Impact of crowding in local ambulance demand on call-to-ambulance scene arrival in out-of-hospital cardiac arrest.

BACKGROUND: Rapid emergency medical service (EMS) response is an important prognostic factor in out-of-hospital cardiac arrest (OHCA). This study aims to evaluate the association between local hourly EMS demand and ambulance response in OHCA. METHODS: OHCA occurring in 24 districts of Seoul from 2013 to 2018 was analyzed. Hourly ambulance demand per ambulance in each local district of patient location at the hour of cardiac arrest was calculated as the crowding index. The crowding index was categorized according to quartiles (1Q: ≤0.43, 2Q: 0.44-0.67, 3Q: 0.68-0.99, 4Q: ≥1.0 calls/h\r/ambulance). The primary outcome was ambulance dispatched within 1 km of the OHCA scene. Multivariable logistic regression analysis was performed to test the association between the local hourly ambulance demand and outcomes. RESULTS: A total of 26,479 patients were analyzed. The rate of ambulance dispatched within 1 km decreased according to the crowding quartile (1Q: 31.3%, 2Q: 30.0%, 3Q: 28.8%, and 4Q: 26.6%). Compared to 1Q, adjusted odds ratios (95% CIs) of dispatch distance within 1 km in 2Q, 3Q, and 4Q were 0.92 (0.86-0.99), 0.86 (0.80-0.94), and 0.77 (0.71-0.84), respectively. CONCLUSION: Crowding in local ambulance demand was associated with less ambulance dispatched within 1 km and delayed response to the scene in OHCA. Strategies to mitigate and adjust to ambulance demand crowding may be considered for better EMS response performance.

Emergency medical dispatch services across Pan-Asian countries: a web-based survey.

BACKGROUND: Dispatch services (DS's) form an integral part of emergency medical service (EMS) systems. The role of a dispatcher has also evolved into a crucial link in patient care delivery, particularly in dispatcher assisted cardio-pulmonary resuscitation (DACPR) during out-of-hospital cardiac arrest (OHCA). Yet, there has been a paucity of research into the emerging area of dispatch science in Asia. This paper compares the characteristics of DS's, and state of implementation of DACPR within the Pan-Asian Resuscitation Outcomes (PAROS) network. METHODS: A cross-sectional descriptive survey addressing population characteristics, DS structures and levels of service, state of DACPR implementation (including protocols and quality improvement programs) among PAROS DS's. RESULTS: 9 DS's responded, representing a total of 23 dispatch centres from 9 countries that serve over 80 million people. Most PAROS DS's operate a tiered dispatch response, have implemented medical oversight, and tend to be staffed by dispatchers with a predominantly medical background. Almost all PAROS DS's have begun tracking key EMS indicators. 77.8% (n = 7) of PAROS DS's have introduced DACPR. Of the DS's that have rolled out DACPR, 71.4% (n = 5) provided instructions in over one language. All DS's that implemented DACPR and provided feedback to dispatchers offered feedback on missed OHCA recognition. The majority of DS's (83.3%; n = 5) that offered DACPR and provided feedback to dispatchers also implemented corrective feedback, while 66.7% (n = 4) offered positive feedback. Compression-only CPR was the standard instruction for PAROS DS's. OHCA recognition sensitivity varied widely in PAROS DS's, ranging from 32.6% (95% CI: 29.9-35.5%) to 79.2% (95% CI: 72.9-84.4%). Median time to first compression ranged from 120 s to 220 s. CONCLUSIONS: We found notable variations in characteristics and state of DACPR implementation between PAROS DS's. These findings will lay the groundwork for future DS and DACPR studies in the PAROS network.

Flattening the COVID-19 Curve: The Unique Role of Emergency Medical Services in Containing a Global Pandemic.

