The accuracy of medical dispatch - a systematic review

Mobile stroke units services in Germany: A cost-effectiveness modeling perspective on catchment zones, operating modes, and staffing

BACKGROUND AND PURPOSE

Investigating the cost-effectiveness of future mobile stroke unit (MSU) services with respect to local idiosyncrasies is essential for enabling large-scale implementation of MSU services. The aim of this study was to assess the cost-effectiveness for varying urban German settings and modes of operation.

METHODS

Costs of different operating times together with different personnel configurations were simulated. Different possible catchment zones, ischemic stroke incidence, circadian distribution, rates of alternative diagnoses, as well as missed cases were incorporated to model case coverage and patient numbers. Based on internationally reported clinical outcomes of MSUs, a 5-year Markov model was applied to analyze the cost-effectiveness for the different program setups.

RESULTS

Compared with standard stroke care, MSUs achieved an additional 0.06 quality-adjusted life years (QALYs) over a 5-year time horizon. Assuming a catchment zone of 750,000 inhabitants and 8 h/7 day operation resulted in an incremental cost-effectiveness ratio (ICER) of €37,182 per QALY from a societal perspective and €45,104 per QALY from a healthcare perspective. Lower ICERs were possible when coverage was expanded to 16 h service on 7 days per week and larger populations. Sensitivity analyses revealed that missing ischemic strokes significantly deteriorated economic performance of MSU.

CONCLUSIONS

Major determinants of cost-effectiveness should be addressed when setting up novel MSU programs. Catchment zones of more than 500,000-700,000 inhabitants and operating times of at least 12-16 h per day, 7 days per week could enable the most cost-effective MSU services in the German healthcare system.

Emergency call utilization over a 10-years period: an observational study in Region Zealand, Denmark, 2013-2022

BACKGROUND

Improving prehospital emergency care requires a comprehensive understanding of the efficiency of emergency medical services and demand fluctuations. The medical emergency call is the primary contact between citizens and the emergency medical dispatch center, serving as the gateway to accessing emergency assistance. This study aimed to characterize the emergency call population and analyze the development of emergency call utilization in Region Zealand in Denmark during a 10-years period.

METHODS

This was an observational register-based study of administrative data from the emergency medical dispatch center in Region Zealand. Data was collected from 1 January 2013 to 31 December 2022. All unique emergency calls from residents to the emergency number "1-1-2" were included. Descriptive analyses were used to characterize the study population. Poisson regression models were used to calculate ratio estimates for the association between years and hospital catchment areas, using the incidence rate of emergency calls as outcome measure.

RESULTS

A total of 641,457 emergency calls were included. A significant increase in the total number of emergency calls was found, with an increase from 58,454 annual calls to 80,819 calls over the study period. The incidence rate per 1000 residents per year increased from 71.1 to 95.2, a 35% increase. The southern part of the region had significantly more emergency calls per 1000 residents per year during the study period compared to the eastern part of the region (IRR 1.70). Demographically, males comprised 52.3% of cases, and patients aged 65 and older represented 48.2% of calls. Emergency calls were "Emergency level A" in 45.5% and "Emergency level B" in 39.1%. In 22.3% of cases, the emergency call was categorized as "Unclear problem." The most frequent categories were "chest pain" (12.7%), "impaired consciousness" (9.6%), "breathing difficulties" (8.8%), "accidents" (7.9%), and "minor injuries" (7.6%).

CONCLUSIONS

The study revealed a significant increase in emergency calls, both in absolute numbers and per 1000 residents per year, indicating growing demand for emergency care, along with a surge in activity at the region's dispatch center. Regional disparities underscores the potential necessity for tailored developmental approaches over time.

Factors affecting emergency medical dispatchers decision making in stroke calls - a qualitative study

OBJECTIVES

Emergency Medical Communication Centers (EMCC) have a key role in the prehospital chain-of-stroke-survival by recognizing stroke patients and reducing prehospital delay. However, studies on EMCC stroke recognition report both substantial undertriage and overtriage. Since mis-triage at the EMCC challenges the whole chain-of-stroke-survival, by occupying limited resources for non-stroke patients or failing to recognize the true stroke patients, there is a need to achieve a more comprehensive understanding of the dispatchers' routines and experiences. The aim of this study was to explore factors affecting EMCC dispatcher's decision-making in stroke calls.

MATERIALS AND METHODS

A qualitative exploratory study, based on individual semi-structured interviews of 15 medical dispatchers from EMCC Oslo, Norway. Interviews were conducted during August and October 2022 and analyzed using the principles of thematic analysis.

RESULTS

We identified four themes: [1] Pronounced stroke symptoms are easy to identify [2]. Non-specific neurological symptoms raise suspicion of acute stroke but are difficult to differentiate from other medical conditions [3]. Consistent use of the Criteria Based Dispatch (CBD) protocol may increase EMCC overtriage [4]. Contextual conditions at EMCC can affect dispatchers' decision-making process and the ability for experiential learning.

CONCLUSIONS

Medical dispatchers at the EMCC perceive vague and non-specific stroke symptoms, such as dizziness, confusion or altered behaviour, challenging to differentiate from symptoms of other less time-critical medical conditions. They also perceive the current CBD protocol in use as less supportive in assessing such symptoms. High workload and strict EMCC response time interval requirements hinder the gathering of essential patient information and the ability to seek guidance in cases of doubt, potentially exacerbating both EMCC undertriage and overtriage. The absence of feedback loops and other strategies for experiential learning in the EMCC hampers the medical dispatcher's ability to evaluate their own assessments and improve dispatch accuracy.

Design of an emergency medical information system for mass gatherings

Background

The frequency of mass gatherings is increasing. Such events often involve many people and carry the risk of mass casualty incidents, which require substantial medical resources from various healthcare institutions. The current medical system, while meeting daily needs, struggles to address the demand for a high volume of emergency resources and real-time data exchange.

Objective

The aim of this study was to develop an emergency medical information system for mass gatherings.

Methods

We developed an emergency medical information system for mass gatherings. Based on a unified prehospital and intrahospital emergency data exchange protocol, we can directly standardize medical information data and provide data support for the evacuation decision support algorithms of multiple institutions. Wearable devices, vehicle-mounted devices, video calling systems and surveillance systems are connected to capture real-time scenes.

Results

We constructed the system via mobile applications and online platforms and deployed it in 3 hospitals, 5 ambulances and 17 on-site medical locations. We constructed a set of electronic medical records covering the whole first aid process according to the basic principles of first aid. The simulation results show that the proposed algorithm is suitable for mass gatherings. The overall survival rate of patients can be improved by 5 %, and the average evacuation efficiency of patients can be improved by 50 %. Furthermore, in a real-world environment, this method can ensure patient survival and achieve good convergence.

Conclusions

Our system is capable of providing robust medical information support for emergency medical services during large-scale assembly events, ensuring a visualized full-process emergency response and decision-making for the diversion and subsequent transport of a large patient population.

Improving Triage Accuracy in Prehospital Emergency Telemedicine: Scoping Review of Machine Learning-Enhanced Approaches

BACKGROUND

Prehospital telemedicine triage systems combined with machine learning (ML) methods have the potential to improve triage accuracy and safely redirect low-acuity patients from attending the emergency department. However, research in prehospital settings is limited but needed; emergency department overcrowding and adverse patient outcomes are increasingly common.

OBJECTIVE

In this scoping review, we sought to characterize the existing methods for ML-enhanced telemedicine emergency triage. In order to support future research, we aimed to delineate what data sources, predictors, labels, ML models, and performance metrics were used, and in which telemedicine triage systems these methods were applied.

METHODS

A scoping review was conducted, querying multiple databases (MEDLINE, PubMed, Scopus, and IEEE Xplore) through February 24, 2023, to identify potential ML-enhanced methods, and for those eligible, relevant study characteristics were extracted, including prehospital triage setting, types of predictors, ground truth labeling method, ML models used, and performance metrics. Inclusion criteria were restricted to the triage of emergency telemedicine services using ML methods on an undifferentiated (disease nonspecific) population. Only primary research studies in English were considered. Furthermore, only those studies using data collected remotely (as opposed to derived from physical assessments) were included. In order to limit bias, we exclusively included articles identified through our predefined search criteria and had 3 researchers (DR, JS, and KS) independently screen the resulting studies. We conducted a narrative synthesis of findings to establish a knowledge base in this domain and identify potential gaps to be addressed in forthcoming ML-enhanced methods.

RESULTS

A total of 165 unique records were screened for eligibility and 15 were included in the review. Most studies applied ML methods during emergency medical dispatch (7/15, 47%) or used chatbot applications (5/15, 33%). Patient demographics and health status variables were the most common predictors, with a notable absence of social variables. Frequently used ML models included support vector machines and tree-based methods. ML-enhanced models typically outperformed conventional triage algorithms, and we found a wide range of methods used to establish ground truth labels.

