After the Haiti 2021 Earthquake: Triage and treatment data for a cohort of patients transported for higher level of care

Intro: On August 14, a magnitude 7.2 earthquake occurred in the South of Haiti, killing over 2,200 people and leaving at least 12,000 injured. On August 17th, a joint task force coordinated the triage, treatment, and transport for patients arriving at the Port-au-Prince airport from the South. Methods: From August 17th-27th, approximately 243 patients were encountered at the Port-au-Prince airport. For the first three days of operations, written notes, reports, and various chat logs from WhatsApp were used to compile this data. Results: 243 patents were encountered at the airport Triage and Treatment from August 17 to August 27. Orthopedic injuries were the most common presenting injury with 20% of patients having a pelvis fracture (the most prevalent injury). Of the 174 with known transfer destinations, 118 (68%) were transported to one of three tertiary care hospitals, with 99 going via ground ambulance to the two in Port au Prince, and 19 going via HAA helicopter to Mirebalais, 32 miles away. Once treatment operations were initiated, 106 patients received some form of treatment at the airport while awaiting transport. Discussion: Interagency coordination was the key to rapid scale up. To address the most prevalent patient issues, a treatment bundle was conceptualized a few days into operations that consisted of IV fluids, analgesia, IV antibiotics, wound debridement and cleaning, and tetanus prophylaxis.

Association between Mode of Transportation and Survival in Adult Trauma Patients with Blunt Injuries: Matched Cohort Study between Police and Ground Ambulance Transport

Introduction: Early police transport (PT) of penetrating trauma patients has the potential to improve survival rates for trauma patients. There are no well-established guidelines for the transport of blunt trauma patients by PT currently. Study Objective: This study examines the association between the survival rate of blunt trauma patients and the transport modality (police versus ground ambulance). Methods: A retrospective, matched cohort study was conducted using the National Trauma Data Bank (NTDB). All blunt trauma patients transported by police to trauma centers were identified and matched (one-to-four) to patients transported by ground Emergency Medical Services (EMS) for analysis. Descriptive analysis was carried out. This was followed by comparing all patients’ characteristics and their survival rates in terms of the mode of transportation. Results: Out of the 2,469 patients with blunt injuries, EMS transported 1,846 patients and police transported 623 patients. Most patients were 16-64 years of age (86.2%) with a male predominance (82.5%). Fall (38.4%) was the most common mechanism of injury with majority of injuries involving the head and neck body part (64.8%). Fractures were the most common nature of injury (62.1%). The overall survival rate of adult blunt trauma patients was similar for both methods of transportation (99.2%; P = 1.000). Conclusion: In this study, adult blunt trauma patients transported by police had similar outcomes to those transported by EMS. As such, PT in trauma should be encouraged and protocolized to improve resource utilization and outcomes further.

Effect of topography and weather on call to automatic electrical defibrillator attach time by drone for out-of-hospital cardiac arrest: a virtual flight simulation study

Background Delivery of automatic electrical defibrillator (AED) by unmanned aerial vehicle like drones was suggested to improve early defibrillation for out-of-hospital cardiac arrest. We developed a drone-AED flight virtual simulator using 3-dimensional topographic and meteorological information. The goal of this study is to assess the effect of topography and weather on call to AED attach time in drone-AED program. Methods We included patients from 2013 to 2016 in Seoul, South Korea, registered in the Korean out-of-hospital cardiac arrest registry. We developed a drone-AED flight simulation using topographic information of Seoul for Euclidean flight pathway and topographic flight pathway including vertical flight to overcome high-rise structures. We used 4 drone flight scenarios according to weather conditions or visibility: flight and control advanced drone, flight advanced drone, control advanced drone and basic drone. Primary outcome was emergency medical service call to AED attach time. Secondary outcome was success rate of call to AED attachment within 5 or 10 minutes, and pre-arrival rate of drone-AED before AED delivery by ground ambulance. Results 16,596 patients were included. Median flight time of drone-AED was 2.6 and 1.0 minute for topographic flight simulation and Euclidean pathway. Call to AED attach time in topographic pathway was 7.0 minutes in flight and control advanced drone and 8.0 minutes in basic drone. The time in Euclidean pathway was 6.5 minutes in flight and control advanced drone and 7.0 minutes in basic drone. Pre-arrival rate of drone-AED in Euclidean pathway was 38.0% and 16.3% for flight and control advanced drone and basic drone. whereas, pre-arrival rate in the topographic pathway was 27.0% and 11.7%, respectively. Conclusions Drone-AED took longer call to AED attach time in basic drone than flight and control advanced drone. Pre-arrival rate of flight and control advanced drone was decreased in topographic flight pathway compared to Euclidean pathway. Trial registration This study used cases retrospectively registered in the Korean out-of-hospital cardiac arrest registry.