BACKGROUND: The potential excess flow of patients into emergency departments and community clinics for testing and examination during a pandemic poses a major issue. These additional patients may lead to the risk of viral transmission to other patients and medical teams. To contain the spread of coronavirus disease-2019 (COVID-19), the Israeli Ministry of Health initiated a plan spearheaded by Magen David Adom (MDA), Israel's national emergency medical services (EMS) organization. OBJECTIVES: To describe outbreak containment actions initiated by MDA, including a COVID-19 tele-triage center and home testing by paramedics. METHODS: Retrospective analysis was conducted of de-identified data from the call management and command and control systems during the first period of the COVID-19 outbreak in Israel (23 February 2020-15 March 2020). RESULTS: During the study period, the total number of calls to the dispatch centers was 477,321 with a daily average of 21,696, compared to 6000-6500 during routine times. The total number of COVID-19 related calls was 334,230 (daily average 15,194). There were 28,454 calls (8.51% of all COVID-19 related calls, average 1293/day) transferred to the COVID-19 call center. Of the COVID-19 call center inquiries, 8390 resulted in the dispatch of a dedicated vehicle, including a paramedic wearing personal protective equipment, to collect samples for testing (daily average 381). CONCLUSIONS: Maximizing EMS during a pandemic using phone triage, in addition to dispatching paramedics to perform home testing, may significantly distance infected patients from the public and health care system. These steps can further minimize the spread of disease.

High acuity rural transport: findings from a qualitative investigation.

INTRODUCTION: The High Acuity Response Team (HART) was introduced in British Columbia (BC), Canada, to fill a gap in transport for rural patients that was previously being met by nurses and physicians leaving their communities to escort patients in need of critical care. The HART team consists of a critical care registered nurse (CCRN) and registered respiratory therapist (RRT) and attends acute care patients in rural sites by either stabilizing them in their community or transporting them. HART services are deployed in partnership with provincial ambulance services, which provide vehicles and coordination of all requests in the province for patient transport. This article presents the qualitative findings from a research evaluation of the efficacy of the HART model, including staffing and inter-organizational functioning. METHOD: Open-ended qualitative research interviewing was done with key stakeholders from 21 sites. Research participants included HART CCRNs, RRTs, administrative leads, as well as local emergency department (ED) physicians and nurses. Thematic analysis was done of the transcripts. RESULTS: A total of 107 interviews in 21 study sites were completed. Participants described characteristics of the model, perceptions of efficacy and areas for improvement. Rural sites reported a decrease in physician- and nurse-accompanied transports for high-acuity patients due to the HART team, but also noted challenges in delayed deployment, sometimes leading to adverse patient outcomes. CONCLUSIONS: The salient issues for the HART model were grounded in a somewhat artificial distinction between pre-hospital and interfacility transport for rural patients, which leads to a lack of service coordination and potentially avoidable delays. A beneficial systems change would be to move towards dedicated integration of high-acuity transport services into hospital organizational structures and community health services in rural areas.

Decision-Making in Pediatric Transport Team Dispatch Using Script Concordance Testing.

OBJECTIVES: Our objective was to compare decision-making in dispatching pediatric transport teams by Medical Directors of pediatric transport teams (serving as experts) to that of Pediatric Intensivists and Critical Care fellows who often serve as Medical Control physicians. Understanding decision-making around team composition and dispatch could impact clinical management, cost effectiveness, and educational needs. DESIGN: Survey was developed using Script Concordance Testing guidelines. The survey contained 15 transport case vignettes covering 20 scenarios (45 questions). Eleven scenarios assessed impact of intrinsic patient factors (e.g., procedural needs), whereas nine assessed extrinsic factors (e.g., weather). SETTING: Pediatric Critical Care programs accredited by the Accreditation Council for Graduate Medical Education (the United States). SUBJECTS: Pediatric Intensivists and senior Critical Care fellows at Pediatric Critical Care programs were the target population with Transport Medical Directors serving as the expert panel. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Survey results were scored per Script Concordance Testing guidelines. Concordance within groups was assessed using simple percentage agreement. There was little concordance in decision-making by Transport Medical Directors (median Script Concordance Testing percentage score [interquartile range] of 33.9 [30.4-37.3]). In addition, there was no statistically significant difference between the median Script Concordance Testing scores among the senior fellows and Pediatric Intensivists (31.1 [29.6-33.2] vs 29.7 [28.3-32.3], respectively; p = 0.12). Transport Medical Directors were more concordant on reasoning involving intrinsic patient factors rather than extrinsic factors (10/21 vs 4/24). CONCLUSIONS: Our study demonstrates pediatric transport team dispatch decision-making discordance by pediatric critical care physicians of varying levels of expertise and experience. Script Concordance Testing at a local level may better elucidate standards in medical decision-making within pediatric critical care physicians. The development of a curriculum, which provides education and trains our workforce on the logistics of pediatric transport team dispatch, would help standardize practice and evaluate outcomes based on decision-making.

