In the field of medicine, various advanced technologies such as artificial medicine (AI), telemedicine, and robotics are increasingly being adopted. However, their implementation in disaster medicine remains limited.

This scoping review aims to explore how these technologies have been studied and how they might be implemented by Emergency Medical Teams (EMTs) and Emergency Medical Team Coordination Cells (EMTCCs).

The review was conducted following the PRISMA-ScR guidelines. Peer-reviewed articles published between 2014 and 2024 were identified in MEDLINE using keywords related to disasters and advanced technologies. From these, articles relevant to the missions of EMTs and EMTCCs were selected.

A total of 670 studies were identified, and 15 were selected for analysis. The majority of studies focused on mental health (n = 7), triage (n = 3), and decision-making (n = 3). Research targeting pediatric (n = 2) and elderly (n = 1) populations was also found. Advanced technologies utilized included AI (n = 12), telemedicine (n = 3), and robotics (n = 3). The studies originated from the United States (n = 7), China (n = 3), and Japan (n = 2). A significant portion of the research was concerned with predicting outcomes for high-risk patients, assisting in medical care in the absence of specialized personnel, and facilitating remote medical consultations.

These technologies have the potential to enhance the efficiency of medical support, expedite information sharing, and improve safety at disaster sites when employed by EMTs and EMTCCs.

Unmanned Aircraft Systems (UAS) are transforming various sectors, including logistics and healthcare. This paper investigates the potential of UAS for enhancing emergency medical response by facilitating real-time management, swift medical supply delivery, and efficient resupply systems for mass casualty and point-of-injury scenarios.

The primary goal is to evaluate how UAS can improve the response times, operational efficiency, and effectiveness of Emergency Medical Teams (EMTs) during crises. The paper also aims to address the integration of UAS into existing emergency frameworks and regulatory, technical, operational, and logistical challenges involved.

The study explores UAS’s capabilities in real-time surveillance, reconnaissance, and Command and Control (C2) to support EMT decision-making. It covers the delivery of pharmaceuticals, medical equipment, vaccines, and telemedicine support. Additionally, it reviews the integration of UAS into current emergency response systems, focusing on compliance with aviation regulations, development of operational procedures, and necessary training and infrastructure.

UAS have shown promise in enhancing EMT operational efficiency, particularly in hostile and hard-to-reach areas. Case studies, including the UN Support Office in Somalia (UNSOS) pilot project, demonstrate UAS’s practical applications in medical logistics, public health, disaster relief, and telemedicine. Key performance indicators are established to measure the success of UAS implementations.

The innovative use of UAS in emergency medical interventions marks a significant advancement in healthcare delivery. By improving speed, efficiency, and accessibility, UAS can revolutionize emergency medical responses, particularly in isolated and challenging environments. As UAS technology evolves, its role in emergency medical support is expected to expand, further enhancing crisis healthcare delivery.

Integrating mental health in disaster responses is crucial. Mental disorders are often neglected in the aftermath of a crisis. However, unmanaged psychiatric disorders increase individual and societal strain, making it essential for EMTs to be equipped with fast, reliable, and easy to use tools for identifying and treating such concerns, especially as disasters can intensify psychological conditions.

Since diagnosing mental health problems is a labor-intensive, time-consuming, and challenging process, primarily because mental health conditions are complex and often lack quantifiable tests or measures for accurate assessment, we aim to provide a decision support system for EMTs to support the detection of mental disorders.

We developed an AI model trained on the health records of 812,853 people to detect depressive disorder (specificity 0.999, sensitivity 0.944). This model will now be extended to identify additional mental health conditions that are pertinent in disaster situations, such as anxiety, mood and stress disorders, and addictive behaviors. For this, it is crucial to recognize that the presentation of mental disorders is culture-specific and varies between emergency situations and normal daily lives as well as the quality and completeness of the recorded data.

Considering increasing rates of post-disaster related mental health disorders, our novel models help to early recognize, and phenotype diseases, streamline EMT operations, and reduce costs and suffering associated with mental health burden.

Incorporating AI can significantly enhance the detection of mental health issues in disaster situations, providing timely medical intervention by EMTs and supporting the Sustainable Development Goals of health, equality, and well-being.

The use of computer modelling and simulation is allowing researchers to test operational assumptions in a virtual but controlled experimental environment.

