Mass Casualty Incident Triage Research Articles

The Use of Smartphone-Based Highly Realistic MCI Training as an Adjunct to Traditional Training Methods.

Training for mass casualty incident (MCI) response is critical to ensure that resource allocation and treatment priorities limit preventable mortality. Previous research has investigated the use of immersive virtual environments as an alternative to high fidelity MCI training, which is expensive and logistically challenging to implement. While these have demonstrated positive early results, they still require complex technology deployment, dedicated training facilities, and significant time from instructors and facilitators. This study explores the feasibility of a smartphone-based application for trauma care training and MCI triage to fill the gap between classroom learning and high-fidelity simulation. The goals of this investigation were to evaluate clinician perceptions of a virtual MCI training simulator's usability, acceptability, fidelity, functionality, and pacing. This study used a smartphone-based training simulation called Extensible Field and Evacuation Care Training in a Virtual Environment (EFECTIVE), which presents virtual patient scenarios in a gamified, but visually high-fidelity environment. A total of 21 participants were recruited as a convenience sample of medical students, paramedics, nurses, and emergency medicine resident and attending physicians at University of Massachusetts Memorial Medical Center, an urban tertiary care medical center. Participants completed a brief tutorial and then performed a series of virtual patient scenarios and 1 MCI scenario on the simulator, each of which was 5 minutes in duration. Then, each participant completed a survey assessing the perceived usability, acceptability, fidelity, functionality, and pacing of the virtual training simulator. The research protocol was approved by the University of Massachusetts Chan Medical School Institutional Review Board. 48% of participants disagreed that a virtual simulator could completely replace live MCI training, though 71% agreed that app-based simulations could effectively supplement live MCI training and 67% felt that they could be used to learn how to order medical interventions in care under fire scenarios. 80% of participants agreed that the simulation could be used to practice MCI triage and to gain experience with coordinating movement of casualties to casualty collection points. 67% of participants believed that use of virtual simulators would increase their MCI preparedness. 76% agreed that the clinical cases depicted were medically realistic and that the clinical cases presented accurately represented the scenarios described. In addition, despite being presented on a smartphone as opposed to virtual reality, 62% of participants rated the experience immersive. This study provides encouraging evidence that easy to deploy smartphone-based simulations may be an effective way to supplement MCI and care under fire training. Although the study is limited by a small sample size, there was strong agreement among participants from a wide variety of emergency medicine roles that such a simulation could train core topics associated with MCI triage. Because app-based simulations are easily deployable and can be executed quickly and frequently, they could be used as a more flexible training model compared to large scale live or virtual reality-based simulations. The results of this investigation also indicate that a sufficient level of medical realism can be achieved without live simulation.

Utilization of an Asynchronous Online Learning Module Followed by Simulated Scenario to Train Emergency Medicine Residents in Mass-Casualty Triage.

This is a combined independent study and simulation session designed to teach and drill Mass Casualty Incident (MCI) Triage and is intended for emergency medicine residents at all levels. The training of emergency medicine residents to assume leadership roles in disaster response is important. However, lack of accepted specific educational goals on the national level leads to significant variability between residencies. The purpose of this session is to train EM residents in the use of the Simple Triage and Rapid Treatment (START) and pediatric JumpSTART algorithms for triage in mass casualty incidents (MCIs) using an asynchronous model. By the end of this small group session, learners will be able to: 1) describe START triage for adult MCI victims; 2) describe JumpSTART triage for pediatric MCI victims; 3) demonstrate the ability to apply the START and JumpSTART triage algorithms in a self-directed learning environment; 4) demonstrate the ability to apply the START and JumpSTART triage algorithms in a simulated mass casualty scenario under time constraints; and 5) demonstrate appropriate use of acute life-saving interventions as dictated by the START and JumpSTART triage algorithms in a high-pressure simulated environment. This session utilizes an online independent study module that was created de novo for this specific purpose by the authors followed by a high-pressure in-person simulation session where learners practice applying the START triage model with multiple simulated patients under time constraint. Learner feedback was collected after completion of the session. Retention of learning objectives was tested at four months via multiple-choice quiz. The session was very well received by our residents, who appreciated the opportunity to practice applying START triage under pressure. The average score on the pretest was 49%. Response rates to the post-test were low, but residents scored an average of 73%, indicating a trend towards retention of learning objectives. Overall, the utilization of a de novo online learning module followed by simulation proved to be a well-received method of teaching MCI triage to emergency medicine residents. We consider this to be an effective way to train MCI Triage with minimal in-conference time utilization. We plan to implement this training annually to provide our residents with longitudinal reinforcement of this vital skill. Mass casualty, MCI, triage, START triage, JumpSTART Triage, disaster, disaster preparedness, disaster curriculum, prehospital, EMS.