A new preparedness policy for EMS logistics.

Response time in emergency medical services (EMS) is defined as the interval for an ambulance to arrive the scene after receipt of a 911 call. When several ambulances are available upon the receipt of a new call, a decision of selecting an ambulance has to be made in an effort to reduce response time. Dispatching the closest unit available is commonly used in practice; however, recently the Preparedness policy was designed that is in a simplistic form yet being capable of securing a long-term efficiency. This research aims to improve the Preparedness policy, resolving several critical issues inherent in the current form of the policy. The new Preparedness policy incorporates a new metric of preparedness based on the notion of centrality and involves a tuning parameter, weight on preparedness, which has to be appropriately chosen according to operational scenario. Computational experiment shows that the new policy significantly improves the former policy robustly in various scenarios.

A markov decision process model for the optimal dispatch of military medical evacuation assets.

We develop a Markov decision process (MDP) model to examine aerial military medical evacuation (MEDEVAC) dispatch policies in a combat environment. The problem of deciding which aeromedical asset to dispatch to each service request is complicated by the threat conditions at the service locations and the priority class of each casualty event. We assume requests for MEDEVAC support arrive sequentially, with the location and the priority of each casualty known upon initiation of the request. The United States military uses a 9-line MEDEVAC request system to classify casualties as being one of three priority levels: urgent, priority, and routine. Multiple casualties can be present at a single casualty event, with the highest priority casualty determining the priority level for the casualty event. Moreover, an armed escort may be required depending on the threat level indicated by the 9-line MEDEVAC request. The proposed MDP model indicates how to optimally dispatch MEDEVAC helicopters to casualty events in order to maximize steady-state system utility. The utility gained from servicing a specific request depends on the number of casualties, the priority class for each of the casualties, and the locations of both the servicing ambulatory helicopter and casualty event. Instances of the dispatching problem are solved using a relative value iteration dynamic programming algorithm. Computational examples are used to investigate optimal dispatch policies under different threat situations and armed escort delays; the examples are based on combat scenarios in which United States Army MEDEVAC units support ground operations in Afghanistan.

Dispatch of Helicopter Emergency Medical Services Via Advanced Automatic Collision Notification.

BACKGROUND: Advanced automatic collision notification (AACN) is a system for predicting occupant injury from collision information. If the helicopter emergency medical services (HEMS) physician can be alerted by AACN, it may be possible to reduce the time to patient contact. OBJECTIVE: The purpose of this study was to validate the feasibility of early HEMS dispatch via AACN. METHODS: A full-scale validation study was conducted. A car equipped with AACN was made to collide with a wall. Immediately after the collision, the HEMS was alerted directly by the operation center, which received the information from AACN. Elapsed times were recorded and compared with those inferred from the normal, real-world HEMS emergency request process. RESULTS: AACN information was sent to the operation center only 7 s after the collision; the HEMS was dispatched after 3 min. The helicopter landed at the temporary helipad 18 min later. Finally, medical intervention was started 21 min after the collision. Without AACN, it was estimated that the HEMS would be requested 14 min after the collision by fire department personnel. The start of treatment was estimated to be at 32 min, which was 11 min later than that associated with the use of AACN. CONCLUSIONS: The dispatch of the HEMS using the AACN can shorten the start time of treatment for patients in motor vehicle collisions. This study demonstrated that it is feasible to automatically alert and activate the HEMS via AACN.

Smartphone application alerts for early trauma team activation: Millennial technology in healthcare.

