The obstacles to maximising the impact of public access defibrillation: an assessment of the dispatch mechanism for out-of-hospital cardiac arrest

European Resuscitation Council Guidelines 2021: Systems saving lives

The European Resuscitation Council (ERC) has produced these Systems Saving Lives guidelines, which are based on the 2020 International Consensus on Cardiopulmonary Resuscitation Science with Treatment Recommendations. The topics covered include chain of survival, measuring performance of resuscitation, social media and smartphones apps for engaging community, European Restart a Heart Day, World Restart a Heart, KIDS SAVE LIVES campaign, lower-resource setting, European Resuscitation Academy and Global Resuscitation Alliance, early warning scores, rapid response systems, and medical emergency team, cardiac arrest centres and role of dispatcher.

Unrecognized Out of Hospital Cardiac Arrest Symptoms during Thailand’s Emergency Medical Services

BACKGROUND: To improve survival rate, the main focus of adult cardiac arrest management includes rapid recognition, prompt administration of cardiopulmonary resuscitation (CPR), defibrillation for shockable rhythms, post-return of spontaneous circulation (ROSC) care, and identification and treatment of underlying causes. This study aimed to identify the determinants of unrecognized cardiac arrest, and to study the recognition rate of out-of-hospital cardiac arrest (OHCA) by emergency medical services call handlers. METHODS: We included OHCA patients who were transferred to hospital via Emergency Medical Services (EMS) of Srinagarind hospital, Khon Kaen, Thailand, from 1st January 2020 to 31st December 2020. The primary outcome was to identify symptoms that lead to an unrecognized cardiac arrest by the EMS call handlers. Secondary outcomes were to identify the recognition rate of OHCA by emergency medical services call handlers, and assess the outcome of CPR performed on OHCA patients. RESULTS: There were a total of 58 patients in the present study, 26 patients (44.8%) and 32 patients (55.2%) belonged to the unrecognized and recognized cardiac arrest groups, respectively. The most common symptoms that led to unrecognized cardiac arrest were a state of unconsciousness (46.2%), major trauma (15.4%), and seizure-like activity (11.5%). The rate of ROSC was higher in the unrecognized cardiac arrest group (34.6% vs. 15.6%) but the rate of survival to hospital discharge was higher in the recognized cardiac arrest group (6.3% vs 0%). CONCLUSIONS: Falling unconscious is the most common symptom of unrecognized OHCA cases seen by EMS in Thailand. Basic life support, especially an immediate assessment of a patient’s respiratory status should be taught in health programs in school or through public service channels.

Predictors of recognition of out of hospital cardiac arrest by emergency medical services call handlers in England: a mixed methods diagnostic accuracy study

Background

The 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.

Methods

Retrospective, 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.

Results

A 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).

Conclusions

There 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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13049-020-00823-9.

Diagnosis of out-of-hospital cardiac arrest by emergency medical dispatch: A diagnostic systematic review

INTRODUCTION

Cardiac arrest is a time-sensitive condition requiring urgent intervention. Prompt and accurate recognition of cardiac arrest by emergency medical dispatchers at the time of the emergency call is a critical early step in cardiac arrest management allowing for initiation of dispatcher-assisted bystander CPR and appropriate and timely emergency response. The overall accuracy of dispatchers in recognizing cardiac arrest is not known. It is also not known if there are specific call characteristics that impact the ability to recognize cardiac arrest.

METHODS

We performed a systematic review to examine dispatcher recognition of cardiac arrest as well as to identify call characteristics that may affect their ability to recognize cardiac arrest at the time of emergency call. We searched electronic databases for terms related to "emergency medical dispatcher", "cardiac arrest", and "diagnosis", among others, with a focus on studies that allowed for calculating diagnostic test characteristics (e.g. sensitivity and specificity). The review was consistent with Grading of Recommendations, Assessment, Development and Evaluation (GRADE) method for evidence evaluation.

RESULTS

We screened 2520 article titles, resulting in 47 studies included in this review. There was significant heterogeneity between studies with a high risk of bias in 18 of the 47 which precluded performing meta-analyses. The reported sensitivities for cardiac arrest recognition ranged from 0.46 to 0.98 whereas specificities ranged from 0.32 to 1.00. There were no obvious differences in diagnostic accuracy between different dispatching criteria/algorithms or with the level of education of dispatchers.

CONCLUSION

The sensitivity and specificity of cardiac arrest recognition at the time of emergency call varied across dispatch centres and did not appear to differ by dispatch algorithm/criteria used or education of the dispatcher, although comparisons were hampered by heterogeneity across studies. Future efforts should focus on ways to improve sensitivity of cardiac arrest recognition to optimize patient care and ensure appropriate and timely resource utilization.

