHCA. All consecutive patients implemented with ECPR by our heliborne ECPR team from January 2014 to December 2017 were included. We analyzed usual CA characteristics, different times (no-flow, low-flow, time between OHCA and dispatch…), and patient outcome.Results: During this 4-year study period, 33 patients were included. Mean age was 43.9 years. Mean distance from the ECPR-team base to OHCA location was 41 km. Mean low-flow time was 110 minutes. Five patients survived with good neurological outcome; 6 patients developed brain death and became organ donors.Conclusion: These results show the possibility to make ECPR accessible for patients far from ECPR centers. Survival rate is non negligible, especially in the absence of therapeutic alternative. An earlier trigger of the ECPR-team could reduce the low-flow time and probably increase survival. This strategy improves equity of access to ECPR and needs to be confirmed by further studies.

Rapid reorganization of the Milan metropolitan public safety answering point operations during the initial phase of the COVID-19 outbreak in Italy

Objective

To quantify how the first public announcement of confirmed coronavirus disease 2019 (COVID-19) in Italy affected a metropolitan region's emergency medical services (EMS) call volume and how rapid introduction of alternative procedures at the public safety answering point (PSAP) managed system resources.

Methods

PSAP processes were modified over several days including (1) referral of non-ill callers to public health information call centers; (2) algorithms for detection, isolation, or hospitalization of suspected COVID-19 patients; and (3) specialized medical teams sent to the PSAP for triage and case management, including ambulance dispatches or alternative dispositions. Call volumes, ambulance dispatches, and response intervals for the 2 weeks after announcement were compared to 2017-2019 data and the week before.

Results

For 2 weeks following outbreak announcement, the primary-level PSAP (police/fire/EMS) averaged 56% more daily calls compared to prior years and recorded 9281 (106% increase) on Day 4, averaging ∼400/hour. The secondary-level (EMS) PSAP recorded an analogous 63% increase with 3863 calls (∼161/hour; 264% increase) on Day 3. The COVID-19 response team processed the more complex cases (n = 5361), averaging 432 ± 110 daily (∼one-fifth of EMS calls). Although community COVID-19 cases increased exponentially, ambulance response intervals and dispatches (averaging 1120 ± 46 daily) were successfully contained, particularly compared with the week before (1174 ± 40; P = 0.02).

Conclusion

With sudden escalating EMS call volumes, rapid reorganization of dispatch operations using tailored algorithms and specially assigned personnel can protect EMS system resources by optimizing patient dispositions, controlling ambulance allocations and mitigating hospital impact. Prudent population-based disaster planning should strongly consider pre-establishing similar highly coordinated medical taskforce contingencies.

Symptom-Based Dispatching in an Emergency Medical Communication Centre: Sensitivity, Specificity, and the Area under the ROC Curve

Measuring the performance of emergency medical dispatch tools used in paramedic-staffed emergency medical communication centres (EMCCs) is rarely performed. The objectives of our study were, therefore, to measure the performance and accuracy of Geneva's dispatch system based on symptom assessment, in particular, the performance of ambulance dispatching with lights and sirens (L&S) and to measure the effect of adding specific protocols for each symptom. Methods: We performed a prospective observational study including all emergency calls received at Geneva's EMCC (Switzerland) from 1 January 2014 to 1 July 2019. The risk levels selected during the emergency calls were compared to a reference standard, based on the National Advisory Committee for Aeronautics (NACA) scale, dichotomized to severe patient condition (NACA ≥ 4) or stable patient condition (NACA < 4) in the field. The symptom-based dispatch performance was assessed using a receiver operating characteristic (ROC) curve. Contingency tables and a Fagan nomogram were used to measure the performance of the dispatch with or without L&S. Measurements were carried out by symptom, and a group of symptoms with specific protocols was compared to a group without specific protocols. Results: We found an acceptable area under the ROC curve of 0.7474, 95%CI (0.7448-0.7503) for the 148,979 assessments included in the study. Where the severity prevalence was 21%, 95%CI (20.8-21.2). The sensitivity of the L&S dispatch was 87.5%, 95%CI (87.1-87.8); and the specificity was 47.3%, 95%CI (47.0-47.6). When symptom-specific assessment protocols were used, the accuracy of the assessments was slightly improved. Conclusions: Performance measurement of Geneva's symptom-based dispatch system using standard diagnostic test performance measurement tools was possible. The performance was found to be comparable to other emergency medical dispatch systems using the same reference standard. However, the implementation of specific assessment protocols for each symptom may improve the accuracy of symptom-based dispatch systems.