Developing a valid computer simulation model allowing (1) to model complex medical response systems with several types of victims, (2) to test different aspects of the medical response.

The SIMEDIS (Simulation for the Assessment and Optimization of Medical Disaster Management) computer simulator consists of 3 interactive components: the victim creation model, the victim monitoring model, and the medical response model.

The objectives of the study were to create a disaster medical response simulation model in the case of an aircraft crash and in a CBRN incident simulation, to test and to optimize existing and future medical disaster response plans, to develop a victim model, to develop a victim creation model and a victim monitoring model, and to produce a pre-hospital medical response model.

The case studies showed that the SIMEDIS simulator is offering a valuable tool for testing the impact of several interventional factors on the disaster medical response in specific scenarios including more complex situations such CBRN-incidents.

This study reflects the potential of SIMEDIS to model complex systems, to test different aspects of the disaster medical response and to potentially inform changes in practices. This might be of potential interest for disaster response planners allowing them to make the best choices in composing their medical teams and adapting the medical response system.

The World Health Organization (WHO) Emergency Medical Teams (EMTs) frequently deploy in high-risk environments, including conflict zones, where Chemical, Biological, Radiological, Nuclear (CBRN) threats are a concern. This study aimed to develop a CBRN assessment tool to evaluate the preparedness of WHO EMTs to respond effectively to such incidents.

Develop a comprehensive CBRN assessment tool for evaluating the preparedness of WHO Emergency Medical Teams (EMTs) to respond effectively to CBRN incidents.

Utilizing the WHO Classification and Minimum Standards for EMTs and adapting the Harvard Public Health School’s hospital decontamination self-assessment tool, this tool focuses on key areas aligned with WHO recommendations, including decontamination, staffing, training, response procedures, alert systems, security, personal protective equipment (PPE), staff safety, medical monitoring, decontamination zone setup, and triage.

The developed CBRN assessment tool provides a structured framework to evaluate EMT preparedness across multiple domains critical for CBRN incident response. The tool highlights potential gaps in preparedness and facilitates targeted improvements. This assessment tool can be a valuable resource for WHO EMTs to proactively assess CBRN capabilities. Regular use of this tool can enhance preparedness, response efforts, and improve patient outcomes in the face of CBRN events. Further research is needed to validate the tool’s effectiveness in team preparedness and refine its components.

This CBRN assessment tool is an important step towards strengthening the capacity of WHO EMTs to manage CBRN incidents. By facilitating self-assessment and targeted improvements, the tool contributes to a more effective and coordinated preparedness and response to these complex and challenging events.

The Philippines, being prone to natural disasters, often faces challenges in securing real-time data, hindering effective decision-making. In response, the Philippine Emergency Medical Assistance Team (PEMAT) of Dr. Jose N. Rodriguez Memorial Hospital and Sanitarium (DJNRMHS) developed the PEMAT Information System (PIS) to enhance real-time reporting and support the functions of EMT-Type 1 Fixed facilities during disaster responses. The PIS was successfully launched and fully implemented during the 7.8 Magnitude Earthquake in Türkiye in February 2023.

The PIS aims to enhance the efficiency and effectiveness of Emergency Medical Team (EMT) Type-1 facilities, improve healthcare service quality and patient safety, and deliver real-time data to stakeholders like the Emergency Medical Teams Coordination Cell (EMTCC) and local government agencies for informed planning and action. It also assists in patient tracking during disaster response and recovery phases.

During the Türkiye earthquake response from February 11-24, 2023, PEMAT used the PIS for data collection and reporting per international standards like the International Classification of Diseases and the EMT Minimum Data Set. Timely reports on patient numbers were provided to the EMTCC.

PEMAT catered to 1,022 patients, primarily aged 18-64 (68.59%), with a majority (54.60%) being male. The top reasons for consultation were Acute Upper Respiratory Infection (36.30%), Minor Injury (6.36%), and Skin Disease (6.07%). Notably, 74.16% of cases were unrelated to the earthquake. Timely reporting to the EMT MDS Portal earned commendation from the EMTCC.

The PIS significantly improved healthcare service quality and provided crucial real-time data for decision-making during disaster response and recovery.

Reliable health data before, during and after emergencies and disasters are essential for evidence-based policies and programs. However, standardization of health data collection and reporting was a historical challenge for the medical team dispatched to emergency areas.

The WHO Emergency Medical Team (EMT) Minimum Data Set (MDS) was established in 2017, and has been applied in different health emergencies and disasters as a common health data collection tool.