Implementation of a workshop for mass casualty incident triage training using an immersive virtual reality simulation.

We offered a workshop at the 2023 annual meeting of the Society for Academic Emergency Medicine to teach the Sort-Assess-Lifesaving Interventions-Treatment/Transport (SALT) triage protocol for responding to mass casualty incidents (MCIs) using an immersive virtual reality (VR) simulator. Here, we report workshop outcomes. After a 1-h didactic on the basics of triage protocols, workshop participants rotated through three skill stations at which learners learned how to use the VR headset and controllers, practiced applying SALT triage skills through a tabletop exercise, and then finally used our VR simulator for training responses to MCIs. During their encounter with VR, participants applied their new knowledge to triaging and treating the victims of an explosion in a virtual subway station. After a brief orientation, participants entered the scene to treat and triage virtual patients who had various life-threatening (e.g., acute arterial bleed, penetrating injury, pneumothorax, amputations) and non-life-threatening injuries (lacerations, sprains, hysteria, confusion). The simulator generated a performance report for each workshop attendee to be used for debriefing by a skilled facilitator. Participants were mostly trainees (residents), all of whom properly initiated their encounter with global sort commands (walk and wave) to identify the most critically injured. On average, participants correctly treated 92% of 18 injuries, with all bleeding injuries being properly controlled (tourniquets or wound packing). On average, participants correctly tagged 87.7% of 11 patients, but only took the pulse of 67% of the 11 patients. Learners had difficulty with cases involving embedded shrapnel and properly tagging patients who were stable after treatments. Our VR simulator provided a practical, portable, reproducible training and assessment system for preparing future emergency medical systems (EMS) medical directors to teach their EMS professionals the triage and lifesaving intervention treatment skills needed to save lives.

Prehospital mass casualty incident triage simulation builds knowledge and confidence in medical trainees.

Mass casualty incident (MCI) triage simulation is an increasingly useful tool for teaching triage systems to medical students, trainees, and hospital staff. MCI simulation in the prehospital setting has not yet been studied in this population. We aimed to assess the effectiveness of a prehospital MCI simulation in medical students, residents, and fellows. Our primary outcome was knowledge of the components of the triage algorithms used in MCI response. Our secondary outcome was each participant's confidence level if required to assist with or lead a MCI response. This was an observational study with pre-post surveys. We recruited 30 medical students, 14 emergency medicine (EM) residents, and four pediatric EM fellows to fill out a survey before and after a 3-h simulation session practicing the START and JumpSTART algorithms on two prehospital MCI scenarios. Overall, all groups demonstrated significant improvement in knowledge of triage colors, information needed to assign a triage color, pediatric airway management during a MCI, and indications for breaths-first CPR. They also demonstrated significant increase in confidence both in assisting with and in leading a MCI response. Simulated practice triaging patients in prehospital MCI scenarios improves knowledge of triage algorithms and increases confidence in assisting with or leading a MCI response in medical trainees.