Time Course of Hoist Operations by the Search and Rescue Helicopter Service in Southeast Norway

INTRODUCTION

Optimal dispatch of emergency medical services relies on accurate time estimates of the various prehospital stages. Hoist rescue work time intervals performed by the search and rescue (SAR) helicopter service in Norway have not been studied to date. We aimed to describe the epidemiologic, operational, and medical aspects of the SAR service in southeast Norway. To complement the prehospital timeline, we performed simulated hoist operations.

METHODS

We reviewed time and patient descriptors and medical interventions in hoist operations performed at a SAR base over 5 y. In addition, a simulation study measuring hoist rescue time intervals was performed. Data are presented as mean±SD, except National Advisory Committee for Aeronautics (NACA) scores, which are presented as modes.

RESULTS

There were 148 hoist operations performed during the study period, involving 180 patients. Time to take-off was 13±7 min. There were 88 patients (49%) who were injured; 53 (29%) had a medical condition, and 39 (22%) were evacuees. The mode of the NACA score was 3. Forty-five patients (25%) had an NACA score of 4 to 6. Medical interventions were performed on 77 patients (43%) in 73 operations (49%). Nine patients (5%) were endotracheally intubated, and 1 thoracostomy was performed. The simulated rescuer access time was 4±2 min, the simulated anesthesiologist access time was 6±2 min, and the simulated hoist extrication time was 13±2 min.

CONCLUSIONS

Hoist rescue was performed in 10% (n=148) of the SAR operations. New information about hoist extrication time intervals can improve rescue helicopter dispatch accuracy.

Hacking 9-1-1: Infrastructure Vulnerabilities and Attack Vectors

9-1-1 call centers are a critical component of prehospital care: they accept emergency calls, dispatch field responders such as emergency medical services, and provide callers with emergency medical instructions before their arrival. The aim of this study was to describe the technical structure of the 9-1-1 call-taking system and to describe its vulnerabilities that could lead to compromised patient care. 9-1-1 calls answered from mobile phones and landlines use a variety of technologies to provide information about caller location and other information. These interconnected technologies create potential cyber vulnerabilities. A variety of attacks could be carried out on 9-1-1 infrastructure to various ends. Attackers could target individuals, groups, or entire municipalities. These attacks could result in anything from a nuisance to increased loss of life in a physical attack to worse overall outcomes owing to delays in care for time-sensitive conditions. Evolving 9-1-1 systems are increasingly connected and dependent on network technology. As implications of cybersecurity vulnerabilities loom large, future research should examine methods of hardening the 9-1-1 system against attack.

Symptom description in patients with chest pain-A qualitative analysis of emergency medical calls involving high-risk conditions

AIMS AND OBJECTIVES

To explore the symptoms descriptions and situational information provided by patients during ongoing chest pain events caused by a high-risk condition.

BACKGROUND

Chest pain is a common symptom in patients contacting emergency dispatch centres. Only 15% of these patients are later classified as suffering from a high-risk condition. Prehospital personnel are largely dependent on symptom characteristics when trying to identify these patients.

DESIGN

Qualitative descriptive.

METHODS

Manifest content analysis of 56 emergency medical calls involving patients with chest pain was carried out. A stratified purposive sampling was used to obtain calls concerning patients with high-risk conditions. These calls were then listened to and transcribed. Thereafter, meaning units were identified and coded and finally categorised. Consolidated criteria for reporting qualitative studies guidelines have been applied.