Time-saving Effects Using Helicopter Transportation: Comparison to a Ground Transportation Time Predicted Using a Social Navigation Software

IntroductionPrevious comparison studies regarding two types of transportation, helicopter (HEMS) versus ground emergency medical services (GEMS), have shown underlying heterogeneity as these options have completely different routes and consequent times with reference to one patient. To compare the two types of transportation on a case-by-case basis, we analyzed the retrospectively reviewed HEMS and predicted GEMS data using an open-source navigation software.MethodsPatients transferred by military HEMS from 2016 to 2019 were retrospectively enrolled. The HEMS records on the time of notification, injury point and destination address, and time required were reviewed. The GEMS data on distance and the predicted time required were acquired using open-source social navigation systems. Comparison analyses between the two types of transportation were conducted. Further, linear logistic regression analyses were performed on the distance and time of the two options.ResultsA total of 183 patients were enrolled. There was no statistical difference (p=0.3021) in the distance between the two types of transportation, and the HEMS time was significantly shorter than that of GEMS (61.31 vs. 116.92 minutes, p<0.001). The simple linear curves for HEMS and GEMS were separately secured, and two graphs presented the statistical significance (p) as well as reasonable goodness-of-fit (R2). In general, the HEMS graph demonstrates a more gradual slope and narrow distribution compared to that of GEMS. ConclusionIdeally, HEMS is identified as a better transportation modality because it has a shorter transportation time (56 minutes saved) and a low possibility of potential time delays (larger R2).Running tileHelicopter vs. navigation-based ground ambulance

Dispatch of a helicopter emergency medicine service to patients with a sudden, unexplained loss of consciousness of medical origin

Background Sudden loss of consciousness (LOC) in the prehospital setting in the absence of cardiac arrest and seizure activity may be a challenge from a dispatcher’s perspective: The aetiology is varied, with many causes being transient and mostly self-limiting, whereas other causes are potentially life threatening. In this study we aim to evaluate the dispatch of HEMS to patients with LOC of medical origin, by exploring to which patients with a LOC HEMS is dispatched, which interventions HEMS teams perform in these patients, and whether HEMS interventions can be predicted by patient characteristics. Methods We performed retrospective cohort study of all patients with a reported unexplained LOC (e.g. not attributable to a circulatory arrest or seizures) attended by the Air Ambulance Kent, Surrey & Sussex (AAKSS), over a 4-year period (July 2013–December 2017). Primary outcome was defined as the number of HEMS-specific interventions performed in patients with unexplained LOC. Secondary outcome was the relation of clinical- and dispatch criteria with HEMS interventions being performed. Results During the study period, 127 patients with unexplained LOC were attended by HEMS. HEMS was dispatched directly to 25.2% of the patients, but mostly (74.8%) on request of the ground ambulance crews. HEMS interventions were performed in 65% of the patients (Prehospital Emergency Anaesthesia 56%, hyperosmolar therapy 21%, antibiotic/antiviral therapy 8%, vasopressor therapy 6%) and HEMS conveyed most patients (77%) to hospital. Acute neurological pathology was a prevalent underlying cause of unexplained LOC: 38% had gross pathology on their CT-scan upon arrival in hospital. Both GCS (r = − 0.60, p < .001) and SBP (r = 0.31, p < .001) were related to HEMS interventions being performed on scene. A GCS < 13 predicted the need for HEMS interventions in our population with a sensitivity of 94.9% and a specificity 75% (AUC 0.85). Conclusion HEMS dispatchers and ambulance personnel are able to identify a cohort of patients with unexplained LOC of medical origin who suffer from potentially life threatening (mainly neurological) pathology, in whom HEMS specific intervention are frequently required. Presenting GCS can be used to inform the triage process of patients with LOC at an early stage.

Air and ground ambulance location-allocation-routing problem for designing a temporary emergency management system after a disaster

Disasters cause a huge number of injured patients in a short time while existing emergency facilities encountered devastation and cannot respond properly. Here, the importance of implementing temporary emergency management becomes clear. This study aims to locate some temporary emergency stations across the area by maximal covering after a disaster. Furthermore, a multi-mode fleet is used for transferring patients using different modes of transportation (e.g. helicopter ambulance and bus ambulance). Since the type of patients may change over periods, medical servers can displace among temporary emergency stations dynamically according to disaster severity. For this purpose, a new bi-objective dynamic location-helicopter ambulance allocation-ambulance routing model with multi-medical servers is presented. The first objective function minimizes the operational costs related to the newly designed Emergency Medical Service along with the rate of human loss. The second objective function minimizes the critical time spent before the medical treatment. To validate the developed model, the augmented ε-constraint method is used and applied for the Tehran city, which shows the applicability of the model. Finally, two meta-heuristic algorithms are customized for large-sized problems, and the related results are compared based on multi-objective algorithms’ performance comparison metrics to find the more efficient one.