CONCLUSIONS

This scoping review observed heterogeneity in dataset size, predictors, clinical setting (triage process), and reported performance metrics. Standard structured predictors, including age, sex, and comorbidities, across articles suggest the importance of these inputs; however, there was a notable absence of other potentially useful data, including medications, social variables, and health system exposure. Ground truth labeling practices should be reported in a standard fashion as the true model performance hinges on these labels. This review calls for future work to form a standardized framework, thereby supporting consistent reporting and performance comparisons across ML-enhanced prehospital triage systems.

A retrospective analysis of the need for on-site emergency physician presence and mission characteristics of a rural ground-based emergency medical service

BACKGROUND

This study aimed to address the challenges faced by rural emergency medical services in Europe, due to an increasing number of missions and limited human resources. The primary objective was to determine the necessity of having an on-site emergency physician (EP), while the secondary objectives included analyzing the characteristics of rural EP missions.

METHODS

A retrospective study was conducted, examining rural EP missions carried out between January 1st, 2017, and December 2nd, 2021 in Burgenland, Austria. The need for physical presence of an EP was classified based on the National Advisory Committee for Aeronautics (NACA) score into three categories; category A: no need for an EP (NACA 1-3); category B: need for an EP (NACA 1-3 along with additional medical interventions beyond the capabilities of emergency medical technicians); and category C: definite need for an EP (NACA 4-7). Descriptive statistics were used for analysis.

RESULTS

Out of 16,971 recorded missions, 15,591 were included in the study. Approximately 32.3% of missions fell into category A, indicating that an EP's physical presence was unnecessary. The diagnoses made by telecommunicators matched those of the EPs in only 52.8% of cases.

CONCLUSION

The study suggests that about a third of EP missions carried out in rural areas might not have a solid medical rationale. This underscores the importance of developing an alternative care approach for these missions. Failing to address this could put additional pressure on already stretched EMS systems, risking their collapse.

Population-Level Surveillance of Domestic Assaults in the Home Using the National Emergency Medical Services Information System (NEMSIS)

Violence in the home, including partner violence, child abuse, and elder abuse, is pervasive in the United States. An informatics approach allowing automated analysis of administrative data to identify domestic assaults and release timely and localized data would assist preventionists to identify geographic and demographic populations of need and design tailored interventions. This study examines the use of an established national dataset, the NEMSIS 2019, as a potential annual automated data source for domestic assault surveillance. An algorithm was used to identify individuals who utilized emergency medical services (EMS) for a physical assault in a private residence (N = 176,931). Descriptive analyses were conducted to define the identified population and disposition of patients. A logistic regression was performed to predict which characteristics were associated with consistent domestic assault identification by the on-scene EMS clinician and dispatcher. The sample was majority female (52.2%), White (44.7%), urban (85.5%), and 21-29 years old (24.4%). A disproportionate number of those found dead on scene were men (74.5%), and female patients more often refused treatment (57.8%) or were treated and then released against medical advice (58.4%). Domestic assaults against children and seniors had higher odds of being consistently identified by both the dispatcher and EMS clinician than those 21-49, and women had lower odds of consistent identification than men. While a more specific field to identify the type of domestic assault (e.g., intimate partner) would help inform specialized intervention planning, these data indicate an opportunity to systematically track domestic assaults in communities and describe population-specific needs.

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.

Video livestreaming from medical emergency callers' smartphones to emergency medical dispatch centres: a scoping review of current uses, opportunities, and challenges

BACKGROUND

Timely dispatch of appropriate emergency medical services (EMS) resources to the scene of medical incidents, and/or provision of treatment at the scene by bystanders and medical emergency lay callers (referred to as 'callers' in this review) can improve patient outcomes. Currently, in dispatch systems worldwide, prioritisation of dispatch relies mostly on verbal telephone information from callers, but advances in mobile phone technology provide means for sharing video footage. This scoping review aimed to map and identify current uses, opportunities, and challenges for using video livestreaming from callers' smartphones to emergency medical dispatch centres.

METHODS

A scoping review of relevant published literature between 2007 and 2023 in the English language, searched within MEDLINE; CINAHL and PsycINFO, was descriptively synthesised, adhering to the PRISMA extension for scoping reviews.

RESULTS

Twenty-four articles remained from the initial search of 1,565 articles. Most studies were simulation-based and focused on emergency medical dispatchers' (referred to as 'dispatcher/s' in this review) assisted video cardiopulmonary resuscitation (CPR), predominantly concerned with measuring how video impacts CPR performance. Nine studies were based on real-life practice. Few studies specifically explored experiences of dispatchers or callers. Only three articles explored the impact that using video had on the dispatch of resources. Opportunities offered by video livestreaming included it being: perceived to be useful; easy to use; reassuring for both dispatchers and callers; and informing dispatcher decision-making. Challenges included the potential emotional impact for dispatchers and callers. There were also concerns about potential misuse of video, although there was no evidence that this was occurring. Evidence suggests a need for appropriate training of dispatchers and video-specific dispatch protocols.

CONCLUSION

Research is sparse in the context of video livestreaming. Few studies have focussed on the use of video livestreaming outside CPR provision, such as for trauma incidents, which are by their nature time-critical where visual information may offer significant benefit. Further investigation into acceptability and experience of the use of video livestreaming is warranted, to understand the potential psychological impact on dispatchers and callers.

Pediatric trauma patients in Swedish ambulance services -a retrospective observational study of assessments, interventions, and clinical outcomes

BACKGROUND

Pediatric trauma patients constitute a significant portion of the trauma population treated by Swedish Emergency Medical Services (EMS), and trauma remains a notable cause of death among Swedish children. Previous research has identified potential challenges in prehospital assessments and interventions for pediatric patients. In Sweden, there is limited information available regarding pediatric trauma patients in the EMS. The aim of this study was to investigate the prevalence of pediatric trauma patients within the Swedish EMS and describe the prehospital assessments, interventions, and clinical outcomes.

METHODS

This retrospective observational study was conducted in a region of Southwestern Sweden. A random sample from ambulance and hospital records from the year 2019 was selected. Inclusion criteria were children aged 0-16 years who were involved in trauma and assessed by EMS clinicians.

RESULTS

A total of 440 children were included in the study, representing 8.4% of the overall trauma cases. The median age was 9 years (IQR 3-12), and 60.5% were male. The leading causes of injury were low (34.8%) and high energy falls (21%), followed by traffic accidents. The children were assessed as severely injured in 4.5% of cases. A quarter of the children remained at the scene after assessment. Complete vital signs were assessed in 29.3% of children, and 81.8% of children were assessed according to the ABCDE structure. The most common intervention performed by prehospital professionals was the administration of medication. The mortality rate was 0.2%.

CONCLUSIONS

Pediatric trauma cases accounted for 8.4% of the overall trauma population with a variations in injury mechanisms and types. Vital sign assessments were incomplete for a significant proportion of children. The adherence to the ABCDE structure, however, was higher. The children remained at the scene after assessment requires further investigation for patient safety.

Emergency Medical Services dispatcher recognition of stroke: A systematic review

PURPOSE

Stroke 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.

METHODS

The 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.

FINDINGS

Of 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.

DISCUSSION

Stroke 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.

CONCLUSION

While 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.

Accuracy of telephone triage for predicting adverse outcomes in suspected COVID-19: an observational cohort study

OBJECTIVE

To assess accuracy of telephone triage in identifying need for emergency care among those with suspected COVID-19 infection and identify factors which affect triage accuracy.

DESIGN

Observational cohort study.

SETTING

Community telephone triage provided in the UK by Yorkshire Ambulance Service NHS Trust (YAS).

PARTICIPANTS

40 261 adults who contacted National Health Service (NHS) 111 telephone triage services provided by YAS between 18 March 2020 and 29 June 2020 with symptoms indicating COVID-19 infection were linked to Office for National Statistics death registrations and healthcare data collected by NHS Digital.

OUTCOME

Accuracy of triage disposition was assessed in terms of death or need for organ support up to 30 days from first contact.

RESULTS

Callers had a 3% (1200/40 261) risk of serious adverse outcomes (death or organ support). Telephone triage recommended self-care or non-urgent assessment for 60% (24 335/40 261), with a 1.3% (310/24 335) risk of adverse outcomes. Telephone triage had 74.2% sensitivity (95% CI: 71.6 to 76.6%) and 61.5% specificity (95% CI: 61% to 62%) for the primary outcome. Multivariable analysis suggested respiratory comorbidities may be overappreciated, and diabetes underappreciated as predictors of deterioration. Repeat contact with triage service appears to be an important under-recognised predictor of deterioration with 2 contacts (OR 1.77, 95% CI: 1.14 to 2.75) and 3 or more contacts (OR 4.02, 95% CI: 1.68 to 9.65) associated with false negative triage.