RESULTS

A wide range of situational information and symptoms descriptions was found. Pain and affected breathing were dominating aspects, but other situational information and several other symptoms were also reported. The situational information and these symptoms were classified into seven categories: Pain narrative, Affected breathing, Bodily reactions, Time, Bodily whereabouts, Fear and concern and Situation management. The seven categories consisted of 17 subcategories.

CONCLUSIONS

Patients with chest pain caused by a high-risk condition present a wide range of symptoms which are described in a variety of ways. They describe different kinds of chest pain accompanied by pain from other parts of the body. Breathing difficulties and bodily reactions such as muscle weakness are also reported. The variety of symptoms and the absence of a typical symptomatology make risk stratification on the basis of symptoms alone difficult.

RELEVANCE TO CLINICAL PRACTICE

This study highlights the importance of an open mind when assessing patients with chest pain and the requirement of a decision support tool in order to improve risk stratification in these patients.

Does dispatcher-assisted bystander CPR improve outcomes from adult out-of-hospital cardiac arrest?

This short review addresses the evidence behind dispatcher-assisted CPR (DA-CPR) and whether it contributes to overall survival of out-of-hospital cardiac arrest (OHCA). Six papers directly addressed the review question and were selected for appraisal, including one systematic review. The outcomes of these studies demonstrate variable results from the implementation of DA-CPR strategies. While DA-CPR has some utility as a substitute for spontaneously delivered bystander CPR, available evidence suggests there is scope to improve. Further work should focus on the identification and adoption of more effective protocols.

Predictive Modeling of 30-Day Emergency Hospital Transport of Patients Using a Personal Emergency Response System: Prognostic Retrospective Study

BACKGROUND

Telehealth programs have been successful in reducing 30-day readmissions and emergency department visits. However, such programs often focus on the costliest patients with multiple morbidities and last for only 30 to 60 days postdischarge. Inexpensive monitoring of elderly patients via a personal emergency response system (PERS) to identify those at high risk for emergency hospital transport could be used to target interventions and prevent avoidable use of costly readmissions and emergency department visits after 30 to 60 days of telehealth use.

OBJECTIVE

The objectives of this study were to (1) develop and validate a predictive model of 30-day emergency hospital transport based on PERS data; and (2) compare the model's predictions with clinical outcomes derived from the electronic health record (EHR).

METHODS

We used deidentified medical alert pattern data from 290,434 subscribers to a PERS service to build a gradient tree boosting-based predictive model of 30-day hospital transport, which included predictors derived from subscriber demographics, self-reported medical conditions, caregiver network information, and up to 2 years of retrospective PERS medical alert data. We evaluated the model's performance on an independent validation cohort (n=289,426). We linked EHR and PERS records for 1815 patients from a home health care program to compare PERS-based risk scores with rates of emergency encounters as recorded in the EHR.

RESULTS

In the validation cohort, 2.22% (6411/289,426) of patients had 1 or more emergency transports in 30 days. The performance of the predictive model of emergency hospital transport, as evaluated by the area under the receiver operating characteristic curve, was 0.779 (95% CI 0.774-0.785). Among the top 1% of predicted high-risk patients, 25.5% had 1 or more emergency hospital transports in the next 30 days. Comparison with clinical outcomes from the EHR showed 3.9 times more emergency encounters among predicted high-risk patients than low-risk patients in the year following the prediction date.

CONCLUSIONS

Patient data collected remotely via PERS can be used to reliably predict 30-day emergency hospital transport. Clinical observations from the EHR showed that predicted high-risk patients had nearly four times higher rates of emergency encounters than did low-risk patients. Health care providers could benefit from our validated predictive model by targeting timely preventive interventions to high-risk patients. This could lead to overall improved patient experience, higher quality of care, and more efficient resource utilization.

Public knowledge and expectations about dispatcher assistance in out-of-hospital cardiac arrest

AIM

To assess the factors associated with the knowledge and expectations among the general public about dispatcher assistance in out-of-hospital cardiac arrest incidents.