ChatGPT's performance before and after teaching in mass casualty incident triage

Since its initial launching, ChatGPT has gained significant attention from the media, with many claiming that ChatGPT’s arrival is a transformative milestone in the advancement of the AI revolution. Our aim was to assess the performance of ChatGPT before and after teaching the triage of mass casualty incidents by utilizing a validated questionnaire specifically designed for such scenarios. In addition, we compared the triage performance between ChatGPT and medical students. Our cross-sectional study employed a mixed-methods analysis to assess the performance of ChatGPT in mass casualty incident triage, pre- and post-teaching of Simple Triage And Rapid Treatment (START) triage. After teaching the START triage algorithm, ChatGPT scored an overall triage accuracy of 80%, with only 20% of cases being over-triaged. The mean accuracy of medical students on the same questionnaire yielded 64.3%. Qualitative analysis on pre-determined themes on ‘walking-wounded’, ‘respiration’, ‘perfusion’, and ‘mental status’ on ChatGPT showed similar performance in pre- and post-teaching of START triage. Additional themes on ‘disclaimer’, ‘prediction’, ‘management plan’, and ‘assumption’ were identified during the thematic analysis. ChatGPT exhibited promising results in effectively responding to mass casualty incident questionnaires. Nevertheless, additional research is necessary to ensure its safety and efficacy before clinical implementation.

Performance of Google bard and ChatGPT in mass casualty incidents triage

AimThe objective of our research is to evaluate and compare the performance of ChatGPT, Google Bard, and medical students in performing START triage during mass casualty situations. MethodWe conducted a cross-sectional analysis to compare ChatGPT, Google Bard, and medical students in mass casualty incident (MCI) triage using the Simple Triage And Rapid Treatment (START) method. A validated questionnaire with 15 diverse MCI scenarios was used to assess triage accuracy and content analysis in four categories: “Walking wounded,” “Respiration,” “Perfusion,” and “Mental Status.” Statistical analysis compared the results. ResultGoogle Bard demonstrated a notably higher accuracy of 60%, while ChatGPT achieved an accuracy of 26.67% (p = 0.002). Comparatively, medical students performed at an accuracy rate of 64.3% in a previous study. However, there was no significant difference observed between Google Bard and medical students (p = 0.211). Qualitative content analysis of ‘walking-wounded’, ‘respiration’, ‘perfusion’, and ‘mental status’ indicated that Google Bard outperformed ChatGPT. ConclusionGoogle Bard was found to be superior to ChatGPT in correctly performing mass casualty incident triage. Google Bard achieved an accuracy of 60%, while chatGPT only achieved an accuracy of 26.67%. This difference was statistically significant (p = 0.002).

Development and validation of SALT Triage method to facilitate the identification and classification of patients in Mass Casualty Incidents.

Mass Casualty Incidents (MCIs) have caused great financial losses. These incidents are referred to a situation in which the number of casualties caused by the accident temporarily increases to such an extent that it is not possible to treat all these patients with the facilities and capacities available in the area. To offer fair and proportionate medical services to all patients, it is necessary to use a process called patient triage. This study aimed to modify the Sort Assess Lifesaving Intervention Treatment/transport (SALT) triage method to simplify the differentiation of patients from green from yellow and gray from red. This is a methodological study with a descriptive cross-sectional approach that by studying the SALT triage method and using the criteria defined in the Reference Standard, facilitates the identification of patients with a minor (Outpatient) and fatal injury (Expectant). Then, using two common and modified SALT triage methods, 100 simulated patients were triaged and the obtained data were evaluated and compared in terms of accuracy and speed. The improvement made in the SALT triage method was able to reduce 22% of the total triage error of the first nurse and improved 18% in green, 43% in yellow, 15% in red, and 13% in the gray category. In the second nurse, this method was able to reduce 29% of the errors and in the category of green patients, 41%, yellow 47%, red was unchanged, and gray 38% improvement was observed. Furthermore, the average triage rate was 4 and 5 seconds shorter per patient in the first and second nurses, respectively. With this modification, the diagnostic power has increased by 22% in the first nurse and 29% in the second nurse. Due to the significant increase in the accuracy of the mSALT (Modified SALT) triage method, this modification can be considered useful and can be used to advance the goals of triage in MCIs.