Adult Basic Life Support: International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations

This 2020 International Consensus on Cardiopulmonary Resuscitation (CPR) and Emergency Cardiovascular Care Science With Treatment Recommendations on basic life support summarizes evidence evaluations performed for 20 topics that were prioritized by the Basic Life Support Task Force of the International Liaison Committee on Resuscitation. The evidence reviews include 16 systematic reviews, 3 scoping reviews, and 1 evidence update. Per agreement within the International Liaison Committee on Resuscitation, new or revised treatment recommendations were only made after a systematic review.

Systematic reviews were performed for the following topics: dispatch diagnosis of cardiac arrest, use of a firm surface for CPR, sequence for starting CPR (compressions-airway-breaths versus airway-breaths-compressions), CPR before calling for help, duration of CPR cycles, hand position during compressions, rhythm check timing, feedback for CPR quality, alternative techniques, public access automated external defibrillator programs, analysis of rhythm during chest compressions, CPR before defibrillation, removal of foreign-body airway obstruction, resuscitation care for suspected opioid-associated emergencies, drowning, and harm from CPR to victims not in cardiac arrest.

The topics that resulted in the most extensive task force discussions included CPR during transport, CPR before calling for help, resuscitation care for suspected opioid-associated emergencies, feedback for CPR quality, and analysis of rhythm during chest compressions. After discussion of the scoping reviews and the evidence update, the task force prioritized several topics for new systematic reviews.

Adult Basic Life Support: 2020 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations

This2020 International Consensus on Cardiopulmonary Resuscitation(CPR)and Emergency Cardiovascular Care Science With Treatment Recommendationson basic life support summarizes evidence evaluations performed for 22 topics that were prioritized by the Basic Life Support Task Force of the International Liaison Committee on Resuscitation. The evidence reviews include 16 systematic reviews, 5 scoping reviews, and 1 evidence update. Per agreement within the International Liaison Committee on Resuscitation, new or revised treatment recommendations were only made after a systematic review.

Systematic reviews were performed for the following topics: dispatch diagnosis of cardiac arrest, use of a firm surface for CPR, sequence for starting CPR (compressions-airway-breaths versus airway-breaths-compressions), CPR before calling for help, duration of CPR cycles, hand position during compressions, rhythm check timing, feedback for CPR quality, alternative techniques, public access automated external defibrillator programs, analysis of rhythm during chest compressions, CPR before defibrillation, removal of foreign-body airway obstruction, resuscitation care for suspected opioid-associated emergencies, drowning, and harm from CPR to victims not in cardiac arrest.

The topics that resulted in the most extensive task force discussions included CPR during transport, CPR before calling for help, resuscitation care for suspected opioid-associated emergencies, feedback for CPR quality, and analysis of rhythm during chest compressions. After discussion of the scoping reviews and the evidence update, the task force prioritized several topics for new systematic reviews.

Machine learning as a supportive tool to recognize cardiac arrest in emergency calls

BACKGROUND

Emergency medical dispatchers fail to identify approximately 25% of cases of out of hospital cardiac arrest, thus lose the opportunity to provide the caller instructions in cardiopulmonary resuscitation. We examined whether a machine learning framework could recognize out-of-hospital cardiac arrest from audio files of calls to the emergency medical dispatch center.

METHODS

For all incidents responded to by Emergency Medical Dispatch Center Copenhagen in 2014, the associated call was retrieved. A machine learning framework was trained to recognize cardiac arrest from the recorded calls. Sensitivity, specificity, and positive predictive value for recognizing out-of-hospital cardiac arrest were calculated. The performance of the machine learning framework was compared to the actual recognition and time-to-recognition of cardiac arrest by medical dispatchers.

RESULTS

We examined 108,607 emergency calls, of which 918 (0.8%) were out-of-hospital cardiac arrest calls eligible for analysis. Compared with medical dispatchers, the machine learning framework had a significantly higher sensitivity (72.5% vs. 84.1%, p < 0.001) with lower specificity (98.8% vs. 97.3%, p < 0.001). The machine learning framework had a lower positive predictive value than dispatchers (20.9% vs. 33.0%, p < 0.001). Time-to-recognition was significantly shorter for the machine learning framework compared to the dispatchers (median 44 seconds vs. 54 s, p < 0.001).

CONCLUSIONS

A machine learning framework performed better than emergency medical dispatchers for identifying out-of-hospital cardiac arrest in emergency phone calls. Machine learning may play an important role as a decision support tool for emergency medical dispatchers.