BACKGROUND

In medical dispatch centres, emergency calls are frequently operated by specially trained nurses as dispatchers. In cardiac arrest incidents, efficient communication between the dispatcher and the caller is vital for prompt recognition and treatment of the cardiac arrest.

DESIGN

A cross-sectional observational survey containing six questions and seven demographic items.

METHOD

From January-June 2017 we conducted standardized interviews among 500 members of the general public in Norway. In addition to explorative statistical methods, we used multivariate logistic analysis.

RESULTS

Most participants expected cardiopulmonary resuscitation instructions, while few expected "help in deciding what to do." More than half regarded the bystanders present to be responsible for the decision to initiate cardiopulmonary resuscitation. Most participants were able to give the correct emergency medical telephone number. The majority knew that the emergency call would not be terminated until the ambulance arrived at the scene. However, only one-third knew that the emergency telephone number operator was a trained nurse.

CONCLUSION

The public expect cardiopulmonary resuscitation instructions from the emergency medical dispatcher. However, the majority assume it is the responsibility of the bystanders to make the decision to initiate cardiopulmonary resuscitation or not. Based on these findings, cardiopulmonary resuscitation training initiatives and public campaigns should focus more on the role of the emergency medical dispatcher as the team leader of the first resuscitation team in cardiac arrest incidents.

Factors affecting emergency medical dispatchers' decision-making: a qualitative study

Introduction

Prehospital emergency medical service dispatchers should make prompt and appropriate decisions to save the life of victims. The complexity of timely and reasonable decision-making in life-threatening conditions has driven researchers to investigate varying aspects of the emergency medical dispatch (EMD) process. The purpose of this study was to explore the contributors to appropriate and prompt decision-making among dispatchers.

Methods

A qualitative study through thematic analysis was designed. Data were collected using observation and semistructured interviews with 16 authorities and dispatchers in seven EMDs across Iran.

Results

The study found “responsiveness” as the main category contributing to improved decision-making in EMD. The components introduced in this study for dispatchers’ responsiveness consisted of two categories. The first was “personal values” including faith and belief, eagerness to help, service excellence, altruism, respect, and impartiality in clinical judgment. The second was “professional attitudes” resulting from education and experience, including the recognition of emergency as a threat to health, sensitivity in triage, response to all requests for help, care for early warnings, commitment to organizational goals and standards, attention to the emergency medical service social support responsibility, and professional temperance.

Conclusion

In this study, responsiveness was identified as a main category in improving the decision-making process among dispatchers. To attain responsiveness, institutionalization of its values and establishment of EMD-specific professional attitudes in dispatchers should be taken into consideration.

Can a Software-Based Metronome Tool Enhance Compression Rate in a Realistic 911 Call Scenario Without Adversely Impacting Compression Depth for Dispatcher-Assisted CPR?

IntroductionImplementation of high-quality, dispatcher-assisted cardiopulmonary resuscitation (DA-CPR) is critical to improving survival from out-of-hospital cardiac arrest (OHCA). However, despite some studies demonstrating the use of a metronome in a stand-alone setting, no research has yet demonstrated the effectiveness of a metronome tool in improving DA-CPR in the context of a realistic 911 call or using instructions that have been tested in real-world emergency calls.HypothesisUse of the metronome tool will increase the proportion of callers able to perform CPR within the target rate without affecting depth.

METHODS

The prospective, randomized, controlled study involved simulated 911 cardiac arrest calls made by layperson-callers and handled by certified emergency medical dispatchers (EMDs) at four locations in Salt Lake City, Utah USA. Participants were randomized into two groups. In the experimental group, layperson-callers received CPR pre-arrival instructions with metronome assistance. In the control group, layperson-callers received only pre-arrival instructions. The primary outcome measures were correct compression rate (counts per minute [cpm]) and depth (mm).