COMPARISON OF START AND SALT TRIAGE SYSTEM IN MASS CASUALTY INCIDENTS: A STUDY OF ON-SITE TRAINING

Background: Mass casualty incident triage is essential in determining the priority of care for patients to maximize the number of survivors. This study aimed to evaluate the effectiveness of two different triage systems, SALT and START, in a simulated mass casualty event. Methods: participants were recruited and randomized into three groups: SALT-trained, START-trained, and untrained control. Participants performed triage on simulated patients pre- and post-training. Data was collected before and after implementing a training program that consist of a brief lecture and open discussion of 10 minutes for each triage system, and it was conducted in a group format. Results: A total of 60 participants were included in our analysis. The results showed that both SALT and START training significantly improved triage accuracy compared to the untrained control group. However, there was no significant difference in accuracy between the SALT and START groups. Additionally, both groups showed significant improvements in triage time post-training. Conclusion: These findings suggest that both SALT and START are effective triage systems in a simulated mass casualty event and highlight the importance of proper training for accurate and efficient triage.

An assessment of mass casualty triage systems using the Alberta trauma registry.

Triage is the process of identifying patients with both the greatest clinical need and the greatest likelihood of benefit in the setting of limited clinical resources. The primary objective of this study was to assess the ability of formal mass casualty incident triage tools to identify patients requiring urgent lifesaving interventions. Data from the Alberta Trauma Registry (ATR) was used to assess seven triage tools: START, JumpSTART, SALT, RAMP, MPTT, BCDand MITT. Clinical data captured in the ATR was used to determine which triage category each of the seven tools would have applied to each patient. These categorizations were compared to a reference standard definition based on the patients' need for specific urgent lifesaving interventions. Of the 9448 records that were captured 8652 were included in our analysis. The most sensitive triage tool was MPTT, which demonstrated a sensitivity of 0.76 (0.75, 0.78). Four of the seven triage tools evaluated had sensitivities below 0.45. JumpSTART had the lowest sensitivity and the highest under-triage rate for pediatric patients. All the triage tools evaluated had a moderate to high positive predictive value (> 0.67) for patients who had experienced penetrating trauma. There was a wide range in the sensitivity of triage tools to identify patients requiring urgent lifesaving interventions. MPTT, BCD and MITT were the most sensitive triage tools assessed. All of the triage tools assessed should be employed with caution during mass casualty incidents as they may fail to identify a large proportion of patients requiring urgent lifesaving interventions.

The Advancement of the Scientific Study of Prehospital MCI Response from TIIDE to NIGHTINGALE: A Scoping Review

Introduction:The European Union Horizon 2020 research and innovation funding program awarded the NIGHTINGALE grant to develop a toolkit to support first responders engaged in prehospital (PH) mass casualty incident (MCI) response. To reach the projects’ objectives, the NIGHTINGALE consortium adapted the Translational Science (TS) process. The aim of this study is to perform the first TS (T1) phase PRISMA scoping review to extract data that will be used to guide the creation of the initial evidence-based second TS phase (T2) modified Delphi statements for a subsequent study.Method:The consortium was divided into three work groups (WGs) MCI triage, Prehospital Life Support and Damage Control (PHLSDC) and Prehospital Processes (PHP). Each WG conducted simultaneous literature searches following the PRISMA extension for scoping review with a common research strategy sharing MCI related search terms and then terms specific for each WG. Final included articles went through data extraction based on identified themes and sub-themes from PH MCI response literature to be used to create the future statements.Results:The initial search yielded 925 total references to be considered for a title and abstract review (PH Triage 311, PHLSDC 329, PHP 285), then 483 articles for a full reference review (MCI Triage 111, PHLSDC 216, PHP 156) and 155 articles for the database extraction process (MCI Triage 27, PHLSDC 38, PHP 90).Conclusion:The progression of the study of prehospital MCI response enabled NIGHTINGALE partners to methodically obtain information that will contribute to each WG’s creation of initial T2 modified Delphi statements.