Recognition of out-of-hospital cardiac arrest during emergency calls - a systematic review of observational studies

Background

The medical dispatcher plays an essential role as part of the first link in the Chain of Survival, by recognising the out-of-hospital cardiac arrest (OHCA) during the emergency call, dispatching the appropriate first responder or emergency medical services response, performing dispatcher assisted cardiopulmonary resuscitation, and referring to the nearest automated external defibrillator. The objective of this systematic review was to evaluate and compare studies reporting recognition of OHCA patients during emergency calls.

Methods

This systematic review was reported in compliance with the PRISMA guidelines. We systematically searched MEDLINE, Embase and the Cochrane Library on 4 November 2015. Observational studies, reporting the proportion of clinically confirmed OHCAs that was recognised during the emergency call, were included. Two authors independently screened abstracts and full-text articles for inclusion. Data were extracted and the risk of bias within studies was assessed using the QUADAS-2 tool for quality assessment of diagnostic accuracy studies.

Results

A total of 3,180 abstracts were screened for eligibility and 53 publications were assessed in full-text. We identified 16 studies including 6,955 patients that fulfilled the criteria for inclusion in the systematic review. The studies reported recognition of OHCA with a median sensitivity of 73.9% (range: 14.1–96.9%). The selection of study population and the definition of “recognised OHCA” (threshold for positive test) varied greatly between the studies, resulting in high risk of bias. Heterogeneity in the studies precluded meta-analysis.

Conclusion

Among the 16 included studies, we found a median sensitivity for OHCA recognition of 73.9% (range: 14.1–96.9%). However, great heterogeneity between study populations and in the definition of “recognised OHCA”, lead to insufficient comparability of results. Uniform and transparent reporting is required to ensure comparability and development towards best practice.

Part 3: Adult Basic Life Support and Automated External Defibrillation: 2015 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations

This review comprises the most extensive literature search and evidence evaluation to date on the most important international BLS interventions, diagnostics, and prognostic factors for cardiac arrest victims. It reemphasizes that the critical lifesaving steps of BLS are (1) prevention, (2) immediate recognition and activation of the emergency response system, (3) early high-quality CPR, and (4) rapid defibrillation for shockable rhythms. Highlights in prevention indicate the rational and judicious deployment of search-and-rescue operations in drowning victims and the importance of education on opioid-associated emergencies. Other 2015 highlights in recognition and activation include the critical role of dispatcher recognition and dispatch-assisted chest compressions, which has been demonstrated in multiple international jurisdictions with consistent improvements in cardiac arrest survival. Similar to the 2010 ILCOR BLS treatment recommendations, the importance of high quality was reemphasized across all measures of CPR quality: rate, depth, recoil, and minimal chest compression pauses, with a universal understanding that we all should be providing chest compressions to all victims of cardiac arrest. This review continued to focus on the interface of BLS sequencing and ensuring high-quality CPR with other important BLS interventions, such as ventilation and defibrillation. In addition, this consensus statement highlights the importance of EMS systems, which employ bundles of care focusing on providing high-quality chest compressions while extricating the patient from the scene to the next level of care. Highlights in defibrillation indicate the global importance of increasing the number of sites with public-access defibrillation programs. Whereas the 2010 ILCOR Consensus on Science provided important direction for the “what” in resuscitation (ie, what to do), the 2015 consensus has begun with the GRADE methodology to provide direction for the quality of resuscitation. We hope that resuscitation councils and other stakeholders will be able to translate this body of knowledge of international consensus statements to build their own effective resuscitation guidelines.

Barriers to recognition of out-of-hospital cardiac arrest during emergency medical calls: a qualitative inductive thematic analysis

Background

The chance of surviving out-of-hospital cardiac arrest (OHCA) depends on early and correct recognition of cardiac arrest by the emergency medical dispatcher during the emergency call. When cardiac arrest is identified, telephone guided cardiopulmonary resuscitation (CPR) and referral to an automated external defibrillator should be initiated. Previous studies have investigated barriers to recognition of OHCA, and found the caller’s description of sign of life, the type of caller, caller’s emotional state, an inadequate dialogue during the emergency call, and patient’s agonal breathing as influential factors. Though many of these factors are included in the algorithms used by medical dispatchers, many OHCA still remain not recognised. Qualitative studies investigating the communication between the caller and dispatcher are very scarce. There is a lack of knowledge about what influences the dispatchers’ recognition of OHCA, focusing on the communication during the emergency call.

