Features of Emergency Medical System calls that facilitate or inhibit Emergency Medical Dispatcher recognition that a patient is in, or at imminent risk of, cardiac arrest: A systematic mixed studies review.
Ontology highlight
ABSTRACT: Aim
To identify and appraise evidence relating to the features of an Emergency Medicine System call interaction that enable, or inhibit, an Emergency Medical Dispatcher's recognition that a patient is in out-of-hospital cardiac arrest, or at imminent risk of out-of-hospital cardiac arrest.Methods
All study designs were eligible for inclusion. Data sources included Medline, BNI, CINAHL, EMBASE, PubMed, Cochrane Database of Systematic Reviews, AMED and OpenGrey. Stakeholder resources were screened and experts in resuscitation were asked to review the studies identified. Studies were appraised using the Mixed Methods Appraisal Tool. Synthesis was completed using a segregated mixed research synthesis approach.Results
Thirty-two studies were included in the review. Three main themes were identified: Key features of the Emergency Medical Service call interaction; Managing the Emergency Medical Service call; Emotional distress.Conclusion
A dominant finding is the difficulty in recognising abnormal/agonal breathing during the Emergency Medical Service call. The interaction between the caller and the Emergency Medical Dispatcher is critical in the recognition of patients who suffer an out-of-hospital cardiac arrest. Emergency Medical Dispatchers adapt their approach to the Emergency Medical Service call, and regular training for Emergency Medical Dispatchers is recommended to optimise out-of-hospital cardiac arrest recognition. Further research is required with a focus on the Emergency Medical Service call interaction of patients who are alive at the time of the Emergency Medical Service call and who later deteriorate into OHCA.PROSPERO registration: CRD42019155458.
SUBMITTER: Kirby K
PROVIDER: S-EPMC8605417 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:ImportanceEmergency medical dispatchers fail to identify approximately 25% of cases of out-of-hospital cardiac arrest (OHCA), resulting in lost opportunities to save lives by initiating cardiopulmonary resuscitation.ObjectiveTo examine how a machine learning model trained to identify OHCA and alert dispatchers during emergency calls affected OHCA recognition and response.Design, setting, and participantsThis double-masked, 2-group, randomized clinical trial analyzed all calls to emergency number 112 (equivalent to 911) in Denmark. Calls were processed by a machine learning model using speech recognition software. The machine learning model assessed ongoing calls, and calls in which the model identified OHCA were randomized. The trial was performed at Copenhagen Emergency Medical Services, Denmark, between September 1, 2018, and December 31, 2019.InterventionDispatchers in the intervention group were alerted when the machine learning model identified out-of-hospital cardiac arrest, and those in the control group followed normal protocols without alert.Main outcomes and measuresThe primary end point was the rate of dispatcher recognition of subsequently confirmed OHCA.ResultsA total of 169?049 emergency calls were examined, of which the machine learning model identified 5242 as suspected OHCA. Calls were randomized to control (2661 [50.8%]) or intervention (2581 [49.2%]) groups. Of these, 336 (12.6%) and 318 (12.3%), respectively, had confirmed OHCA. The mean (SD) age among of these 654 patients was 70 (16.1) years, and 419 of 627 patients (67.8%) with known gender were men. Dispatchers in the intervention group recognized 296 confirmed OHCA cases (93.1%) with machine learning assistance compared with 304 confirmed OHCA cases (90.5%) using standard protocols without machine learning assistance (P?=?.15). Machine learning alerts alone had a significantly higher sensitivity than dispatchers without alerts for confirmed OHCA (85.0% vs 77.5%; P?<?.001) but lower specificity (97.4% vs 99.6%; P?<?.001) and positive predictive value (17.8% vs 55.8%; P?<?.001).Conclusions and relevanceThis randomized clinical trial did not find any significant improvement in dispatchers' ability to recognize cardiac arrest when supported by machine learning even though artificial intelligence did surpass human recognition.Trial registrationClinicalTrials.gov Identifier: NCT04219306.