CONCLUSION

Patients advised to self-care or receive non-urgent clinical assessment had a small but non-negligible risk of serious clinical deterioration. Repeat contact with telephone services needs recognition as an important predictor of subsequent adverse outcomes.

Dispatch Categories as Indicators of Out-of-Hospital Time Critical Interventions and Associated Emergency Department Outcomes

OBJECTIVES

Emergency medical services (EMS) systems increasingly grapple with rising call volumes and workforce shortages, forcing systems to decide which responses may be delayed. Limited research has linked dispatch codes, on-scene findings, and emergency department (ED) outcomes. This study evaluated the association between dispatch categorizations and time-critical EMS responses defined by prehospital interventions and ED outcomes. Secondarily, we proposed a framework for identifying dispatch categorizations that are safe or unsafe to hold in queue.

METHODS

This retrospective, multi-center analysis encompassed all 9-1-1 responses from 8 accredited EMS systems between 1/1/2021 and 06/30/2023, utilizing the Medical Priority Dispatch System (MPDS). Independent variables included MPDS Protocol numbers and Determinant levels. EMS treatments and ED diagnoses/dispositions were categorized as time-critical using a multi-round consensus survey. The primary outcome was the proportion of EMS responses categorized as time-critical. A non-parametric test for trend was used to assess the proportion of time-critical responses Determinant levels. Based on group consensus, Protocol/Determinant level combinations with at least 120 responses (∼1 per week) were further categorized as safe to hold in queue (<1% time-critical intervention by EMS and <5% time-critical ED outcome) or unsafe to hold in queue (>10% time-critical intervention by EMS or >10% time-critical ED outcome).

RESULTS

Of 1,715,612 EMS incidents, 6% (109,250) involved a time-critical EMS intervention. Among EMS transports with linked outcome data (543,883), 12% had time-critical ED outcomes. The proportion of time-critical EMS interventions increased with Determinant level (OMEGA: 1%, ECHO: 38%, p-trend < 0.01) as did time-critical ED outcomes (OMEGA: 3%, ECHO: 31%, p-trend < 0.01). Of 162 unique Protocols/Determinants with at least 120 uses, 30 met criteria for safe to hold in queue, accounting for 8% (142,067) of incidents. Meanwhile, 72 Protocols/Determinants met criteria for unsafe to hold, accounting for 52% (883,683) of incidents. Seven of 32 ALPHA level Protocols and 3/17 OMEGA level Protocols met the proposed criteria for unsafe to hold in queue.

CONCLUSIONS

In general, Determinant levels aligned with time-critical responses; however, a notable minority of lower acuity Determinant level Protocols met criteria for unsafe to hold. This suggests a more nuanced approach to dispatch prioritization, considering both Protocol and Determinant level factors.

Impact of delayed mobile medical team dispatch for respiratory distress calls: a propensity score matched study from a French emergency communication center

BACKGROUND

Shortness of breath is a common complaint among individuals contacting emergency communication center (EMCCs). In some prehospital system, emergency medical services include an advanced life support (ALS)-capable team. Whether such team should be dispatched during the phone call or delayed until the BLS-capable paramedic team reports from the scene is unclear. We aimed to evaluate the impact of delayed MMT dispatch until receiving the paramedic review compared to immediate dispatch at the time of the call on patient outcomes.

METHODS

A cross-sectional study conducted in Lyon, France, using data obtained from the departmental EMCC during the period from January to December 2019. We included consecutive calls related to adult patients experiencing acute respiratory distress. Patients from the two groups (immediate mobile medical team (MMT) dispatch or delayed MMT dispatch) were matched on a propensity score, and a conditional weighted logistic regression assessed the adjusted odds ratios (ORs) for each outcome (mortality on days 0, 7 and 30).

RESULTS

A total of 870 calls (median age 72 [57-84], male 466 53.6%) were sought for analysis [614 (70.6%) "immediate MMT dispatch" and 256 (29.4%) "delayed MMT" groups]. The median time before MMT dispatch was 25.1 min longer in the delayed MMT group (30.7 [26.4-36.1] vs. 5.6 [3.9-8.8] min, p < 0.001). Patients subjected to a delayed MMT intervention were older (median age 78 [66-87] vs. 69 [53-83], p < 0.001) and more frequently highly dependent (16.3% vs. 8.6%, p < 0.001). A higher proportion of patients in the delayed MMT group required bag valve mask ventilation (47.3% vs. 39.1%, p = 0.03), noninvasive ventilation (24.6% vs. 20.0%, p = 0.13), endotracheal intubation (7.0% vs. 4.1%, p = 0.07) and catecholamine infusion (3.9% vs. 1.3%, p = 0.01). After propensity score matching, mortality at day 0 was higher in the delayed MMT group (9.8% vs. 4.2%, p = 0.002). Immediate MMT dispatch at the call was associated with a lower risk of mortality on day 0 (0.60 [0.38;0.82], p < 0.001) day 7 (0.50 [0.27;0.72], p < 0.001) and day 30 (0.56 [0.35;0.78], p < 0.001) CONCLUSIONS: This study suggests that the deployment of an MMT at call in patients in acute respiratory distress may result in decreased short to medium-term mortality compared to a delayed MMT following initial first aid assessment.

Emergency medical dispatchers' experiences of using the Medical Priority Dispatch System telephone triage to identify maternity emergencies: a qualitative focus group study

OBJECTIVES

The ambulance service plays a pivotal role in the provision of care in out-of-hospital maternity emergencies. Telephone triage of this patient group is complex and must be sensitive to an emergency situation to prevent unnecessary delays in treatment. This study aimed to explore emergency medical dispatchers' (EMDs) perceptions of the structured protocol they use.

DESIGN

Voluntary participation in semistructured phenomenological focus groups. The participants were asked to discuss their experiences of using Medical Priority Dispatch System Protocol 24 (pregnancy, childbirth and miscarriage). Thematic analysis was applied to code and group topics. Discussion between the EMDs is presented for each theme and their experiences, including quotes, are presented to offer an overview of the maternity protocol and its use.

SETTING

A large urban UK ambulance service.

PARTICIPANTS

23 control room staff.

RESULTS

Perceptions of maternity emergencies, challenges with key questions, the need for sensitivity surrounding miscarriage, using prearrival instructions and postdispatch instructions to help patients and ideas for additional ProQA functionality emerged as the five overarching themes. Protocol 24 was considered to reflect many of the clinical factors EMDs associate with maternity emergencies although further factors, including some non-clinical, were suggested for inclusion. Miscarriage and termination-related calls were thought to be challenging as the language of the protocol is designed for pregnancy. However, instructions were generally considered well written and user-friendly, although some were thought to be unnecessary. EMDs were largely positive regarding the ProQA software, but felt backward navigation was difficult if a situation changed.

CONCLUSIONS

Maternity calls were considered rewarding but complex by EMDs. We suggest changes including the use of more sensitive language in response to miscarriage and termination and make recommendations for the omission and inclusion of specific instructions, as well as enhancements to key questions and functionality. Further research is needed to ensure focus group findings are generalisable to other services, particularly in other countries.

Telephone triage and dispatch of ambulances to patients with suspected and verified acute stroke - a descriptive study

OBJECTIVES

In this study we aimed to explore EMCC triage of suspected and confirmed stroke patients to gain more knowledge about the initial phase of the acute stroke response chain. Accurate dispatch at the Emergency Medical Communication Center (EMCC) is crucial for optimal resource utilization in the prehospital service, and early identification of acute stroke is known to improve patient outcome.

MATERIALS AND METHODS

We conducted a descriptive retrospective study based on data from the Emergency Department and EMCC records at a comprehensive stroke center in Oslo, Norway, during a six-month period (2019-2020). Patients dispatched with EMCC stroke criteria and/or discharged with a stroke diagnosis were included. We identified EMCC true positive, false positive and false negative stroke patients and estimated EMCC stroke sensitivity and positive predictive value (PPV). Furthermore, we analyzed prehospital time intervals and identified patient destinations to gain knowledge on ambulance services assessments.

RESULTS

We included 1298 patients. EMCC stroke sensitivity was 77% (95% CI: 72 - 82%), and PPV was 16% (95% CI: 14 - 18%). EMCC false negative stroke patients experienced an increased median prehospital delay of 11 min (p < 0.001). Upon arrival at the scene, 68% of the EMCC false negative patients were identified as suspected stroke cases by the ambulance services. Similarly, 68% of the false positive stroke patients were either referred to a GP, out-of-hours GP acute clinic, local hospitals or left at the scene by the ambulance services, indicating that no obvious stroke symptoms were identified by ambulance personnel upon arrival at the scene.