Summarize the findings from analyzing the health data collected by the EMT MDS in emergencies and disasters since 2018

The WHO Centre for Health Development (WHO Kobe Centre (WKC)) supported and jointly conducted a research project to synthesize the existing knowledge and analyze case studies on the application of the WHO EMT MDS. The study was led by Hiroshima University and collaborated with WHO EMT and multinational research institutes.

The research project demonstrated the function and value of the EMT MDS to timely collect analyzable data that enables decision makers to understand the health needs of affected areas, and conduct data-based resource allocation. Multiple barriers and facilitating factors for successful application of the tool were also identified. In addition, several new findings on early onset of mental health problems and other related matters were identified.

EMT MDS is now used as a common health data collection tool in emergencies and disasters. Accumulated data from different emergencies and disasters will support building robust scientific evidence to better protect people from emergencies and disasters.

The World Health Organization (WHO) Emergency Medical Team (EMT) Minimum Data Set (MDS) consists of a package of selected medical data items for recording and reporting patient encounters during sudden onset disaster. The MDS is primarily tailored for trauma and surgical care, and its effectiveness, particularly in contexts where other levels of care are needed, namely primary health care (PHC), has been strongly debated.

This study aims to analyze medical data from three UK-MED/UK-EMT deployments, compare the current MDS tool with its context-adapted versions, and explore potential improvements to enhance the effectiveness and adaptability of medical reporting.

We conducted a statistical analysis of medical data collected and reported in three types of settings: a) Ukraine (conflict), b) Malawi (outbreak), and c) Türkiye (earthquake).

The analysis of data from recent deployments in Ukraine, Malawi, and Türkiye reveals that non-trauma medical encounters are often categorized as “other” indicating that the current MDS lacks adaptability to various disaster types (non-trauma), local contexts, and specific medical needs. In addition, the tool generates extensive data with low granularity which has proven unhelpful in supporting health programming decision-making and for analysis of disaggregated data during and post-deployment.

We advocate for a comprehensive revision of the MDS, emphasizing the development of a modular data collection approach that can be tailored to specific local contexts and health services. This revised approach will enhance the utility of collected data for both immediate response efforts and long-term health system improvements, without adding extra data collection burden on clinicians.

Meaningful medical data are crucial for response teams in the aftermath of disaster. Electronic Medical Record (EMR) systems have revolutionized healthcare by facilitating real-time data collection, storage, and analysis. These capabilities are particularly relevant for post-disaster and austere environments. fEMR, an EMR system designed for such settings, enables rapid documentation of patient information, treatments, and outcomes, ensuring critical data capture.

Data collected through fEMR can be leveraged to perform comprehensive monitoring and evaluation (M&E) of emergency medical services, assess operational needs and efficiency, and support public health syndromic surveillance.

Analyzing these data identifies patterns and trends or assesses treatment effectiveness. This insight facilitates data-driven decision-making and the optimization of medical protocols. fEMR’s real-time reports enhance situational awareness and operational coordination among response units. The aggregated data can detect trends, classify case-mix, and facilitate after-action reviews, contributing to continuous improvement in emergency preparedness and response strategies. The system also supports fulfilling reporting requirements for health agencies and funding organizations, ensuring accountability and transparency.

EMRs like fEMR are vital for emergency response teams, supporting immediate patient care and ongoing M&E of disaster response efforts. Its robust data management capabilities support evidence-based practices and strategic planning, improving the effectiveness of emergency medical services in disaster scenarios.

The effective use of fEMR in disaster response scenarios highlights its significance in enhancing operational efficiency, ensuring accountability, and improving the overall effectiveness of emergency medical services through comprehensive data management and real-time reporting.

The WHO endorsed the Emergency Medical Team (EMT) Minimum Data Set (MDS) as a real-time data collection and reporting tool during health emergencies and disasters in 2017. It was for the first time activated in 2019 during Cyclone Idai in Mozambique. Since then, it has been used in 16 countries during various events. However, no assessment on data quality collected via MDS has been conducted.

This study aimed to assess data completeness using data from Cyclone Idai.

We analyzed 282 daily reports containing 18,468 patient consultations from 14 international EMTs between 2019/03/27 and 2019/07/12. We considered data incomplete if inputs for demographic information, health events, outcomes, and relation to disaster were lower than the total number of patient consultations. We calculated the percentage of missing values for MDS items. Logistic regression identified associations between data incompleteness and EMT type.