The purpose of this study is to identify factors affecting medical dispatchers’ recognition of OHCA during emergency calls in a qualitative analysis of calls.

Methods

An investigator triangulated inductive thematic analysis of recordings of out-of-hospital cardiac arrest emergency calls from December 2012. Participants were the callers (bystanders) and the emergency medical dispatchers. Data were analysed using a hermeneutic approach.

Results

Based on the concept of data saturation, 13 recordings of not recognised cardiac arrest and 8 recordings of recognised cardiac arrests were analysed. Three main themes, six subthemes and an embedded theme emerged from the analysis: caller’s physical distance (caller near patient, caller not near patient), caller’s emotional distance (keeping calm, losing control), caller is a healthcare professional (responsibility is handed over to the caller, caller assumes responsibility), and the embedded theme: caller assesses the patient.

Conclusion

The physical and emotional proximity of the caller (bystander) as well as the caller’s professional background affect the dispatcher’s chances of correct recognition and handling of cardiac arrest. The dispatcher should acknowledge the triple roles of conducting patient assessment, instructing the caller, and reassuring the emotionally affected caller.

Cardiac arrest management in general practice in Ireland: a 5-year cross-sectional study

OBJECTIVE

To document the involvement of general practitioners (GPs) in cardiac arrests with resuscitation attempts (CARAs) and to describe the outcomes.

DESIGN

A 5-year prospective cross-sectional study of GPs in Ireland equipped with automated external defibrillators (AEDs) and immediate care training by the MERIT Project, with data collection every 3 months over the 5-year period. Practices reported CARAs by quarterly survey with an 89% mean response rate (81-97% for the period).

SETTING

General practices throughout Ireland.

PARTICIPANTS

495 GP participated: 168 (33.9%) urban, 163 (32.9%) rural and 164 (33.1%) mixed.

INTERVENTIONS

All participating practices received a standard AED and basic life support kit. Training in immediate care was provided for at least one GP in the practice.

MAIN OUTCOME MEASURES

Incidence of CARA in participating practices. Return of spontaneous circulation (ROSC) and discharge alive from hospital.

RESULTS

36% of practices were involved in a CARA during the 5-year period and 13% were involved in more than one CARA. Of the 272 CARAs reported, ROSC occurred in 32% (87/272) and discharge from hospital in 18.7% (49/262). In 45% of cases, the first AED was brought by the GP and in 65%, the GP arrived before the ambulance service. More cases occurred in rural and mixed settings than urban ones, but the survival rates did not differ between areas. In 65% of cases, the GP was on duty at the time of the incident and 47% of cases occurred in the patient's home.

CONCLUSIONS

These outcomes are comparable with more highly structured components of the emergency response system and indicate that GPs have an important role to play in the care of patients in their own communities. GPs experience cardiac arrest cases during the course of their daily work and provide prompt care which results in successful outcomes in urban, mixed and rural settings.

In out-of-hospital cardiac arrest patients, does the description of any specific symptoms to the emergency medical dispatcher improve the accuracy of the diagnosis of cardiac arrest: a systematic review of the literature

AIM

We sought to determine if, in patients with out-of-hospital cardiac arrest (OHCA), the description of any specific symptoms to the emergency medical dispatcher (EMD) improved the accuracy of the diagnosis of cardiac arrest.

METHODS

For this systematic review, we searched MEDLINE, EMBASE and the Cochrane Library with no restrictions, and hand-searched the gray literature. Eligible studies included dispatcher interaction with callers reporting OHCA, and reported diagnosis of cardiac arrest. Two independent reviewers used standardized forms and procedures to review papers for inclusion, quality, and to extract data from eligible studies. Findings were peer-reviewed by the International Liaison Committee on Resuscitation.

RESULTS

We identified 494 citations; 74 were selected for full evaluation (kappa=0.70) and 23 were included (kappa=0.68), including six before-after, two case-control, and 15 descriptive studies. One before-after study and ten descriptive studies report that inquiring about consciousness and breathing status can help dispatchers recognize cardiac arrest with moderate sensitivity [ranging from 38% to 97%], and high specificity [ranging from 95% to 99%]. One case-control study, three before-after studies, and four observational studies report that abnormal breathing is a significant barrier to cardiac arrest recognition. One before-after study and two descriptive studies report that seizure activity can be a manifestation of cardiac arrest.

CONCLUSION

Dispatchers should recognize cardiac arrest when a victim is described as unconscious and not breathing or not breathing normally, and consider cardiac arrest when generalized seizure is described. They should receive specific instructions on how to best recognize the presence of abnormal breathing.