CONCLUSIONS

This study reveals a high EMCC stroke sensitivity and an extensive number of false positive stroke dispatches. By comparing the assessments made by both the EMCC and the ambulance service, we have identified specific patient groups that should be the focus for future research efforts aimed at improving the sensitivity and specificity of stroke recognition in the EMCC.

Establishing an MSU service in a medium-sized German urban area-clinical and economic considerations

Background and purpose

Mobile stroke units (MSU) have been demonstrated to improve prehospital stroke care in metropolitan and rural regions. Due to geographical, social and structural idiosyncrasies of the German city of Mannheim, concepts of established MSU services are not directly applicable to the Mannheim initiative. The aim of the present analysis was to identify major determinants that need to be considered when initially setting up a local MSU service.

Methods

Local stroke statistics from 2015 to 2021 were analyzed and circadian distribution of strokes and local incidence rates were calculated. MSU patient numbers and total program costs were estimated for varying operating modes, daytime coverage models, staffing configurations which included several resource sharing models with the hospital. Additional case-number simulations for expanded catchment areas were performed.

Results

Median time of symptom onset of ischemic stroke patients was 1:00 p.m. 54.3% of all stroke patients were admitted during a 10-h time window on weekdays. Assuming that MSU is able to reach 53% of stroke patients, the average expected number of ischemic stroke patients admitted to MSU would be 0.64 in a 10-h shift each day, which could potentially be increased by expanding the MSU catchment area. Total estimated MSU costs amounted to € 815,087 per annum. Teleneurological assessment reduced overall costs by 11.7%.

Conclusion

This analysis provides a framework of determinants and considerations to be addressed during the design process of a novel MSU program in order to balance stroke care improvements with the sustainable use of scarce resources.

A retrospective study on machine learning-assisted stroke recognition for medical helpline calls

Advanced stroke treatment is time-dependent and, therefore, relies on recognition by call-takers at prehospital telehealth services to ensure fast hospitalisation. This study aims to develop and assess the potential of machine learning in improving prehospital stroke recognition during medical helpline calls. We used calls from 1 January 2015 to 31 December 2020 in Copenhagen to develop a machine learning-based classification pipeline. Calls from 2021 are used for testing. Calls are first transcribed using an automatic speech recognition model and then categorised as stroke or non-stroke using a text classification model. Call-takers achieve a sensitivity of 52.7% (95% confidence interval 49.2-56.4%) with a positive predictive value (PPV) of 17.1% (15.5-18.6%). The machine learning framework performs significantly better (p < 0.0001) with a sensitivity of 63.0% (62.0-64.1%) and a PPV of 24.9% (24.3-25.5%). Thus, a machine learning framework for recognising stroke in prehospital medical helpline calls may become a supportive tool for call-takers, aiding in early and accurate stroke recognition.

Development of indicators for avoidable emergency medical service calls by mapping paramedic clinical impression codes to ambulatory care sensitive conditions and mental health conditions in the UK and Canada

OBJECTIVE

Paramedic assessment data have not been used for research on avoidable calls. Paramedic impression codes are designated by paramedics on responding to a 911/999 medical emergency after an assessment of the presenting condition. Ambulatory care sensitive conditions (ACSCs) are non-acute health conditions not needing hospital admission when properly managed. This study aimed to map the paramedic impression codes to ACSCs and mental health conditions for use in future research on avoidable 911/999 calls.

DESIGN

Mapping paramedic impression codes to existing definitions of ACSCs and mental health conditions.

SETTING

East Midlands Region, UK and Southern Ontario, Canada.

PARTICIPANTS

Expert panel from the UK-Canada Emergency Calls Data analysis and GEospatial mapping (EDGE) Consortium.

RESULTS

Mapping was iterative first identifying the common ACSCs shared between the two countries then identifying the respective clinical impression codes for each country that mapped to those shared ACSCs as well as to mental health conditions. Experts from the UK-Canada EDGE Consortium contributed to both phases and were able to independently match the codes and then compare results. Clinical impression codes for paramedics in the UK were more extensive than those in Ontario. The mapping revealed some interesting inconsistencies between paramedic impression codes but also demonstrated that it was possible.

CONCLUSION

This is an important first step in determining the number of ASCSs and mental health conditions that paramedics attend to, and in examining the clinical pathways of these individuals across the health system. This work lays the foundation for international comparative health services research on integrated pathways in primary care and emergency medical services.

The MeSH heading "Call Center" is due for an update: why we recommend the more precise heading "Emergency Medical Communication Center"

Call centers can be found in various industries. However as a Medical Subject Heading (MeSH) the term "Call centers" does not reflect the critical purpose of handling emergency calls. We recommend "emergency medical communication center(s)", as this provides clarity and precision regarding the primary function and purpose of the center.

Dispatcher Stroke/TIA Recognition in Emergency Medical Call Center and Out-of-Hours Service Calls in Copenhagen, Denmark

Background and Objectives

Recognition of stroke/TIA symptoms by emergency medical services (EMS) is instrumental in providing timely recanalization treatments. We assessed the recognition of stroke/TIA by EMS via the emergency medical call center (EMCC) dispatchers and out-of-hours health service (OOHS) dispatchers.

Methods

In a registry study, based on 2015-2020 data from the Copenhagen EMS, we calculated sensitivity, positive predictive value (PPV), specificity, and negative predictive value (NPV) of dispatcher suspicion of stroke or transient ischemic attack (TIA) and compared against discharge diagnosis.

Results

We included 462,029 contacts to EMCC and 2,573,865 contacts to OOHS. In total, 19,798 contacts had a stroke or TIA diagnosis at hospital discharge. Sensitivity was 0.64 for EMCC dispatchers and 0.25 for OOHS. PPV was 0.28 for EMCC and 0.22 for OOHS; specificity was 0.96 for EMCC and >0.99 for OOHS, and NPV was 0.99 for EMCC and >0.99 for OOHS. Sensitivity improved over the period of the study from 0.62 to 0.68 for EMCC and from 0.20 to 0.25 for OOHS. PPV did not change over the period for EMCC and decreased from 0.26 to 0.19 for OOHS. Both EMCC and OOHS more frequently overlooked stroke in women, in patients calling more than 3 hours after symptom onset, and for more severe strokes. For OHHS, advanced age correlated with lower recognition.

Discussion

As the first study reporting on OOHS setting dispatcher stroke/TIA recognition, we find a need for the improvement of stroke/TIA recognition both in EMCC and in OOHS. Solutions may include specific training of dispatchers, public awareness campaigns, and new technological solutions.

AI-based approach for transcribing and classifying unstructured emergency call data: A methodological proposal

Emergency care-sensitive conditions (ECSCs) require rapid identification and treatment and are responsible for over half of all deaths worldwide. Prehospital emergency care (PEC) can provide rapid treatment and access to definitive care for many ECSCs and can reduce mortality in several different settings. The objective of this study is to propose a method for using artificial intelligence (AI) and machine learning (ML) to transcribe audio, extract, and classify unstructured emergency call data in the Serviço de Atendimento Móvel de Urgência (SAMU) system in southern Brazil. The study used all "1-9-2" calls received in 2019 by the SAMU Novo Norte Emergency Regulation Center (ERC) call center in Maringá, in the Brazilian state of Paraná. The calls were processed through a pipeline using machine learning algorithms, including Automatic Speech Recognition (ASR) models for transcription of audio calls in Portuguese, and a Natural Language Understanding (NLU) classification model. The pipeline was trained and validated using a dataset of labeled calls, which were manually classified by medical students using LabelStudio. The results showed that the AI model was able to accurately transcribe the audio with a Word Error Rate of 42.12% using Wav2Vec 2.0 for ASR transcription of audio calls in Portuguese. Additionally, the NLU classification model had an accuracy of 73.9% in classifying the calls into different categories in a validation subset. The study found that using AI to categorize emergency calls in low- and middle-income countries is largely unexplored, and the applicability of conventional open-source ML models trained on English language datasets is unclear for non-English speaking countries. The study concludes that AI can be used to transcribe audio and extract and classify unstructured emergency call data in an emergency system in southern Brazil as an initial step towards developing a decision-making support tool.

Evaluation of Telephone Cardiopulmonary Resuscitation Performance in Current Practice in Saudi Arabia

Objectives

Out-of-hospital cardiac arrest (OHCA) is a global health problem with a low survival rate. Telephone cardiopulmonary resuscitation (T-CPR) guidance by emergency medical services (EMS) dispatchers can improve CPR performance and, consequently, survival rates. Accordingly, the American Heart Association (AHA) has released performance standards for T-CPR in current practice to improve its quality. However, no study has examined T-CPR performance in Saudi Arabia. Therefore, this study aims to evaluate T-CPR performance in the Saudi Arabian EMS system.

Methods

A retrospective observation of OHCA calls in current practice was conducted in Riyadh, Saudi Arabia. OHCA calls were reviewed to identify those that met the selection criteria. Variables collected included return of spontaneous circulation (ROSC), OHCA recognition rate, time from EMS call receipt to location acquisition, to OHCA recognition and to commencement of CPR.