| S-EPMC7788469 | biostudies-literature
Project description:PurposeStroke treatments are time-sensitive, and thus early and correct recognition of stroke by Emergency Medical Services is essential for outcomes. This is particularly important with the adaption of mobile stroke units. In this systematic review, we therefore aimed to provide a comprehensive overview of Emergency Medical Services dispatcher recognition of stroke.MethodsThe review was registered on PROSPERO and the PRISMA guidelines were applied. We searched PubMed, Embase, and Cochrane Review Library. Screening and data extraction were performed by two observers. Risk of bias was assessed using the QUADAS-2 instrument.FindingsOf 1200 papers screened, 24 fulfilled the inclusion criteria. Data on sensitivity was reported in 22 papers and varied from 17.9% to 83.0%. Positive predictive values were reported in 12 papers and ranged from 24.0% to 87.7%. Seven papers reported specificity, which ranged from 20.0% to 99.1%. Six papers reported negative predictive value, ranging from 28.0% to 99.4%. In general, the risk of bias was low.DiscussionStroke recognition by dispatchers varied greatly, but overall many patients with stroke are not recognised, despite the initiatives taken to improve stroke literacy. The available data are of high quality, however Asian, African, and South American populations are underrepresented.ConclusionWhile the data are heterogenous, this review can serve as a reference for future research in emergency medical dispatcher stroke recognition and initiatives to improve prehospital stroke recognition.
| S-EPMC11318428 | biostudies-literature
Project description:IntroductionEmergency telephone calls placed by bystanders are crucial to the recognition of out-of-hospital cardiac arrest (OHCA), fast ambulance dispatch and initiation of early basic life support. Clear and efficient communication between caller and call-taker is essential to this time-critical emergency, yet few studies have investigated the impact that linguistic factors may have on the nature of the interaction and the resulting trajectory of the call. This research aims to provide a better understanding of communication factors impacting on the accuracy and timeliness of ambulance dispatch.Methods and analysisA dataset of OHCA calls and their corresponding metadata will be analysed from an interdisciplinary perspective, combining linguistic analysis and health services research. The calls will be transcribed and coded for linguistic and interactional variables and then used to answer a series of research questions about the recognition of OHCA and the delivery of basic life-support instructions to bystanders. Linguistic analysis of calls will provide a deeper understanding of the interactional dynamics between caller and call-taker which may affect recognition and dispatch for OHCA. Findings from this research will translate into recommendations for modifications of the protocols for ambulance dispatch and provide directions for further research.Ethics and disseminationThe study has been approved by the Curtin University Human Research Ethics Committee (HR128/2013) and the St John Ambulance Western Australia Research Advisory Group. Findings will be published in peer-reviewed journals and communicated to key audiences, including ambulance dispatch professionals.
| S-EPMC5541602 | biostudies-literature
Project description:BACKGROUND:Little is known regarding paediatric medical emergency calls to Danish Emergency Medical Dispatch Centres (EMDC). This study aimed to investigate these calls, specifically the medical issues leading to them and the pre-hospital units dispatched to the paediatric emergencies. METHODS:We performed a retrospective, observational study on paediatric medical emergency calls managed by the EMDC in the Region of Southern Denmark in February 2016. We reviewed audio recordings of emergency calls and ambulance records to identify calls concerning patients ≤ 15 years. We examined EMDC dispatch records to establish how the medical issues leading to these calls were classified and which pre-hospital units were dispatched to the paediatric emergencies. We analysed the data using descriptive statistics. RESULTS:Of a total of 7052 emergency calls in February 2016, 485 (6.9%) concerned patients ≤ 15 years. We excluded 19 and analysed the remaining 466. The reported medical issues were commonly classified as: "seizures" (22.1%), "sick child" (18.9%) and "unclear problem" (12.9%). The overall most common pre-hospital response was immediate dispatch of an ambulance with sirens and lights with a supporting physician-manned mobile emergency care unit (56.4%). The classification of medical issues and the dispatched pre-hospital units varied with patient age. DISCUSSION:We believe our results might help focus the paediatric training received by emergency medical dispatch staff on commonly encountered medical issues, such as the symptoms and conditions pertaining to the symptom categories "seizures" and "sick child". Furthermore, the results could prove useful in hypothesis generation for future studies examining paediatric medical emergency calls. CONCLUSION:Almost 7% of all calls concerned patients ≤ 15 years. Medical issues pertaining to the symptom categories "seizures", "sick child" and "unclear problem" were common and the calls commonly resulted in urgent pre-hospital responses.