RESULTS

A total of 148 layperson-callers (57.4% assigned to experimental group) participated in the study. There was a statistically significant association between the number of participants who achieved the target compression rate and experimental study group (P=.003), and the experimental group had a significantly higher median compression rate than the control group (100 cpm and 89 cpm, respectively; P=.013). Overall, there was no significant correlation between compression rate and depth.

CONCLUSION

An automated software metronome tool is effective in getting layperson-callers to achieve the target compression rate and compression depth in a realistic DA-CPR scenario.Scott G, Barron T, Gardett I, Broadbent M, Downs H, Devey L, Hinterman EJ, Clawson J, Olola C. Can a software-based metronome tool enhance compression rate in a realistic 911 call scenario without adversely impacting compression depth for dispatcher-assisted CPR? Prehosp Disaster Med. 2018;33(4):399-405.

Effect of Dial-Out Prefix Change on 9-1-1 Calls at a Large State University

BACKGROUND

Accessing the emergency medical services system via 9-1-1 operators is an effective way for patients to seek urgent health care; however, technological advances and telecommunication practices inundate the 9-1-1 and emergency services infrastructure with unintentional calls that delay response efforts to legitimate medical emergencies.

OBJECTIVE

To determine whether the change in university-wide dial-out prefix from "9" to "7" reduced unnecessary calls to a 9-1-1 call center.

METHODS

This is a retrospective study conducted utilizing information obtained from the University of North Carolina at Chapel Hill (UNC) Department of Public Safety (DPS) call center. Call center calls received during pre-change, intervening, and post-change periods were included in the study. The cost savings, defined in time and money, resulting from the prefix change were also examined.

RESULTS

A total of 33,646 calls were made during the study period (January 11, 2010 through December 31, 2012) and included in the analysis. The prefix change was found to reduce the rate of invalid calls to the call center by 319 calls per month, resulting in a 43% reduction in total calls to the call center while preserving the rate of valid calls. The largest decrease occurred in hang-up calls (a decrease of 232 calls per month), especially those originating from the university. The prefix change was found to save the UNC DPS telecommunications division approximately $798.82 per month and the police officer division approximately $3,874.95 per month.

CONCLUSION

A prefix change was not only beneficial to the UNC community but it also has potentially wide-reaching effects. A reduction of invalid 9-1-1 calls translates to telecommunicators having more time available to handle true emergencies, phone lines remaining available for true emergencies, and police officers dedicating more time and effort to matters that necessitate officer assistance. Based on the call decrease seen with the prefix change, this study may be used as evidence to advocate for a change of dial-out codes beginning with "9."

Identifying Key Words in 9-1-1 Calls for Stroke: A Mixed Methods Approach

OBJECTIVES

Identifying stroke during a 9-1-1 call is critical to timely prehospital care. However, emergency medical dispatchers (EMDs) recognize stroke in less than half of 9-1-1 calls, potentially due to the words used by callers to communicate stroke signs and symptoms. We hypothesized that callers do not typically use words and phrases considered to be classical descriptors of stroke, such as focal neurologic deficits, but that a mixed-methods approach can identify words and phrases commonly used by 9-1-1 callers to describe acute stroke victims.

METHODS

We performed a mixed-method, retrospective study of 9-1-1 call audio recordings for adult patients with confirmed stroke who were transported by ambulance in a large urban city. Content analysis, a qualitative methodology, and computational linguistics, a quantitative methodology, were used to identify key words and phrases used by 9-1-1 callers to describe acute stroke victims. Because a caller's level of emotional distress contributes to the communication during a 9-1-1 call, the Emotional Content and Cooperation Score was scored by a multidisciplinary team.

RESULTS

A total of 110 9-1-1 calls, received between June and September 2013, were analyzed. EMDs recognized stroke in 48% of calls, and the emotional state of most callers (95%) was calm. In 77% of calls in which EMDs recognized stroke, callers specifically used the word "stroke"; however, the word "stroke" was used in only 38% of calls. Vague, non-specific words and phrases were used to describe stroke victims' symptoms in 55% of calls, and 45% of callers used distractor words and phrases suggestive of non-stroke emergencies. Focal neurologic symptoms were described in 39% of calls. Computational linguistics identified 9 key words that were more commonly used in calls where the EMD identified stroke. These words were concordant with terms identified through qualitative content analysis.