BACKGROUND: Data access through smartphone applications (apps) has reframed procedure and policy in healthcare, but its impact in trauma remains unclear. Citizen is a free app that provides real-time alerts curated from 911 dispatch data. Our primary objective was to determine whether app alerts occurred earlier than recorded times for trauma team activation and emergency department arrival. METHODS: Trauma registry entries were extracted from a level one urban trauma center from January 1, 2018 to June 30, 2019 and compared with app metadata from the center catchment area. We matched entries to metadata according to description, date, time, and location then compared metadata timestamps to trauma team activation and emergency department arrival times. We computed percentage of time the app reported traumatic events earlier than trauma team activation or emergency department arrival along with exact binomial 95% confidence interval; median differences between times were presented along with interquartile ranges. RESULTS: Of 3,684 trauma registry entries, 209 (5.7%) matched app metadata. App alerts were earlier for 96.1% and 96.2% of trauma team activation and emergency department arrival times, respectively, with events reported median 36 (24-53, IQR) minutes earlier than trauma team activation and 32 (25-42, IQR) minutes earlier than emergency department arrival. Registry entries for younger males, motor vehicle-related injuries and penetrating traumas were more likely to match alerts (P < .0001). CONCLUSION: Apps like Citizen may provide earlier notification of traumatic events and therefore earlier mobilization of trauma service resources. Earlier notification may translate into improved patient outcomes. Additional studies into the benefit of apps for trauma care are warranted.

Analysis of Monitoring, Early Warning and Emergency Response System for New Major Infectious Diseases in China and Overseas.

In recent years, the impact of new major infectious diseases on people's normal life is becoming more and more frequent, which has brought great impact on people's life safety and social economy, especially the corona virus disease 2019, which has been sweeping the globe. Public health and disease prevention and control systems in different countries have different performances in response to the pandemic, but they all have exposed many shortcomings. Countries around the world urgently need to improve the monitoring, early warning and emergency response systems for new major infectious diseases. As the outpost and main part of medical rescue, the hospital urgently needs to establish a set of scientifically advanced emergency response mechanism that is suitable for the business process of the medical system and unified standards in order to improve the response efficiency and quality of emergency treatment.

Description of call handling in emergency medical dispatch centres in Scandinavia: recognition of out-of-hospital cardiac arrests and dispatcher-assisted CPR.

BACKGROUND: The European resuscitation council have highlighted emergency medical dispatch centres as an important key player for early recognition of Out-of-Hospital Cardiac Arrest (OHCA) and in providing dispatcher assisted cardiopulmonary resuscitation (CPR) before arrival of emergency medical services. Early recognition is associated with increased bystander CPR and improved survival rates. The aim of this study is to describe OHCA call handling in emergency medical dispatch centres in Copenhagen (Denmark), Stockholm (Sweden) and Oslo (Norway) with focus on sensitivity of recognition of OHCA, provision of dispatcher-assisted CPR and time intervals when CPR is initiated during the emergency call (NO-CPRprior), and to describe OHCA call handling when CPR is initiated prior to the emergency call (CPRprior). METHODS: Baseline data of consecutive OHCA eligible for inclusion starting January 1st 2016 were collected from respective cardiac arrest registries. A template based on the Cardiac Arrest Registry to Enhance Survival definition catalogue was used to extract data from respective cardiac arrest registries and from corresponding audio files from emergency medical dispatch centres. Cases were divided in two groups: NO-CPRprior and CPRprior and data collection continued until 200 cases were collected in the NO-CPRprior-group. RESULTS: NO-CPRprior OHCA was recognised in 71% of the calls in Copenhagen, 83% in Stockholm, and 96% in Oslo. Abnormal breathing was addressed in 34, 7 and 98% of cases and CPR instructions were started in 50, 60, and 80%, respectively. Median time (mm:ss) to first chest compression was 02:35 (Copenhagen), 03:50 (Stockholm) and 02:58 (Oslo). Assessment of CPR quality was performed in 80, 74, and 74% of the cases. CPRprior comprised 71 cases in Copenhagen, 9 in Stockholm, and 38 in Oslo. Dispatchers still started CPR instructions in 41, 22, and 40% of the calls, respectively and provided quality assessment in 71, 100, and 80% in these respective instances. CONCLUSIONS: We observed variations in OHCA recognition in 71-96% and dispatcher assisted-CPR were provided in 50-80% in NO-CPRprior calls. In cases where CPR was initiated prior to emergency calls, dispatchers were less likely to start CPR instructions but provided quality assessments during instructions.