Completeness of information on team and location was 100%. Incompleteness rates were 7.1% for sex and age, 37.2% for health events, 48.9% for outcomes, and 41.8% for the relation of health events to the disaster. Type 1 Fixed EMTs reported less complete data compared to Type 1 Mobile and Type 2 EMTs. Classified EMTs were more likely to report complete data.

Overall, MDS daily report completeness needs improvement. Type 1 Fixed EMTs may have lower completeness due to busier schedules, while Type 1 Mobile EMTs benefit from more effective just-in-time training. Type 2 teams, being less busy, achieve more accurate data entry. Training for data collection is essential for better data completeness.

Clinical records are crucial for patient safety, continuity of care, and reflect the quality of care. In disasters, their importance increases due to limited patient information and complex scenarios. PT EMT clinical records should follow WHO recommendations and SOPs to ensure good practices and patient safety, especially during care transitions. Currently, PT EMT records are paper based until the Emergency Medical Team Operating System (EOS) digital system is implemented.

The aim was to review PT EMT’s clinical records from 2023 to assess adherence to procedures, identify improvement areas, provide feedback to professionals, and promote a culture of patient safety and continuous improvement.

Ten clinical records were randomly selected from each PT EMT deployment in 2023, totaling 60 records analyzed and registered using a specific checklist.

Records were missing information for: mission identification (35%), patient nationality (52%); contact details (100%); event date (12%); event type (57%); event-mission relationship (87%); time of 1st triage (43%); triage result (25%); patient assessment time (33%); patient history (48%); allergies (45%); usual medication (57%); diagnosis (30%); medication prescription and administration (21%); procedures carried out (44%;, patient situation decision (43%); physician signature (12%) and ID number (53%; decision date (22%), and decision time (33%).

To standardize patient clinical recording, we planned and implemented: inclusion of this topic during briefings in deployments and in the PT EMT annual training plan; elaboration of a specific SOP, update record templates; conduct a workshop during DIRECT Course. The audits will be repeated with 2024 clinical records to evaluate the measures’ effectiveness.

When a natural or man-made disaster occurs, emergency medical teams (EMTs) are dispatched to provide medical surge capacity for injured and sick individuals. Accurate predictions of EMTs consultations during disasters can improve dispatch and withdrawal decisions. However, no published studies have yet demonstrated a method for predicting the number of consultations or patients based on EMT activity data.

This research explores an innovative yet simple and reliable method to predict the number of consultations needed by EMTs during disasters, aiming to enhance the effectiveness and efficiency of medical response.

Data were collected using Japan-Surveillance in Post-Extreme Emergencies and Disasters (J-SPEED) and Minimum Data Set (MDS) for five disasters in Japan and one in Mozambique. For each disaster, the number of consultations was predicted from the K value and constant attenuation model, originally developed for predicting COVID-19 patient numbers.

The total number of EMT consultations per disaster ranged from 684 to 18,468. The predicted curve and actual K data were similar for each of the disasters (R2 from 0.953 to 0.997), but offset adjustments were needed for the Kumamoto earthquake and the Mozambique cyclone because their R2 values were below 0.985. For the six disasters, the difference between the number of consultations predicted from K values and the measured cumulative number of consultations ranged from ±1.0% to ±4.1%.

The K value and constant attenuation model reliably predicted EMT consultations during six different disasters. This simple model may be useful for the coordination of future responses of EMTs during disasters.

Effectiveness of EMT deployments have long been questioned. It is often suspected that EMTs are reluctant to share information that could be used for evaluation because they are concerned by the gap between expected and reality. The multitude of methods used to evaluate, without similar language, limits comparisons, and makes it difficult to make any meaningful generalizations on conclusions and recommendations. Hence, a common set of criteria to evaluate an EMT deployment must be established.

To understand perspectives of evaluating EMT deployments for floods, tropical cyclones, earthquakes, and tsunamis

In-depth interviews were conducted with 17 EMT stakeholders. Mentioned evaluation indicators were listed in the Delphi Method questionnaire.

Two rounds of Delphi Method questionnaire were conducted, where fifteen and sixteen participants responded respectively, with all participants in round one responding to round two. Participants were asked to rate evaluation indicators and respective questions according to their perceived suitability using a four-point Likert scale. Suggestions provided in the first round were incorporated into the second round. Consensus was reached when more than 75% of respondents rated slightly suitable or highly suitable.