CONCLUSIONS

Most 9-1-1 callers used vague, non-specific, or distractor words and phrases and infrequently provide classic stroke descriptions during 9-1-1 calls for stroke. Both qualitative and quantitative methodologies identified similar key words and phrases associated with accurate EMD stroke recognition. This study suggests that tools incorporating commonly used words and phrases could potentially improve EMD stroke recognition.

9-1-1 Triage of Non-Traumatic Chest Pain: Association with Hospital Diagnosis

OBJECTIVE

Chest pain is one of the most common reasons people seek emergency care-and one of the most critical. In the United States, chest pain is the second most common reason for emergency department (ED) visits. A patient's primary complaint of "chest pain" may reflect a broad range of underlying causes; therefore, it is important that emergency medical service (EMS) agencies gain a thorough understanding of these cases, beginning with the initial management of chest pain in the 9-1-1 center. The primary objective of this study was to compare hospital-confirmed patient discharge diagnoses to all calls handled by emergency medical dispatchers (EMDs) using the Chest Pain/Chest Discomfort (Non-Traumatic) Chief Complaint Protocol.

METHODS

The retrospective descriptive study utilized emergency medical dispatch, EMS, and hospital datasets, collected at two emergency communication centers in North America, from January 1, 2013 to December 31, 2014. Patients who were dispatched using the Chest Pain/Chest Discomfort Chief Complaint Protocol and matched to hospital datasets were included. The primary outcome was the number and percentage of cases classified as ischemic heart disease (IHD), other cardiac-related conditions, or non-cardiac-related conditions associated with chest pain. We also evaluated the distribution of causes of chest pain across demographic indicators and dispatch determinants.

RESULTS

3,007 cases were identified as "chest pain" at dispatch for which corresponding hospital records were identified. Cases in the study were obtained by linking EMS/Hospital and Emergency Medical Dispatch datasets. Of these cases, 47.1% (n = 1,417) were due to cardiac-related causes of chest pain, 61.5% of which were Ischemic Heart Disease (IHD), while the rest had other cardiac-related causes. Of the IHDs, 32.1% were Acute Myocardial Infarction (AMI).

CONCLUSIONS

Underlying causes of non-traumatic chest pain reported to 9-1-1 demonstrate a wide range of etiologies, with a mix similar to that of chest pain patients in several other healthcare settings, including hospital emergency departments. Most IHD events are triaged by EMDs to the (highest) DELTA priority level, while the CHARLIE level captures nearly all of the remaining IHD cases.

The Danish quality database for prehospital emergency medical services

AIM OF DATABASE

The aim of the Danish quality database for prehospital emergency medical services (QEMS) is to assess, monitor, and improve the quality of prehospital emergency medical service care in the entire prehospital patient pathway. The aim of this review is to describe the design and the implementation of QEMS.

STUDY POPULATION

The study population consists of all "112 patient contacts" defined as emergency patients, where the entrance to health care is a 112 call forwarded to one of the five regional emergency medical coordination centers in Denmark since January 1, 2014. Estimated annual number of included "112 patients" is 300,000-350,000.

MAIN VARIABLES

We defined nine quality indicators and the following variables: time stamps for emergency calls received at one of the five regional emergency medical coordination centers, dispatch of prehospital unit(s), arrival of first prehospital unit, arrival of first supplemental prehospital unit, and mission completion. Finally, professional level and type of the prehospital resource dispatched to an incident and end-of-mission status (mission completed by phone, on scene, or admission to hospital) are registered.

DESCRIPTIVE DATA

Descriptive data included age, region, and Danish Index for Emergency Care including urgency level.

CONCLUSION

QEMS is a new database under establishment and is expected to provide the basis for quality improvement in the prehospital setting and in the entire patient care pathway, for example, by providing prehospital data for research and other quality databases.