The Effectiveness of a New Dispatcher-Assisted Basic Life Support Training Program on Quality in Cardiopulmonary Resuscitation Performance During Training and Willingness to Perform Bystander Cardiopulmonary Resuscitation: A Cluster Randomized Controlled Study.

INTRODUCTION: A new dispatcher-assisted basic life support training program, called "Home Education and Resuscitation Outcome Study (HEROS)" was developed with a goal to provide high-quality dispatcher-assisted cardiopulmonary resuscitation (CPR) training, with a focus on untrained home bystanders. This study aimed to determine whether the HEROS program is associated with improved quality in CPR performance during training and willingness to provide bystander CPR compared with other basic life support programs without dispatcher-assisted CPR (non-HEROS). METHODS: This clustered randomized trial was conducted in 3 district health centers in Seoul. Intervention group was trained with the HEROS program and control group was trained with non-HEROS program. The primary outcome was overall CPR quality, measured as total CPR score. Secondary outcomes were other CPR quality parameters including average compression depth and rate, percentages of adequate depth, and acceptable release. Tertiary outcomes were posttraining survey results. Difference in difference analysis was performed to analyze the outcomes. RESULTS: Among total 1929 trainees, 907 (47.0%) were trained with HEROS program. Compared with the non-HEROS group, the HEROS group showed higher-quality CPR performances and better maintenance of their CPR quality throughout the course (total scores of 84% vs. 80% for first session and 72% vs. 67% for last session; difference in difference of 12.2 vs. 13.2). Other individual CPR parameters also showed significantly higher quality in the HEROS group. The posttraining survey showed that both groups were highly willing to perform bystander CPR (91.4% in the HEROS vs. 92.3% in the non-HEROS) with only 3.4% of respondents in the HEROS group were not willing to volunteer compared with 6.2% in the non-HEROS group (P < 0.01). CONCLUSIONS: The HEROS training program helped trainees perform high-quality CPR throughout the course and enhanced their willingness to provide bystander CPR.

A Revised Ecological Model of Occupational Stress: Applications to 9-1-1 Telecommunicators.

Background: A cohesive body of scientific evidence has documented the adverse impacts of occupational stress on worker health and safety and, to a lesser extent, on organizational outcomes. How such adverse impacts may be prevented and/or ameliorated are important to understand, but progress has been limited due to the lack of a robust and comprehensive theoretical model of occupational stress. Methods: Building on a review of existing theoretical models of occupational stress and an ecological framework, a multilevel conceptual model of occupational stress and strain is proposed that identifies various and potentially interacting sources of occupational stressors as well as potential protective factors. Results: The revised ecological model proposed herein embraces a broad conceptualization of outcomes and includes an individual worker, work unit (team) performance as well as organizational level outcomes; for example, resilience/dysfunction. Conclusion/Application to Practice: This model provides occupational health nurses with an improved understanding of occupational and worker health as well as guidance in developing targeted interventions and generating new lines of occupational stress research.

Championing survival: connecting the unknown network of responders to address out-of-hospital cardiac arrest.

Early intervention for out-of-hospital cardiac arrest (OHCA) presents a challenge for Emergency Medical Services (EMS) across Europe. Strategies designed to address this include education and training initiatives for citizens and building CPR skills capacity and awareness amongst health care professionals. However, there is a need to improve access to volunteer first responders who can commence CPR and defibrillate before the arrival of EMS. In the UK, initiatives such GoodSAM have integrated crowdsourcing technology with ambulance services to allow them autonomy in alerting responders to OHCAs which is parallel to an EMS dispatch. These services are building capacity to improve the initial 'call for help' and time to commence CPR and defibrillation if indicated. The next step is to identify and implement appropriate methods for public engagement, involvement and eventual networking of resources with statutory bodies such as local EMS. As crowdsourcing volunteer responders is at an early stage, there is a need to determine whether crowdsourcing is associated with patient outcomes, what its impact is on those responding to OHCA, whether it facilitates or impedes current services, and whether it is a safe and cost effective way to involve citizens to intervene in the community during cardiac arrest or other medical emergencies? Addressing such issues is likely to provide further insight into the role and effectiveness of new technologies and their potential impact on the wider community.