Results

A total of 308 OHCA cases were reviewed, and 100 calls were included. ROSC was identified in 10% of the included calls. OHCA was correctly recognized in 62% of the calls. The time to OHCA identification and CPR performance from EMS call receipt were found to be 303 s and 367 s, respectively.

Conclusion

T-CPR performance in Saudi Arabia is below AHA standards. However, this is similar to what has been reported in the literature. Avoiding any unnecessary call transfer during OHCA calls and prompt identification of callers' locations could improve T-CPR performance.

Understanding patient non-transport decision theories in the pre-hospital setting: a narrative review

BACKGROUND

In pre-hospital emergency care, decisions regarding patient non-conveyance emerged as significant determinants of healthcare outcomes and resource utilization. These complex decisions became integral to the progress of emergency medical services, thus warranting an evolving exploration within the medical discourse.

OBJECTIVES AND METHODS

This narrative review aimed to synthesize and critically evaluate various theoretical stances on patient non-conveyance in the pre-hospital emergency. The focus on studies published between January 2012 and August 2022 was intentional to capture contemporary practices and insights. PubMed and Google Scholar served as the primary databases for the investigation, while the AL-Rayyan® software facilitated a thorough screening process.

RESULTS AND DISCUSSION

Twenty-nine studies-encompassing articles, books, and theses-were discovered through our search, each presenting unique perspectives on patient non-transport, thus highlighting its criticality as a healthcare concern. Predominant factors influencing non-transport decisions were classified into patient-initiated refusals (PIR), clinician-initiated decisions (CID), and dispatcher-initiated decisions (DID).

CONCLUSIONS

The issue of patient non-conveyance to hospitals continues to pose a crucial challenge to the seamless operation of emergency healthcare systems, warranting increased attention from various healthcare entities. To comprehend and pinpoint potential areas of improvement, a comprehensive analysis of pre-hospital non-transport events is imperative. A well-informed, strategic approach could prevent resource waste while ensuring patients receive the required and definitive care.

KEY MESSAGES

Why is this topic important? Some studies have suggested that non-transport to hospitals following emergency calls is safe. However, it is a concerning issue for health systems. It is also considered a key performance metric for health systems. What does this review attempt to show? This review aimed to map the various factors discussed in the literature regarding the decisions not to transport patients following emergency calls in a pre-hospital setting. What are the key findings? The existing theories regarding non-transport to hospitals after the provision of emergency care in the pre-hospital setting were identified. Non-transport due to non-clinical decisions jeopardizes emergency care outcomes for paediatric and elderly patients in particular. Hence, further research is required to identify and control the factors governing these decisions. How is patient care impacted? The decisions regarding patient transport following emergency calls in a pre-hospital setting are crucial for patient outcomes. They could impact the pre-hospital emergency care outcomes as well as patient safety. They can also affect the emergency services resources' ability to respond to other critical emergencies.

Association between initial presenting level of consciousness and patient acuity - A potential application for secondary triage in emergency ambulance calls

INTRODUCTION

Conscious state assessment is important for the triage of emergency patients. In this study, we measured the association between ambulance patients' conscious state and high versus lower acuity, with a view to informing telephone triage assessment of conscious state.

METHODS

Data were analysed from one year of emergency ambulance incidents in Perth, Western Australia. Patient conscious state at the time of paramedic arrival was compared to acuity (based on paramedic assessment and management). We determined the proportion of high-acuity patients across six levels of consciousness (Alert, Confused, Drowsy, Voice Response, Pain Response, Unresponsive) overall, and within individual protocols of the Medical Priority Dispatch System (MPDS).

RESULTS

The proportion of high acuity patients increased with each step across the consciousness scale. Applying conscious state as a binary predictor of acuity, the largest increases occurred moving the threshold from Alert to Confused (22.0-48.6% high acuity) and Drowsy to Voice Response (61.9-89.5% high acuity). The Area Under the Curve (AUC) of the Receiver Operating Characteristic was 0.65. Within individual protocols, the highest AUC was in Cardiac Arrest (0.89), Overdose/Poisoning (0.81), Unknown Problem (0.76), Diabetic Problem, (0.74) and Convulsions/Fitting (0.73); and lowest in Heart problems (0.55), Abdominal Pain (0.55), Breathing Problems (0.55), Back Pain (0.53), and Chest Pain (0.52).

CONCLUSION

Based on these proportions of high acuity patients, it is reasonable to consider patients with any altered conscious state a high priority. The value of conscious state assessment for predicting acuity varies markedly between MPDS protocols. These findings could help inform secondary triage of ambulance patients during the emergency call.

Prehospital Emergency Care in Low- and Middle-Income Countries: A Systematic Review

BACKGROUND

An under-developed and fragmented prehospital Emergency Medical Services (EMS) system is a major obstacle to the timely care of emergency patients. Insufficient emphasis on prehospital emergency systems in low- and middle-income countries (LMICs) currently causes a substantial number of avoidable deaths from time-sensitive illnesses, highlighting a critical need for improved prehospital emergency care systems. Therefore, this systematic review aimed to assess the prehospital emergency care services across LMICs.

METHODS

This systematic review used four electronic databases, namely: PubMed/MEDLINE, CINAHL, EMBASE, and SCOPUS, to search for published reports on prehospital emergency medical care in LMICs. Only peer-reviewed studies published in English language from January 1, 2010 through November 1, 2022 were included in the review. The Newcastle-Ottawa Scale (NOS) and Critical Appraisal Skills Programme (CASP) checklist were used to assess the methodological quality of the included studies. Further, the protocol of this systematic review has been registered on the International Prospective Register of Systematic Reviews (PROSPERO) database (Ref: CRD42022371936) and has been conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.

RESULTS

Of the 4,909 identified studies, a total of 87 studies met the inclusion criteria and were therefore included in the review. Prehospital emergency care structure, transport care, prehospital times, health outcomes, quality of information exchange, and patient satisfaction were the most reported outcomes in the considered studies.

CONCLUSIONS

The prehospital care system in LMICs is fragmented and uncoordinated, lacking trained medical personnel and first responders, inadequate basic materials, and substandard infrastructure.

Epidemiological Determinants of Patient Non-Conveyance to the Hospital in an Emergency Medical Service Environment

BACKGROUND

The increasing prevalence of comorbidities worldwide has spurred the need for time-effective pre-hospital emergency medical services (EMS). Some pre-hospital emergency calls requesting EMS result in patient non-conveyance. Decisions for non-conveyance are sometimes driven by the patient or the clinician, which may jeopardize the patients' healthcare outcomes. This study aimed to explore the distribution and determinants of patient non-conveyance to hospitals in a Middle Eastern national Ambulance Service that promotes the transportation of all emergency call patients and does not adopt clinician-based non-conveyance decision.

METHODS

Using R Language, descriptive, bivariate, and binary logistic regression analyses were conducted for 334,392 multi-national patient non-conveyance emergency calls from June 2018 to July 2022, from a total of 1,030,228 calls to which a response unit was dispatched.

RESULTS

After data pre-processing, 237,862 cases of patient non-conveyance to hospital were retained, with a monthly average of 41.96% (n = 8799) of the emergency service demands and a standard deviation of 5.49% (n = 2040.63). They predominantly involved South Asians (29.36%, n = 69,849); 64.50% (n = 153,427) were of the age category from 14 to 44 years; 61.22% (n = 145,610) were male; 74.59% (n = 177,424) from the urban setting; and 71.28% (n = 169,552) had received on-scene treatment. Binary logistic regression with full variables and backward methods identified the final models of the determinants of patient non-conveyance decisions with an Akaike information criterion prediction estimator, respectively, of (250,200) and (250,169), indicating no significant difference between both models (Chi-square test; p-value = 0.63).

CONCLUSIONS

Despite exercising a cautious protocol by encouraging patient transportation to hospital, patient non-conveyance seems to be a problem in the healthcare system that strains the pre-hospital medical response teams' resources. Policies and regulations should be adopted to encourage individuals to access other primary care centers when required rather than draining emergency services for non-emergency situations.

Nine golden codes: improving the accuracy of Helicopter Emergency Medical Services (HEMS) dispatch-a retrospective, multi-organisational study in the East of England

BACKGROUND

Helicopter Emergency Medical Services (HEMS) are a limited and expensive resource, and should be intelligently tasked. HEMS dispatch was identified as a key research priority in 2011, with a call to identify a 'general set of criteria with the highest discriminating potential'. However, there have been no published data analyses in the past decade that specifically address this priority, and this priority has been reaffirmed in 2023. The objective of this study was to define the dispatch criteria available at the time of the initial emergency call with the greatest HEMS utility using a large, regional, multi-organizational dataset in the UK.