A Modified Delphi Study to Improve Prehospital Mass Casualty Incident Response

Introduction:The Novel Integrated Toolkit for Enhanced Pre-Hospital Life Support and Triage in Challenging and Large Emergencies (NIGHTINGALE) project was awarded to a consortium to design an innovative toolkit featuring different technological solutions for prehospital mass casualty incident (MCI) response. Translational science (T) methodology was undertaken to develop evidence-based guidelines for MCI response.Method:The consortium was divided into three work groups (WGs) MCI Triage, Prehospital Life Support and Damage Control and Prehospital Processes. Each WG previously collected data through the project T1 scoping review stage to provide the foundation for the initial T2 modified Delphi draft statements to present to WG internal focus groups for content and NIGHTINGALE study objectives. Their refined statements proceeded to WG specific external focus groups for further editing to be clear and concise for the following modified Delphi consensus rounds. Final WG statements were presented to modified Delphi experts for their consensus using the STAT59 platform with instruction to rank each statement on a seven-point linear numeric scale, where 1 = disagree and 7 = agree. Consensus amongst experts was defined as a standard deviation ≤1.0.Results:After three modified Delphi rounds, 18 of 24 statements attained consensus by the MCI Triage experts, eight of 25 by the Prehospital and Life Support and Damage Control experts, and 23 of 28 by the Prehospital Processes experts.Conclusion:The three work groups will utilize consensus statements during the NIGHTINGALE project T3 phase to create evidence-based MCI response guidelines.

Triage Accuracy Rates Using the New MCI Triage System of Regione Piemonte: What’s New?

Introduction:An adequate Mass-Casualty Incident (MCI) triage system is essential to provide the best possible health care to the greatest number of affected people and to optimize the management of the available resources in the context of a MCI.Method:In February 2022, Disaster Medicine Service 118 of Regione Piemonte adopted a new 5-color code-MCI triage system and Emergency Medical System (EMS) personnel was trained through a 3-hours-distance learning course. 515 medical doctors and nurses attended the course and completed the final test (triaging of 50 computer-based simulated patients/cases). Their performance was compared to intended triage designations. We collected the data and conducted a descriptive observational study.Results:A total of 25.750 evaluations were carried out: 1.030 white cases, 6.180 green cases, 6.180 yellow cases, 9.270 red cases and 3,090 black cases. Overall triage accuracy was 89,63%. The overall errors were 2.671 (10.37%). Concerning the type of error, there were 1.415 cases under-triaged (5.5%) and 1.256 cases over- triaged (4.88%). Based on color-code, the highest rate of error was in green cases (3.48%), while black patients showed the highest accuracy rate (0.32%). Based on type, the most frequent error was under-triage of red patients, while the less frequent was over-triage of black patients.Conclusion:The results of the final test performed by EMS personnel showed the accuracy rates of triage using new 5-color code-MCI triage systems of Regione Piemonte to be in range with data reported in the literature. A study limitation is the fact that the data analyzed are derived from online testing performed in no-time limited and no-stress conditions. Another potential limitation is the distance learning which doesn’t allow a discussion with the teacher or a request for clarification. For this reason, we would plan a future study defining the efficacy of the didactic methodology in comparison with face-to-face courses.

A Scoping Review of Pediatric Mass-Casualty Incident Triage Algorithms.

For the pediatric population, there is no consensus on which triage system to use for mass-casualty incidents (MCI). A scoping review was conducted to identify the most accurate triage system for pediatric patients in MCIs. MEDLINE (NLM, Bethesda, MA, USA), Embase (Elsevier Inc., Amsterdam, Netherlands), CINAHL (EBSCO Information Services, Ipswitch, MA, USA), and The Cochrane CENTRAL Register of Controlled Trials (John Wiley & Sons, Hoboken, NJ, USA), as well as Scopus (Elsevier Inc., Amsterdam, Netherlands), Global Health (Centre for Agriculture and Bioscience International, Wallingford, UK), Global Health Archive (Centre for Agriculture and Bioscience International, Wallingford, UK), and Global Index Medicus (World Health Organization, Geneva, Switzerland) were searched for relevant studies that were divided into 3 categories: accuracy of a single system, comparison of 2 or more primary triage system and comparison of secondary triage systems. Grey literature was also searched. 996 studies were identified from which 18 studies were included. Systems studied were found to have poor inter-rater reliability, had a low level of agreement between providers, had missed critically ill patients or were not externally validated. 11 studies compared pediatric MCI triage algorithms using different strategies and the most accurate algorithm was not identified. A recently developed secondary triage system, specifically for pediatric patients, was found to perform better than the comparison triage system. Although some algorithms performed better than others, no primary triage algorithm was accurate enough for the pediatric population. However, only 1 secondary triage algorithm was found to be superior to the others.