Prehospital time and mortality in patients requiring a highest priority emergency medical response: a Danish registry-based cohort study.

OBJECTIVE: To examine the association between time from emergency medical service vehicle dispatch to hospital arrival and 1-day and 30-day mortality. DESIGN: Register-based cohort study. SETTING: North Denmark Region (≈8000 km2, catchment population ≈600 000). PARTICIPANTS: We included all highest priority dispatched ambulance transports in North Denmark Region in 2006-2012. INTERVENTIONS: Using logistic regression and the g-formula approach, we examined the association between time from emergency dispatch to hospital arrival and mortality for presumed heart, respiratory, cerebrovascular and other presumed medical conditions, as well as traffic or other accidents, as classified by emergency dispatch personnel. MAIN OUTCOME MEASURES: 1-day and 30-day mortality. RESULTS: Among 93 167 individuals with highest priority ambulances dispatched, 1948 (2.1%) were dead before the ambulance arrived and 19 968 (21.4%) were transported to the hospital under highest priority (median total prehospital time from dispatch to hospital arrival 47 min (25%-75%: 35-60 min); 95th percentile 84 min). Among 18 709 with population data, 1-day mortality was 10.9% (n=2038), and was highest for patients with dyspnoea (20.4%) and lowest for patients with traffic accidents (2.8%). Thirty-day mortality was 18.3% and varied between 36.6% (patients with dyspnoea) and 3.7% (traffic accidents). One-day mortality was not associated with total prehospital time, except for presumed heart conditions, where longer prehospital time was associated with decreased mortality: adjusted OR for >60 min vs 0-30 min was 0.61 (95% CI 0.40 to 0.91). For patients with dyspnoea, OR for >60 min vs 0-30 min was 0.90 (95% CI 0.56 to 1.45), for presumed cerebrovascular conditions OR 1.41 (95% CI 0.53 to 3.78), for other presumed medical conditions OR 0.84 (95% CI 0.70 to 1.02), for traffic accidents OR 0.65 (95% CI 0.29 to 1.48) and for other accidents OR 0.84 (95% CI 0.47 to 1.51). Similar findings were found for 30-day mortality. CONCLUSIONS: In this study, where time from emergency dispatch to hospital arrival mainly was <80 min, there was no overall relation between this prehospital time measure and mortality.

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.

Patient and rescuer safety: recommendations for dispatch and prioritization of rescue resources based on a retrospective study of Norwegian avalanche incidents 1996-2017.

BACKGROUND: Avalanche emergency response should address current accident scenarios to optimize survival chances of victims and to keep rescuers safe. The purpose of this article is to present a basis for evaluation and necessary adjustments in dispatch, prioritization, and management of Norwegian avalanche rescue operations. METHODS: This is the first peer-reviewed retrospective study of all Norwegian avalanche incidents registered by the two Joint Rescue Co-ordination Centers (JRCCs) in the period 1996-2017 that describes the characteristics and trends of rescue missions and victims. RESULTS: The Norwegian JRCCs have registered 720 snow avalanche events, with a total of 568 avalanche victims, of which 120 (21%) died. Including those fatally injured, a total of 313 avalanche victims in 209 accidents were treated as patients (55%), and we saw > 1 patient in 24% of these operations. Norwegian avalanche victims were partially or completely recovered prior to the arrival of rescuers in 75% (n = 117) of all rescue operations. In the remaining 25% of cases, the rescue service located 62% (n = 55) of the avalanche victims visually or electronically. In 50% of the 720 incidents, rescuers spent time searching in avalanches with no victims. CONCLUSIONS: This survey indicates that we have experienced a shift in Norwegian avalanche rescue: from search for missing persons in the avalanche debris to immediate medical care of already-located patients. The findings suggest that a stronger focus on both patient and rescuer safety is necessary. The patients must be ensured the right treatment at the right place at the right time and the allocation of rescue resources must reflect a need to reduce exposure in avalanche terrain, especially in cases with no affirmed victims. We present a flowchart with a recommended rescue response to avalanche accidents in Norway.