| S-EPMC5756442 | biostudies-literature
Project description:BackgroundThe European resuscitation council have highlighted emergency medical dispatch centres as an important key player for early recognition of Out-of-Hospital Cardiac Arrest (OHCA) and in providing dispatcher assisted cardiopulmonary resuscitation (CPR) before arrival of emergency medical services. Early recognition is associated with increased bystander CPR and improved survival rates. The aim of this study is to describe OHCA call handling in emergency medical dispatch centres in Copenhagen (Denmark), Stockholm (Sweden) and Oslo (Norway) with focus on sensitivity of recognition of OHCA, provision of dispatcher-assisted CPR and time intervals when CPR is initiated during the emergency call (NO-CPRprior), and to describe OHCA call handling when CPR is initiated prior to the emergency call (CPRprior).MethodsBaseline data of consecutive OHCA eligible for inclusion starting January 1st 2016 were collected from respective cardiac arrest registries. A template based on the Cardiac Arrest Registry to Enhance Survival definition catalogue was used to extract data from respective cardiac arrest registries and from corresponding audio files from emergency medical dispatch centres. Cases were divided in two groups: NO-CPRprior and CPRprior and data collection continued until 200 cases were collected in the NO-CPRprior-group.ResultsNO-CPRprior OHCA was recognised in 71% of the calls in Copenhagen, 83% in Stockholm, and 96% in Oslo. Abnormal breathing was addressed in 34, 7 and 98% of cases and CPR instructions were started in 50, 60, and 80%, respectively. Median time (mm:ss) to first chest compression was 02:35 (Copenhagen), 03:50 (Stockholm) and 02:58 (Oslo). Assessment of CPR quality was performed in 80, 74, and 74% of the cases. CPRprior comprised 71 cases in Copenhagen, 9 in Stockholm, and 38 in Oslo. Dispatchers still started CPR instructions in 41, 22, and 40% of the calls, respectively and provided quality assessment in 71, 100, and 80% in these respective instances.ConclusionsWe observed variations in OHCA recognition in 71-96% and dispatcher assisted-CPR were provided in 50-80% in NO-CPRprior calls. In cases where CPR was initiated prior to emergency calls, dispatchers were less likely to start CPR instructions but provided quality assessments during instructions.
| S-EPMC8247132 | biostudies-literature
Project description:BackgroundThe aim of this study was to identify key indicator symptoms and patient factors associated with correct out of hospital cardiac arrest (OHCA) dispatch allocation. In previous studies, from 3% to 62% of OHCAs are not recognised by Emergency Medical Service call handlers, resulting in delayed arrival at scene.MethodsRetrospective, mixed methods study including all suspected or confirmed OHCA patients transferred to one acute hospital from its associated regional Emergency Medical Service in England from 1/7/2013 to 30/6/2014. Emergency Medical Service and hospital data, including voice recordings of EMS calls, were analysed to identify predictors of recognition of OHCA by call handlers. Logistic regression was used to explore the role of the most frequently occurring (key) indicator symptoms and characteristics in predicting a correct dispatch for patients with OHCA.ResultsA total of 39,136 dispatches were made which resulted in transfer to the hospital within the study period, including 184 patients with OHCA. The use of the term 'Unconscious' plus one or more of symptoms 'Not breathing/Ineffective breathing/Noisy breathing' occurred in 79.8% of all OHCAs, but only 72.8% of OHCAs were correctly dispatched as such. 'Not breathing' was associated with recognition of OHCA by call handlers (Odds Ratio (OR) 3.76). The presence of key indicator symptoms 'Breathing' (OR 0.29), 'Reduced or fluctuating level of consciousness' (OR 0.24), abnormal pulse/heart rate (OR 0.26) and the characteristic 'Female patient' (OR 0.40) were associated with lack of recognition of OHCA by call handlers (p-values < 0.05).ConclusionsThere is a small proportion of calls in which cardiac arrest indicators are described but the call is not dispatched as such. Stricter adherence to dispatch protocols may improve call handlers' OHCA recognition. The existing dispatch protocol would not be improved by the addition of further terms as this would be at the expense of dispatch specificity.