A total of 23 indicators and 160 questions have been raised, and all indicators and 157 questions reached consensus after two rounds of Delphi Method. A draft evaluation framework was formed, based on the After-Action Review published by the WHO.

A standardized evaluation framework will be beneficial to assess deployments. Further research can be done to identify areas within the evaluation framework that should be prioritized.

A standardized system for assessing Emergency Medical Teams (EMT) performance is essential for enhancing EMT preparedness, response, and quality assurance. An after-action review (AAR) is a qualitative tool used to evaluate actions taken during emergencies, identifying best practices, gaps, and lessons learned. While AARs have been widely applied to assess national emergency responses, their use for evaluating EMT performance is scarcely documented, and guidance is lacking.

This proposal aims to promote and support the development of a systematic approach for the assessment of EMT performance during emergencies, through the implementation of suitable AARs methodologies following deployments.

We propose a collaborative approach encompassing academic institutions, EMTs, WHO Secretariat, and other relevant stakeholders, which can focus on developing, testing, and implementing AARs tailored for EMTs by integrating scientific methods and field experiences.

Proposed strategy includes actions to:

• - Revise previously conducted AARs assessing EMT deployments, including methodology, pillars assessed, feasibility, resources, application of results.

• - Identify key elements for a systematic AAR approach that best evaluates EMT performance.

• - Test the feasibility and appropriateness of different AARs methodologies in different contexts and emergencies.

• - Develop guidance for the implementation of ARRs following EMT deployments, both to assess individual EMT performance and overall EMT response.

• - Identify/create a system for sharing AARs, enabling a systematic analysis of experiences from which new knowledge and conclusions are generated.

Collaborative efforts to guide AAR use for the assessment of EMT performance will lead to evidence-based recommendations that strengthen EMT response capacities and contribute to the EMT 2030 Strategic Objectives.

The National Institute of Medical Emergency holds the Portuguese Emergency Medical Team - PT EMT, certified by WHO in 2019, and since then its activity has been growing in several areas: assistance, advice, training, and cooperation between partners.

Our aim is to present the lessons learnt over five years of PT EMT’s activity in national and international missions and how the cycle of continuous improvement implemented to date has progressed.

Analyze the evolution of the PT EMT and incorporate the lessons learnt into the continuous improvement cycle.

Case study, analysis and reflection on lessons learnt from PT EMT deployments.

From 2019 to 2024, PT EMT was involved in 3 standby international deployments and 20 effective deployments: 8 international, 4 national Mass Gathering events, 1 national insular territory, 3 EU MODEX exercises, 2 mainland Portugal, 1 international territory and 1 MEDEVAC.

The planning, preparation and implementation of each deployment was specific and unique, depending on mission profile. This diversity and number of missions has streamlined internal and external processes, making deployment more efficient and faster, particularly the organization and standardization of medical kit loads, their weight and volume, their packaging for air or land transport, which has made it easier to draw up the cargo manifest.

As a result of the activity described above, continuous improvement processes have been implemented in various areas, namely: data records and collection; communication strategies with staff pool; team medical readiness; cargo manifest; packaging and transport; mission files preparation; management of clinical and logistical supply chain.

Past disaster responses have demonstrated the importance of occupational health services for Emergency Medical Team (EMT) members. However, that implementation has been mostly left to individual teams and organizations and with less systematic approaches. During the Noto Peninsula earthquake that occurred in January 2024, the Emergency Medical Team Coordination Cell (EMTCC) activated the new Occupational Health System; J-SPEED Health Check-up for the first time to monitor health status of all EMT members and to provide comprehensive occupational services regardless of their affiliated organizations.

To review methodology and key achievements of the J-SPEED Health Check-up during the Noto Earthquake 2024 in Japan.

During their deployment, all EMT members were suggested by the EMTCC which was embedded in the local health authority to enter and report their health status daily by using the J-SPEED+ application, which was originally developed to report the EMT Minimum Data Set (MDS) of patients. At the EMTCC, J-SPEED analysis support team conducted data analysis, and Disaster Occupational Health Assistance Team (DOHAT) provided targeted interventions to the individuals identified to be supported.