Experiences among firefighters and police officers of responding to out-of-hospital cardiac arrest in a dual dispatch programme in Sweden: an interview study.

OBJECTIVES: The objective of this study was to explore firefighters' and police officers' experiences of responding to out-of-hospital cardiac arrest (OHCA) in a dual dispatch programme. DESIGN: A qualitative interview study with semi-structured, open-ended questions where critical incident technique (CIT) was used to collect recalled cardiac arrest situations from the participants' narratives. The interviews where transcribed verbatim and analysed with inductive content analysis. SETTING: The County of Stockholm, Sweden. PARTICIPANTS: Police officers (n=10) and firefighters (n=12) participating in a dual dispatch programme with emergency medical services in case of suspected OHCA of cardiac or non-cardiac origin. RESULTS: Analysis of 60 critical incidents was performed resulting in three consecutive time sequences (preparedness, managing the scene and the aftermath) with related categories, where first responders described the complexity of the cardiac arrest situation. Detailed information about the case and the location was crucial for the preparedness, and information deficits created stress, frustration and incorrect perceptions about the victim. The technical challenges of performing cardiopulmonary resuscitation and managing the airway was prominent and the need of regular team training and education in first aid was highlighted. CONCLUSIONS: Participating in dual dispatch in case of suspected OHCA was described as a complex technical and emotional process by first responders. Providing case discussions and opportunities to give, and receive feedback about the case is a main task for the leadership in the organisations to diminish stress among personnel and to improve future OHCA missions.

Survival analysis and classification methods for forest fire size.

Factors affecting wildland-fire size distribution include weather, fuels, and fire suppression activities. We present a novel application of survival analysis to quantify the effects of these factors on a sample of sizes of lightning-caused fires from Alberta, Canada. Two events were observed for each fire: the size at initial assessment (by the first fire fighters to arrive at the scene) and the size at "being held" (a state when no further increase in size is expected). We developed a statistical classifier to try to predict cases where there will be a growth in fire size (i.e., the size at "being held" exceeds the size at initial assessment). Logistic regression was preferred over two alternative classifiers, with covariates consistent with similar past analyses. We conducted survival analysis on the group of fires exhibiting a size increase. A screening process selected three covariates: an index of fire weather at the day the fire started, the fuel type burning at initial assessment, and a factor for the type and capabilities of the method of initial attack. The Cox proportional hazards model performed better than three accelerated failure time alternatives. Both fire weather and fuel type were highly significant, with effects consistent with known fire behaviour. The effects of initial attack method were not statistically significant, but did suggest a reverse causality that could arise if fire management agencies were to dispatch resources based on a-priori assessment of fire growth potentials. We discuss how a more sophisticated analysis of larger data sets could produce unbiased estimates of fire suppression effect under such circumstances.

Clinician tasking in ambulance control improves the identification of major trauma patients and pre-hospital critical care team tasking.

INTRODUCTION: Trauma remains the fourth leading cause of death in western countries and is the leading cause of death in the first four decades of life. NICE guidance in 2016 advocated the attendance of pre-hospital critical care trauma team (PHCCT) in the pre-hospital stage of the care of patients with major trauma. Previous publications support dispatch by clinicians who are also actively involved in the delivery of the PHCCT service; however there is a lack of objective outcome measures across the current reviewed evidence base. In this study, we aimed to assess the accuracy of PHCCT clinician led dispatch, when measured by Injury Severity Score (ISS). METHODS: A retrospective cohort study over a 2 year period pre and post implementation of a PHCCT clinician led dispatch of PHCCT for potential major trauma patients, using national ambulance data combined with national trauma registry data. RESULTS: A total of 99,702 trauma related calls were made to SAS including 495 major trauma patients with an ISS >15, and a total of 454 dispatches of a PHCCT. Following the introduction of a PHCCT clinician staffed trauma desk, the sensitivity for major trauma was increased from 11.3% to 25.9%. The difference in sensitivity between the pre and post trauma desk group was significant at 14.6% (95% CI 7.4%-21.4%, p < .001). DISCUSSION: The results from the study support the results from other studies recommending that a PHCCT clinician should be located in ambulance control to identify major trauma patients as early as possible and co-ordinate the response.