| S-EPMC7789721 | biostudies-literature
Project description:BackgroundImmediate recognition of stroke symptoms is crucial to ensure timely access to revascularisation therapy. Medical dispatchers ensure fast admission to stroke facilities by prioritising the appropriate medical response. Data on medical dispatchers' ability to recognise symptoms of acute stroke are therefore critical in organising emergency stroke care. We aimed to describe the sensitivity and positive predictive value of medical dispatchers' ability to recognise acute stroke during emergency calls, and to identify factors associated with recognition.MethodsThis was an observational study of 2653 consecutive unselected patients with a final diagnosis of stroke or transient ischemic attack (TIA). All admitted through the Emergency Medical Services Copenhagen, during a 2-year study period (2012-2014). Final diagnoses were matched with dispatch codes from the Emergency Medical Dispatch Centre. Sensitivity and positive predictive value were calculated. The effect of age, gender, and time-of-day was analysed using multivariable logistic regression.ResultsThe sensitivity was 66.2 % (95 % CI: 64.4 %-68.0 %), and the positive predictive value was 30.2 % (95 % CI: 29.1 %-31.4 %). The multivariable logistic regression analyses showed that emergency calls during daytime and a final diagnosis of TIA vs. intracerebral haemorrhage (ICH), was positively associated with recognition of stroke (OR 2.70, 95 % CI: 2.04-3.57).DiscussionThis study reports a high rate of stroke recognition compared to other studies ranging from 31% to 74%. The high sensitivity is likely the result of a profound reorganisation of the Emergency Medical ServicesCopenhagen, including the introduction of EMDs with a medical profession, and a criteria-based dispatch tool. A recognition rate of 100 % is not obtainable without an inappropriate amount of false positive cases.ConclusionsWe report an overall high recognition of stroke by medical dispatchers. A final diagnosis of TIA, compared to ICH, was positively associated with recognition of acute stroke. Emergency medical dispatchers serve as the essential first step in ensuring fast-track stroke treatment, which would promote timely acute therapy.Trial registrationUnique identifier: NCT02191514.
| S-EPMC4936322 | biostudies-literature
Project description:BackgroundSince 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.MethodsThe 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.ResultsIt 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).ConclusionThe 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.
| S-EPMC9731330 | biostudies-literature
Project description:Background: With the rapid rise in opioid overdose-related deaths, state policy makers have expanded policies to increase the use of naloxone by emergency medical services (EMS). However, little is known about changes in EMS naloxone administration in the context of continued worsening of the opioid crisis and efforts to increase use of naloxone. This study examines trends in patient demographics and EMS response characteristics over time and by county urbanicity. Methods: We used data from the 2013-2016 National EMS Information System to examine trends in patient demographics and EMS response characteristics for 911-initiated incidents that resulted in EMS naloxone administration. We also assessed temporal, regional, and urban-rural variation in per capita rates of EMS naloxone administrations compared with per capita rates of opioid-related overdose deaths. Results: From 2013 to 2016, naloxone administrations increasingly involved young adults and occurred in public settings. Particularly in urban counties, there were modest but significant increases in the percentage of individuals who refused subsequent treatment, were treated and released, and received multiple administrations of naloxone before and after arrival of EMS personnel. Over the 4-year period, EMS naloxone administrations per capita increased at a faster rate than opioid-related overdose deaths across urban, suburban, and rural counties. Although national rates of naloxone administration were consistently higher in suburban counties, these trends varied across U.S. Census Regions, with the highest rates of suburban administration occurring in the South. Conclusions: Naloxone administration rates increased more quickly than opioid deaths across all levels of county urbanicity, but increases in the percentage of individuals requiring multiple doses and refusing subsequent care require further attention.
| S-EPMC6989345 | biostudies-literature
Project description:ObjectivesThe aim of this study is to describe the demographics of reported traumatic cardiac arrest (TCA) victims, prehospital resuscitation and survival to hospital rate.SettingHelicopter Emergency Medical Service (HEMS) in south-east England, covering a resident population of 4.5 million and a transient population of up to 8 million people.ParticipantsPatients reported on the initial 999 call to be in suspected traumatic cardiac arrest between 1 July 2016 and 31 December 2016 within the trust's geographical region were identified. The inclusion criteria were all cases of reported TCA on receipt of the initial emergency call. Patients were subsequently excluded if a medical cause of cardiac arrest was suspected.Outcome measuresPatient records were analysed for actual presence of cardiac arrest, prehospital resuscitation procedures undertaken and for survival to hospital rates.Results112 patients were reported to be in TCA on receipt of the 999/112 call. 51 (46%) were found not to be in TCA on arrival of emergency medical services. Of the 'not in TCA cohort', 34 (67%) received at least one advanced prehospital medical intervention (defined as emergency anaesthesia, thoracostomy, blood product transfusion or resuscitative thoracotomy). Of the 61 patients in actual TCA, 10 (16%) achieved return-of-spontaneous circulation. In 45 (88%) patients, the HEMS team escorted the patient to hospital.ConclusionA significant proportion of patients reported to be in TCA on receipt of the emergency call are not in actual cardiac arrest but are critically unwell requiring advanced prehospital medical intervention. Early activation of an enhanced care team to a reported TCA call allows appropriate advanced resuscitation. Further research is warranted to determine which interventions contribute to improved TCA survival.
| S-EPMC6129099 | biostudies-literature