Factors affecting nursing students\u2019 intention to use a 3D game to learn field triage skills: a structural equation modelling analysis

BackgroundAs mass casualty incidents are low-probability events, students often do not have the chance to practise field triage skills during their clinical placement. This study used a 3D game to engage participants in experiential learning in a realistic virtual environment. The purpose of the study was to explore factors affecting nursing students’ intention to use a 3D game to learn field triage skills.MethodsThis was a cross-sectional survey study. The technology acceptance model augmented by computer self-efficacy was used as a research model and a questionnaire was used to evaluate students’ intention to use the 3D game to learn field triage. Data was collected from nursing students of a degree-awarding higher education institution in Hong Kong.ResultsA total of 177 valid questionnaires were returned, and structural equation modeling was used to test the research model and hypotheses. Consistent with the technology acceptance model, perceived usefulness (0.21, p < 0.05) and perceived ease of use (0.91, p < 0.001) had a positive effect on the behavioral intention to use the 3D game. Computer self-efficacy positively influenced both perceived usefulness (0.66, p < 0.001) and perceived ease of use (0.73, p < 0.001). The research model explained 42 percent of the variance in the behavioral intention to use the 3D game.ConclusionStudents believed that using the 3D game would enhance their field triage skills and found the game easy to use. Using 3D games to facilitate learning is a worthwhile educational approach for preparing healthcare professionals to handle low-probability clinical tasks, such as field triage in mass casualty incidents. Insights provided by findings of this study included the best way to design and promote interactive education programmes in a virtual environment.

Comparison of Outcome Tools Used to Test Mass-Casualty Algorithms in the Pediatric Population.

Mass-casualty incident (MCI) algorithms are used to sort large numbers of patients rapidly into four basic categories based on severity. To date, there is no consensus on the best method to test the accuracy of an MCI algorithm in the pediatric population, nor on the agreement between different tools designed for this purpose. This study is to compare agreement between the Criteria Outcomes Tool (COT) to previously published outcomes tools in assessing the triage category applied to a simulated set of pediatric MCI patients. An MCI triage category (black, red, yellow, and green) was applied to patients from a pre-collected retrospective cohort of pediatric patients under 14 years of age brought in as a trauma activation to a Level I trauma center from July 2010 through November 2013 using each of the following outcome measures: COT, modified Baxt score, modified Baxt combined with mortality and/or length-of-stay (LOS), ambulatory status, mortality alone, and Injury Severity Score (ISS). Descriptive statistics were applied to determine agreement between tools. A total of 247 patients were included, ranging from 25 days to 13 years of age. The outcome of mortality had 100% agreement with the COT black. The "modified Baxt positive and alive" outcome had the highest agreement with COT red (65%). All yellow outcomes had 47%-53% agreement with COT yellow. "Modified Baxt negative and <24 hours LOS" had the highest agreement with the COT green at 89%. Assessment of algorithms for triaging pediatric MCI patients is complicated by the lack of a gold standard outcome tool and variability between existing measures.

Prehospital Disaster Triage Does Not Predict Pediatric Outcomes: Comparing the Criteria Outcomes Tool to Three Mass-Casualty Incident Triage Algorithms.

It remains unclear which mass-casualty incident (MCI) triage tool best predicts outcomes for child disaster victims. The primary objective of this study was to compare triage outcomes of Simple Triage and Rapid Treatment (START), modified START, and CareFlight in pediatric patients to an outcomes-based gold standard using the Criteria Outcomes Tool (COT). The secondary outcomes were sensitivity, specificity, under-triage, over-triage, and overall accuracy at each level for each MCI triage algorithm. Singleton trauma patients under 16 years of age with complete prehospital, emergency department (ED), and in-patient data were identified in the 2007-2009 National Trauma Data Bank (NTDB). The COT outcomes and procedures were translated into ICD-9 procedure codes with added timing criteria. Gold standard triage levels were assigned using the COT based on outcomes, including mortality, injury type, admission to the hospital, and surgical procedures. Comparison triage levels were determined based on algorithmic depictions of the three MCI triage tools. A total of 31,093 patients with complete data were identified from the NTDB. The COT was applied to these patients, and the breakdown of gold standard triage levels, based on their actual clinical outcomes, was: 17,333 (55.7%) GREEN; 11,587 (37.3%) YELLOW; 1,572 (5.1%) RED; and 601 (1.9%) BLACK. CareFlight had the best sensitivity for predicting COT outcomes for BLACK (83% [95% confidence interval, 80%-86%]) and GREEN patients (79% [95% CI, 79%-80%]) and the best specificity for RED patients (89% [95% CI, 89%-90%]). Among three prehospital MCI triage tools, CareFlight had the best performance for correlating with outcomes in the COT. Overall, none of three tools had good test characteristics for predicting pediatric patient needs for surgical procedures or hospital admission.