METHODS

This retrospective observational study utilized dispatch data from a regional emergency medical service (EMS) and three HEMS organisations in the East of England, 2016-2019. In a logistic regression model, Advanced Medical Priority Dispatch System (AMPDS) codes with ≥ 50 HEMS dispatches in the study period were compared with the remainder to identify codes with high-levels of HEMS patient contact and HEMS-level intervention/drug/diagnostic (HLIDD). The primary outcome was to identify AMPDS codes with a > 10% HEMS dispatch rate of all EMS taskings that would result in 10-20 high-utility HEMS dispatches per 24-h period in the East of England. Data were analysed in R, and are reported as number (percentage); significance was p < 0.05.

RESULTS

There were n = 25,491 HEMS dispatches (6400 per year), of which n = 23,030 (90.3%) had an associated AMPDS code. n = 13,778 (59.8%) of HEMS dispatches resulted in patient contact, and n = 8437 (36.6%) had an HLIDD. 43 AMPDS codes had significantly greater rates of patient contact and/or HLIDD compared to the reference group. In an exploratory analysis, a cut-off of ≥ 70% patient contact rate and/or ≥ 70% HLIDD (with a > 10% HEMS dispatch of all EMS taskings) resulted in 17 taskings per 24-h period. This definition derived nine AMPDS codes with high HEMS utility.

CONCLUSION

We have identified nine 'golden' AMPDS codes, available at the time of initial emergency call, that are associated with high-levels of whole-system and HEMS utility in the East of England. We propose that UK EMS should consider immediate HEMS dispatch to these codes.

Increasing emergency number utilisation is not driven by low-acuity calls: an observational study of 1.5 million emergency calls (2018-2021) from Berlin

BACKGROUND

The Emergency Medical Service (EMS) in Germany is increasingly challenged by strongly rising demand. Speculations about a greater utilisation for minor cases have led to intensive media coverage, but empirical evidence is lacking. We investigated the development of low-acuity calls from 2018 to 2021 in the federal state of Berlin and its correlations with sociodemographic characteristics.

METHODS

We analysed over 1.5 million call documentations including medical dispatch codes, age, location and time using descriptive and inferential statistics and multivariate binary logistic regression. We defined a code list to classify low-acuity calls and merged the dataset with sociodemographic indicators and data on population density.

RESULTS

The number of emergency calls (phone number 112 in Germany) increased by 9.1% from 2018 to 2021; however, the proportion of low-acuity calls did not increase. The regression model shows higher odds of low-acuity for young to medium age groups (especially for age 0-9, OR 1.50 [95% CI 1.45-1.55]; age 10-19, OR 1.77 [95% CI 1.71-1.83]; age 20-29, OR 1.64 [95% CI 1.59-1.68] and age 30-39, OR 1.40 [95% CI 1.37-1.44]; p < 0.001, reference group 80-89) and for females (OR 1.12 [95% CI 1.1-1.13], p < 0.001). Odds were slightly higher for calls from a neighbourhood with lower social status (OR 1.01 per index unit increase [95% CI 1.0-1.01], p < 0.05) and at the weekend (OR 1.02 [95% CI 1.0-1.04, p < 0.05]). No significant association of the call volume with population density was detected.

CONCLUSIONS

This analysis provides valuable new insights into pre-hospital emergency care. Low-acuity calls were not the primary driver of increased EMS utilisation in Berlin. Younger age is the strongest predictor for low-acuity calls in the model. The association with female gender is significant, while socially deprived neighbourhoods play a minor role. No statistically significant differences in call volume between densely and less densely populated regions were detected. The results can inform the EMS in future resource planning.

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

Background

In charge of dispatching the ambulances, Emergency Medical Services (EMS) call center specialists often have difficulty deciding the acuity of a case given the information they can gather within a limited time. Although there are protocols to guide their decision-making, observed performance can still lack sensitivity and specificity. Machine learning models have been known to capture complex relationships that are subtle, and well-trained data models can yield accurate predictions in a split of a second.

Methods

In this study, we proposed a proof-of-concept approach to construct a machine learning model to better predict the acuity of emergency cases. We used more than 360,000 structured emergency call center records of cases received by the national emergency call center in Singapore from 2018 to 2020. Features were created using call records, and multiple machine learning models were trained.

Results

A Random Forest model achieved the best performance, reducing the over-triage rate by an absolute margin of 15% compared to the call center specialists while maintaining a similar level of under-triage rate.

Conclusions

The model has the potential to be deployed as a decision support tool for dispatchers alongside current protocols to optimize ambulance dispatch triage and the utilization of emergency ambulance resources.

Differences between the dispatch priority assessments of emergency medical dispatchers and emergency medical services: a prospective register-based study in Finland

BACKGROUND

Responsive and efficient emergency medical services (EMS) require accurate telephone triage. In Finland, such services are provided by Emergency Response Centre Agency (ERC Agency). In 2018, a new Finnish computer-assisted emergency dispatch system was introduced: the Emergency Response Integrated Common Authorities (ERICA). After the introduction of ERICA, the appropriateness of EMS dispatch has not been investigated yet. The study´s objective is to determine the consistency between the priority triage of the emergency medical dispatcher (EMD) and the on-scene priority assessment of the EMS, and whether the priority assessment consistency varied among the dispatch categories.

METHODS

This was a prospective register-based study. All EMS dispatches registered in the Tampere University Hospital area from 1 August 2021 to 31 August 2021 were analysed. The EMD's mission priority triaged during the emergency call was compared with the on-scene EMS's assessment of the priority, derived from the pre-set criteria. The test performance levels were measured from the crosstabulation of true or false positive and negative values of the priority assessment. Statistical significance was analysed using the chi-square test and the Kruskal-Wallis H test, and p-values < 0.05 were considered significant.

RESULTS

Of the 6416 EMS dispatches analysed in this study, 36% (2341) were urgent according to the EMD's dispatch priority, and of these, only 29% (688) were urgent according to the EMS criteria. On the other hand, 64% (4075) of the dispatches were non-urgent according to the EMD's dispatch priority, of which 97% (3949) were non-urgent according to the EMS criteria. Moreover, there were differences between the EMD and EMS priority assessments among the dispatch categories (p < 0.001). The overall efficiency was 72%, sensitivity 85%, specificity 71%, positive predictive value 29%, and negative predictive value 97%.

CONCLUSION

While the EMD recognised the non-urgent dispatches with high consistency with the EMS criteria, most of the EMD's urgent dispatches were not urgent according to the same criteria. This may diminish the availability of the EMS for more urgent missions. Thus, measures are needed to ensure more accurate and therefore, more efficient use of EMS resources in the future.

Accuracy of dispatch and prehospital triage performance in poisonings - A retrospective study from northern Finland

BACKGROUND

Increasing numbers of dispatches place a burden on EMS; this study sought to assess the prehospital evaluation of poisoned patients transported to hospital. The primary aim of this study was to measure dispatch centre and EMS provider performance as well as factors contributing to the recognition of poisoning among prehospital patients. The secondary aim was to compare triage performance between dispatch centres and EMS providers.

METHODS

A retrospective single-centre study in Northern Finland was conducted. Patients suspected as poisonings by dispatch centres as well as other EMS-transported patients who received a diagnosis of poisoning in hospital between June 1, 2015 and June 1, 2017, were included.

RESULTS

There were a total of 1668 poisoning-related EMS missions. Dispatch centres suspected poisonings with sensitivity of 79.9% (95% CI 76.7-82.9) and specificity of 98.9% (95% CI 98.9-99.0) when all EMS missions were taken into account. In a logistic regression model, decreased state of consciousness as dispatch code (OR 7.18, 95% CI 1.90-27.05) and intravenous fluid resuscitation (OR 6.58, 95% CI 1.34-32.37) were associated with EMS transport providers not recognizing poisoning. Overtriage rate appeared significantly higher (33.6%, 95% CI 28.6-39.2) for dispatch when compared with transport (17.8%, 95% CI 13.9-22.6).

CONCLUSION

Dispatch centres seem to suspect poisonings fairly accurately. Poisonings unrecognized by EMS providers may be linked with intravenous fluid resuscitation and decreased patient consciousness. Overtriage appears to resolve somewhat from dispatch to transport. There were no fatal poisonings in this study population.

[Use of emergency services for suicide attempts during the SARS-CoV-2 pandemic-a prevalence study]

Background

The pandemic has caused several changes in the emergency care system. The deployment figures in emergency medical services have shown atypical fluctuations. This has also been explained by changes in behavior and an increased sense of stress among the population. Existing research provides hints for the increased incidence of mental health symptoms in emergency care during ongoing pandemics.

Objective

In this context, this paper examines the occurrence of emergency medical services calls related to the keyword suicide in relation to total calls.