Development of the Aerial Remote Triage System using drones in mass casualty scenarios: A survey of international experts.

The use of drones for triage in mass-casualty incidents has recently emerged as a promising technology. However, there is no triage system specifically adapted to a remote usage. Our study aimed to develop a remote triage procedure using drones. The research was performed in three stages: literature review, the development of a remote triage algorithm using drones and evaluation of the algorithm by experts. Qualitative synthesis and the calculation of content validity ratios were done to achieve the Aerial Remote Triage System. This algorithm assesses (in this order): major bleeding, walking, consciousness and signs of life; and then classify the injured people into several priority categories: priority 1 (red), priority 2 (yellow), priority 3 (green) and priority * (violet). It includes the possibility to indicate save-living interventions to injured people and bystanders, like the compression of bleeding injuries or the adoption of the recovery position. The Aerial Remote Triage System may be a useful way to perform triage by drone in complex emergencies when it is difficult to access to the scene due to physical, chemical or biological risks.

Simulated Mass Casualty Incident Triage Exercise for Training Medical Personnel.

The target audience is any medical professional who requires training in mass casualty incident (MCI) triage. This could apply to pre-hospital specialists, nurses, medical students, residents, and physicians. Emergency medicine specialists must be able to triage patients quickly, especially in an MCI scenario. The simple triage and rapid treatment (START) system allows providers to categorize patients according to the urgency with which patients must access limited resources. Providers should be comfortable utilizing the START triage system before an MCI or disaster so that they can be prepared to implement it if necessary. This exercise uses simulation and gamification as instructional strategies to encourage knowledge of and comfort with the START triage system for emergency providers. By the end of this exercise, learners should be able to (1) recite the basic START patient categories (2) discuss the physical exam signs associated with each START category, (3) assign roles to medical providers in a mass casualty scenario, (4) accurately categorize patients into triage categories: green, yellow, red, and black, and (5) manage limited resources when demand exceeds availability. Gamification is the use of elements of game design in non-game contexts.1 Gamification was implemented in this scenario by assigning participants to roles and teams, while creating an engaging, fun, and competitive environment. The exercise also uses low fidelity simulation (without simulation equipment) to encourage learners to practice using the START triage system in a low stakes environment.2 It is possible for the learners to be divided into two groups that each have the same patients, resources, and objectives. The team that finishes triaging all patients first would be declared the winner. However, in our implementation, we completed the exercise as a single group of learners and patients. Learners were given a survey at the end of implementation and also given the opportunity to discuss feedback with the instructors in a group discussion after completing the exercise. There was no formal assessment completed after the exercise. Informal feedback was collected at the end of the exercise. Residents and medical students all enjoyed the experience. The feedback was overwhelmingly positive. All participants providing feedback stated they would enjoy participating in the exercise again and suggested that it is implemented annually for review of triage topics. We also received informal feedback for suggested changes which we will discuss in this article. An optional, anonymous survey was given to participants at the end of the exercise. There were six responses. Of those surveyed, 100% of participants stated the effectiveness and value of the exercise was outstanding (a rating of five on a scale of one to five). Regarding the quality of the exercise, and whether the participants felt engaged, 100% of responses gave a rating of five. When asked to consider the relevance of the session, 100% of participants selected a score of five ("I loved this session"). Regarding whether the content was applicable to practice of emergency medicine, 80% of respondents stated the session was highly relevant and 20% of responses selected a score of mostly relevant. One question asked for points of improvement for the session to which there were no responses. Learners were assigned roles in the exercise by the incident commander, fulfilling objective three. The START categories were discussed at the beginning of the exercise by the lead proctor (using PowerPoint) and then utilized throughout the exercise, thus accomplishing objectives one and two. The residents/students filling the triage roles were primarily responsible for fulfilling objective four; however, all participants assisted in categorization of patients throughout the exercise. Finally, objective five was addressed through the various social situations and complications that can be implemented during the exercise. We chose not to implement the additional "radiation contamination" scenario (details available in the article text) due to time constraints; however, this is an additional option to address objective five. The implementation was effective based on informal feedback from participants and proctors as well as evidenced by the responses to the anonymous survey. Learners found the aspects of resource management, review of START triage, repetition of the START triage system, and medical management of various types of trauma informative and meaningful. We received valuable feedback from both learners and proctors, which we will discuss in this article. Mass casualty incident, disaster, START, gamification, simulation, emergency medicine, triage, triage category, contamination, teamwork, trauma, projectile trauma, penetrating injury, blunt trauma, intracranial hemorrhage, fracture, trauma in pregnancy, active shooter, radiation, radio communication.