Methods

This is a retrospective cross-sectional study based on routine documentation from a fire and rescue dispatch center with descriptive and exploratory data analyses. The data are divided by settlement-structural county types and compared with incidences and pandemic phases.

Results

Phase 1 and 2a show a decrease in the number of dispatches during the pandemic. In addition, there is a shift in the number of dispatch cases with a context of suicide by structure types in phase 3. A decreased dispatch rate in the sparsely populated rural county is offset by an increase in the metropolitan area. Changes made to the control center system resulted in an increase in the number of dispatch cases in the context of suicide.

Conclusion

Continuous mental health surveillance, including data collected by emergency medical services, can provide valuable insight. The study also highlights the need for standardization of emergency dispatch center data.

Optimizing an Emergency Medical Dispatch System to Improve Prehospital Diagnosis and Treatment of Acute Coronary Syndrome: Nationwide Retrospective Study in China

Background

Acute coronary syndrome (ACS) is the most time-sensitive acute cardiac event that requires rapid dispatching and response. The medical priority dispatch system (MPDS), one of the most extensively used types of emergency dispatch systems, is hypothesized to provide better-quality prehospital emergency treatment. However, few studies have revealed the impact of MPDS use on the process of ACS care.

Objective

This study aimed to investigate whether the use of MPDS was associated with higher prehospital diagnosis accuracy and shorter prehospital delay for patients with ACS transferred by an emergency medical service (EMS), using a national database in China.

Methods

This retrospective analysis was based on an integrated database of China’s MPDS and hospital registry. From January 1, 2016, to December 31, 2020, EMS-treated ACS cases were divided into before MPDS and after MPDS groups in accordance with the MPDS launch time at each EMS center. The primary outcomes included diagnosis consistency between hospital admission and discharge, and prehospital delay. Multivariable logistic regression and propensity score–matching analysis were performed to compare outcomes between the 2 groups for total ACS and subtypes.

Results

A total of 9806 ACS cases (3561 before MPDS and 6245 after MPDS) treated by 43 EMS centers were included. The overall diagnosis consistency of the after MPDS group (Cohen κ=0.918, P<.001) was higher than that of the before MPDS group (Cohen κ=0.889, P<.001). After the use of the MPDS, the call-to-EMS arrival time was shortened in the matched ACS cases (20.0 vs 16.0 min, P<.001; adjusted difference: –1.67, 95% CI –2.33 to –1.02; P<.001) and in the subtype of ST-elevation myocardial infarction (adjusted difference: –3.81, 95% CI –4.63 to –2.98, P<.001), while the EMS arrival-to-door time (20.0 vs 20.0 min, P=.31) was not significantly different in all ACS cases and subtypes.

Conclusions

The optimized use of MPDS in China was associated with increased diagnosis consistency and a reduced call-to-EMS arrival time among EMS-treated patients with ACS. An emergency medical dispatch system should be designed specifically to fit into different prehospital modes in the EMS system on a regional basis.

Exploring the challenges to telephone triage in pre-hospital emergency care: a qualitative content analysis

Background

One of the important indices for the efficacy of pre-hospital emergency services is telephone triage. The dispatching team members are faced with many challenges in telephone triage which can adversely affect their performance. This study was conducted in the south of Iran to determine the challenges to telephone triage in pre-hospital emergency services.

Method

The present study is qualitative-descriptive where the sample was selected purposefully. Data were collected through 18 semi-structured, in-depth interviews with 18 dispatching team members in pre-hospital emergency care. The collected qualitative data were analyzed using the content analysis approach recommended by Graneheim and Lundman.

Results

Analysis of the data resulted in the emergence of three themes and ten sub-themes. The three main themes extracted from the data included inefficient interaction, insufficient and unreal information, and professional challenges.

Conclusion

The dispatching unit personnel in pre-hospital emergency care are confronted with various interactional, organizational, and professional issues. Accordingly, the senior managers in emergency departments should take effective measures to remove the existing barriers toward improving the efficacy of telephone triage and, by extension, the quality of pre-hospital emergency care services.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-08585-z.

Association of Cardiac Arrest With Opioid Overdose in Transport

Introduction

Drug overdose is the leading cause of injury-related death in the United States. It has been linked to respiratory depression and cardiac toxicity, both of which can lead to cardiac arrest. Despite this potential association, few studies have examined this relationship, particularly in transport to the hospital. The purpose of this research was to determine if there was a relationship between opioid overdose and cardiac arrest in transport.

Methods

A sample (n = 1 000 000) was utilized from the National EMS Information System (NEMSIS) from the year 2019. A logistic regression model was used to predict cardiac arrest from dispatch reason with gender, race, and age included as controls.

Results

Overdose-related dispatch reason was associated with an increased likelihood of cardiac arrest in transport (Odds Ratio = 1.65, 95% Confidence Interval: [1.22, 2.22]).

Conclusions

Opioid overdose is associated with an increased incidence of cardiac arrest in transport in the United States.

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.

Improving ambulance dispatch triage to trauma: A scoping review using the framework of development and evaluation of clinical prediction rules

OBJECTIVE

Ambulance dispatch algorithms should function as clinical prediction rules, identifying high acuity patients for advanced life support, and low acuity patients for non-urgent transport. Systematic reviews of dispatch algorithms are rare and focus on study types specific to the final phases of rule development, such as impact studies, and may miss the complete value-added evidence chain. We sought to summarise the literature for studies seeking to improve dispatch in trauma by performing a scoping review according to standard frameworks for developing and evaluating clinical prediction rules.

METHODS

We performed a scoping review searching MEDLINE, EMBASE, CINAHL, the CENTRAL trials registry, and grey literature from January 2005 to October 2021. We included all study types investigating dispatch triage to injured patients in the English language. We reported the clinical prediction rule phase (derivation, validation, impact analysis, or user acceptance) and the performance and outcomes measured for high and low acuity trauma patients.

RESULTS

Of 2067 papers screened, we identified 12 low and 30 high acuity studies. Derivation studies were most common (52%) and rule-based computer-aided dispatch was the most frequently investigated (23 studies). Impact studies rarely reported a prior validation phase, and few validation studies had their impact investigated. Common outcome measures in each phase were infrequent (0 to 27%), making a comparison between protocols difficult. A series of papers for low acuity patients and another for pediatric trauma followed clinical prediction rule development. Some low acuity Medical Priority Dispatch System codes are associated with the infrequent requirement for advanced life support and clinician review of computer-aided dispatch may enhance dispatch triage accuracy in studies of helicopter emergency medical services.

CONCLUSIONS

Few derivation and validation studies were followed by an impact study, indicating important gaps in the value-added evidence chain. While impact studies suggest clinician oversight may enhance dispatch, the opportunity exists to standardize outcomes, identify trauma-specific low acuity codes, and develop intelligent dispatch systems.

Qualité en régulation médicale : critères et évaluation

Les Samu Centre 15 sont soumis à une politique de qualité qui répond à une approche transversale prenant en considération le patient, le professionnel et l’établissement de santé. La démarche qualité assure à chaque patient de pouvoir accéder à une plateforme de communication en tout point du territoire et d’obtenir pour toutes demandes de soins urgents ou non programmés une réponse juste et adaptée. Pour les professionnels des Samu Centres 15, la qualité en régulation appelle à améliorer puis sécuriser les pratiques dans un contexte de sollicitation constamment croissante depuis ces dernières années. Il s’agit également de garantir des conditions de travail optimales pour les intervenants et de contribuer ainsi à une réponse de qualité. Cette démarche s’intègre également dans la certification par la Haute Autorité de santé des établissements de santé et rentre dans le concept d’hôpitaux « magnétiques » pour allier résultats sanitaires performants et conditions de travail bienveillantes pour les soignants. La stratégie d’amélioration continue de la qualité doit s’appuyer sur des travaux de recherche appliquée à la régulation médicale qu’il convient de développer. S’inspirer des méthodes utilisées dans d’autres systèmes de traitement des appels d’urgence et intégrer de nouveaux outils au sein des Samu Centres 15 pourraient contribuer à atteindre cet objectif de qualité.

A predictive ambulance dispatch algorithm to the scene of a motor vehicle crash: the search for optimal over and under triage rates

Background

Calls for emergency medical assistance at the scene of a motor vehicle crash (MVC) substantially contribute to the demand on ambulance services. Triage by emergency medical dispatch systems is therefore important, to ensure the right care is provided to the right patient, in the right amount of time. A lights and sirens (L&S) response is the highest priority ambulance response, also known as a priority one or hot response. In this context, over triage is defined as dispatching an ambulance with lights and sirens (L&S) to a low acuity MVC and under triage is not dispatching an ambulance with L&S to those who require urgent medical care. We explored the potential for crash characteristics to be used during emergency ambulance calls to identify those MVCs that required a L&S response.

Methods

We conducted a retrospective cohort study using ambulance and police data from 2014 to 2016. The predictor variables were crash characteristics (e.g. road surface), and Medical Priority Dispatch System (MPDS) dispatch codes. The outcome variable was the need for a L&S ambulance response. A Chi-square Automatic Interaction Detector technique was used to develop decision trees, with over/under triage rates determined for each tree. The model with an under/over triage rate closest to that prescribed by the American College of Surgeons Committee on Trauma (ACS COT) will be deemed to be the best model (under triage rate of ≤ 5% and over triage rate of between 25–35%.

Results

The decision tree with a 2.7% under triage rate was closest to that specified by the ACS COT, had as predictors—MPDS codes, trapped, vulnerable road user, anyone aged 75 + , day of the week, single versus multiple vehicles, airbag deployment, atmosphere, surface, lighting and accident type. This model had an over triage rate of 84.8%.

Conclusions

We were able to derive a model with a reasonable under triage rate, however this model also had a high over triage rate. Individual EMS may apply the findings here to their own jurisdictions when dispatching to the scene of a MVC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12873-022-00609-5.

Detection to Hospital Door: Gender Differences of Patients With Acute Stroke Symptoms

Although prehospital stroke management is challenging, it is a crucial part of the acute stroke chain to enable equal access to highly specialised stroke care. It involves a critical understanding of players usually not specialized in acute stroke treatments. There is contradictory information about gender inequity in prehospital stroke detection, dispatch, and delivery to hospital stroke centers. The aim of this narrative review is to summarize the knowledge of gender differences in the first three stages of acute stroke management. Information on the detection of acute stroke symptoms by patients, their relatives, and bystanders is discussed. Women seem to have a better overall knowledge about stroke, although general understanding needs to be improved. However, older age and different social situations of women could be identified as reasons for reduced and delayed help-seeking. Dispatch and delivery lie within the responsibility of the emergency medical service. Differences in clinical presentation with symptoms mainly affecting general conditions could be identified as a crucial challenge leading to gender inequity in these stages. Improvement of stroke education has to be applied to tackle this inequal management. However, specifically designed projects and analyses are needed to understand more details of sex differences in prehospital stroke management, which is a necessary first step for the potential development of substantially improving strategies.

A Review of Incident Prediction, Resource Allocation, and Dispatch Models for Emergency Management

In the last fifty years, researchers have developed statistical, data-driven, analytical, and algorithmic approaches for designing and improving emergency response management (ERM) systems. The problem has been noted as inherently difficult and constitutes spatio-temporal decision making under uncertainty, which has been addressed in the literature with varying assumptions and approaches. This survey provides a detailed review of these approaches, focusing on the key challenges and issues regarding four sub-processes: (a) incident prediction, (b) incident detection, (c) resource allocation, and (c) computer-aided dispatch for emergency response. We highlight the strengths and weaknesses of prior work in this domain and explore the similarities and differences between different modeling paradigms. We conclude by illustrating open challenges and opportunities for future research in this complex domain.

Epidemiology of emergency ambulance service calls related to COVID-19 in Scotland: a national record linkage study

BACKGROUND

COVID-19 has overwhelmed health services across the world; its global death toll has exceeded 5.3 million and continues to grow. There have been almost 15 million cases of COVID-19 in the UK. The need for rapid accurate identification, appropriate clinical care and decision making, remains a priority for UK ambulance service. To support identification and conveyance decisions of patients presenting with COVID-19 symptoms the Scottish Ambulance Service introduced the revised Medical Priority Dispatch System Protocol 36, enhanced physician led decision support and prehospital clinical guidelines. This study aimed to characterise the impact of these changes on the pathways and outcomes of people attended by the SAS) with potential COVID-19.

METHODS

A retrospective record linkage cohort study using National Data collected from NHS Scotland over a 5 month period (April-August 2020).

RESULTS

The SAS responded to 214,082 emergency calls during the study time period. The positive predictive value of the Protocol 36 to identify potentially COVID-19 positive patients was low (17%). Approximately 60% of those identified by Protocol 36 as potentially COVID-19 positive were conveyed. The relationship between conveyance and mortality differed between Protocol 36 Covid-19 positive calls and those that were not. In those identified by Protocol 36 as Covid-19 negative, 30 day mortality was higher in those not conveyed (not conveyed 9.2%; conveyed 6.6%) but in the Protocol 36 Covid-19 positive calls, mortality was higher in those conveyed (not conveyed 4.3% conveyed 8.8%). Thirty-day mortality rates of those with COVID-19 diagnosed through virology was between 28.8 and 30.2%.

CONCLUSION

The low positive predictive value (17%) of Protocol 36 in identifying potential COVID-19 in patients emphasises the importance of ambulance clinicians approaching each call as involving COVID-19, reinforcing the importance of adhering to existing policy and continued use of PPE at all calls. The non-conveyance rate of people that were categorised as COVID-19 negative was higher than in the preceding year in the same service. The reasons for the higher rates of non-conveyance and the relationship between non conveyance rates and death at 3 and 30 days post index call are unknown and would benefit from further study.

A registry-based observational study comparing emergency calls assessed by emergency medical dispatchers with and without support by registered nurses

Background

The requirement concerning formal education for emergency medical dispatcher (EMD) is debated and varies, both nationally and internationally. There are few studies on the outcomes of emergency medical dispatching in relation to professional background. This study aimed to compare calls handled by an EMD with and without support by a registered nurse (RN), with respect to priority level, accuracy, and medical condition.

Methods

A retrospective observational study, performed on registry data from specific regions during 2015. The ambulance personnel’s first assessment of the priority level and medical condition was used as the reference standard. Outcomes were: the proportion of calls dispatched with a priority in concordance with the ambulance personnel’s assessment; over- and undertriage; the proportion of most adverse over- and undertriage; sensitivity, specificity and predictive values for each of the ambulance priorities; proportion of calls dispatched with a medical condition in concordance with the ambulance personnel’s assessment. Proportions were reported with 95% confidence intervals. χ²-test was used for comparisons. P-levels < 0.05 were regarded as significant.

Results

A total of 25,025 calls were included (EMD n = 23,723, EMD + RN n = 1302). Analyses relating to priority and medical condition were performed on 23,503 and 21,881 calls, respectively. A dispatched priority in concordance with the ambulance personnel’s assessment were: EMD n = 11,319 (50.7%) and EMD + RN n = 481 (41.5%) (p < 0.01). The proportion of overtriage was equal for both groups: EMD n = 5904, EMD + RN n = 306, (26.4%) p = 0.25). The proportion of undertriage for each group was: EMD n = 5122 (22.9%) and EMD + RN n = 371 (32.0%) (p < 0.01). Sensitivity for the most urgent priority was 54.6% for EMD, compared to 29.6% for EMD + RN (p < 0.01), and specificity was 67.3% and 84.8% (p < 0.01) respectively. A dispatched medical condition in concordance with the ambulance personnel’s assessment were: EMD n = 13,785 (66.4%) and EMD + RN n = 697 (62.2%) (p = 0.01).

Conclusions

A higher precision of emergency medical dispatching was not observed when the EMD was supported by an RN. How patient safety is affected by the observed divergence in dispatched priorities is an area for future research.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13049-021-00987-y.

Towards enhanced telephone triage for chest pain: a Delphi study to define life-threatening conditions that must be identified

BACKGROUND

Improving telephone triage for patients with chest pain has been identified as a national research priority. However, there is a lack of strong evidence to define the life-threatening conditions (LTCs) that telephone triage ought to identify. Therefore, we aimed to build consensus for the LTCs associated with chest pain that ought to be identified during telephone triage for emergency calls.

METHODS

We conducted a Delphi study in three rounds. Twenty experts in pre-hospital care and emergency medicine experience from the UK were invited to participate. In round I, experts were asked to list all LTCs that would require priority 1, 2, and 4 ambulance responses. Round II was a ranking evaluation, and round III was a consensus round. Consensus level was predefined at > = 70%.

RESULTS

A total of 15 participants responded to round one and 10 to rounds two and three. Of 185 conditions initially identified by the experts, 26 reached consensus in the final round. Ten conditions met consensus for requiring priority 1 response: oesophageal perforation/rupture; ST elevation myocardial infarction; non-ST elevation myocardial infarction with clinical compromise (defined, also by consensus, as oxygen saturation < 90%, heart rate < 40/min or systolic blood pressure < 90 mmHg); acute heart failure; cardiac tamponade; life-threatening asthma; cardiac arrest; tension pneumothorax and massive pulmonary embolism. An additional six conditions met consensus for priority 2 response, and three for priority 4 response.

CONCLUSION

Using expert consensus, we have defined the LTCs that may present with chest pain, which ought to receive a high-priority ambulance response. This list of conditions can now form a composite primary outcome for future studies to derive and validate clinical prediction models that will optimise telephone triage for patients with a primary complaint of chest pain.