Evaluating preparedness of emergency trainees to triage victims of mass casualty incidents

Background: Triage of victims in mass casualty incidents (MCI) is crucial in prioritizing care and allocating resources. Triage skills are important to be evaluated for training and better preparedness. Using clinical vignettes is a well-known approach to evaluate clinicians’ knowledge and decision-making. This study aims to evaluate preparedness of emergency residents and fellows to triage victims of MCI. Methods: Emergency Medicine (EM) residents and fellows at Hamad General Hospital, Emergency Department (HGH-ED) were invited to the study. Each participant filled a questionnaire followed by triaging of 15 vignette-based victims of MCI. Descriptive statistics elaborated on participants’ training and relevant exposures (). It also showed the degree of agreement in their triage results and rates of under-triage and over-triage. Cohen's kappa coefficient showed inter-rater agreement and internal consistency in triage results. Results: Participants included 63 emergency trainees, 27 residents, and 36 fellows. Only 28.3% (n = 17) of them participated in an MCI drill over the past two years. 51.7% (n = 31) attended training on triage in MCI. 73.3% (n = 44) indicated that they have rarely or never triaged victims in a real MCI or a drill. Only 3.3% (n = 2) perceived themselves as highly confident in triaging victims of MCI. A total of 904 triage outcomes resulted from this exercise (). The overall rate of agreement among the triage outcomes is 73% (660 times in 904 triage outcomes). The rate of over-triage was 36.8% and 23% under-triage. Conclusion: Better triage results was associated with previous triage training. The rate of over-triage was as the literature recommends. However, the rate of under triage was alarmingly higher than the literature recommendation as &lt; 5%. The higher rate of under-triage imposes a risk of missing seriously injured victims, which may lead to higher mortality or poor patients’ outcomes. Further training and exercises may be the key to saving more lives and resources.

Simple Emergency Triage (SET) – the new perspective on mass casualty incident triage

The aim: Incidents with large number of casualties present a major challenge for the emergency services. Incident witnesses are always the first on scene. Authors aim at giving them an algorithm arranging the widely known first aid rules in such way, that the number of potential fatalities before the services’ arrival may be decreased. Material and methods: The authors’ main aim was creating an algorithm for mass casualty incident action, comprising elements not exceeding first aid skill level. Proceedings have been systematized, which led to creation of mass casualty incident algorithm. The analysis was based on the subject matter literature, legal acts and regulations, statistical data and author’s personal experience. Results: The analysis and synthesis of data from various sources allowed for the creation of Simple Emergency Triage (SET) algorithm. It has been proven – on theoretical level – that introducing an organized way of proceeding in mass casualty incident on the first aid level is justified. Conclusions: The SET algorithm presented in the article is of an implemental character. It may be a supplement to basic first aid skills. Algorithm may also be the starting point for further empirical research aimed at verifying its effectiveness.