A total of 20,879 data entries were recorded during the deployment, which triggered 148 interventions by the professional Occupational Health Team. Anonymous summary report was made and shared at every EMTCC meeting.

J-SPEED Health Check-up was successfully implemented. Necessary and targeted occupational health supports were provided, awareness of the issue was improved among partners.

The demanding nature of the EMT members’ work in providing care for the affected population in the 7.6 magnitude earthquake that struck the Noto Peninsula, Japan, on January 1, 2024 is noted.

This study aims to examine the relationship between fatigue and the presenteeism of EMT members during this disaster.

A cross-sectional study was conducted from January 1st to March 31st using the J-SPEED (Japanese-Surveillance in Post-Extreme Emergencies and Disasters) health check-up among EMT members. The questionnaire items included fatigue level and presenteeism measured using WFun-D (Work Functioning Impairment Scale for disaster), along with information on the type of activity, occupation, duration of working (days), and symptoms due to fatigue. Logistic regression analysis was applied to determine the association between fatigue and presenteeism of EMT members.

Among the 20,551 cases, 66.2% worked in the field, with the majority being operation coordinators (31.8%), nurses (30.9%), and medical doctors (19.9%). Presenteeism is strongly associated with having medium and high fatigue levels (p<0.0001). Other factors associated with presenteeism in EMT members included: working in January (aOR: 2.13, 95% CI: 1.21-3.74), being a medical doctor (aOR: 1.53, 95% CI: 1.15-2.04) or administrative supporter (aOR: 2.07, 95% CI: 1.28-3.36), experiencing symptoms due to stress (aOR: 4.95, 95% CI: 3.80-6.46).

The study reveals a significant relationship between increasing fatigue levels and presenteeism among EMT members. These findings contribute to evidence-based strategies for fatigue management in disaster response scenarios, with implications for improving the effectiveness of medical response efforts in future large-scale disasters globally.

Following a wave of terrorist bombings in the mid-1990s, France established Medical-Psychological Emergency Units (MPEUs - “Cellule d’Urgence Médico-Psychologique - CUMP”). These units aim to provide immediate mental health and psychosocial support to victims and emergency responders. During the COVID-19 pandemic, the Bordeaux MPEU pioneered the use of cloud computing to coordinate real-time activity across thirteen regional mental health units that serve 6 million people.

Based on 30 years of disaster psychiatry expertise and national guidelines, this innovative approach was recognized by the governmental Regional Health Agency, leading to the development of an information system application (ISA) specifically tailored for managing mental health and psychosocial support during crisis events.

The alpha version of the ISA for MPEU is being tested locally during the Paris 2024 Olympics. It is a multi-media app that offers various functionalities according to user profile. Volunteers are mobilized via the app on their smartphone, have real-time event tracking, and can record their clinical activity. For unit managers, it facilitates triggering the network, deploying resources, and coordinating real-time responses to the evolving crisis. For institutions, it enables monitoring of the ongoing crisis and adjusting responses. The app, designed for major multi-site events, will be beta tested in a full-scale disaster simulation in Bordeaux.

Data will be collected and reported In October, 2024

The ISA-MPEU improves the network’s capacity to provide rapid and effective support in emergencies, while at the same time providing a research tool through its database of mental health responses.

Evaluating high-performance work practices and characteristics of Emergency Medical Teams (EMTs) in frontline quarantine and infectious disease control systems is crucial. Such evaluations not only minimize future risks to staff but also significantly enhance responses to crises. During the COVID-19 pandemic, AUSMAT conducted high-risk missions without any transmission to or between staff, despite including non-AUSMAT-trained personnel and the critical failures recorded in other quarantine operations within Australia.

This study takes a unique approach to identifying the barriers and facilitators of EMTs’ high-performance work practices, the team characteristics that support implementation, and their impact on team functionality, success, failure, and risk management.

A purposive sample of 19 AUSMAT members who held AUSMAT leadership roles for at least fourteen days during the COVID-19 responses from 2020 to 2022 was selected. These AUSMAT Team Leaders, with their real-world experiences, provided invaluable insights for this study.

The preliminary findings of this study underscore the practical implications of specific high-performance characteristics. These include the importance of a precautionary approach, temporal stability of team members, command and control structures, shared leadership, and decentralized decision-making.

The study highlights how these characteristics can significantly impact performance, emphasizing the importance of tailored work practices and supportive team characteristics in enhancing EMT functionality and managing risks effectively.

Since the start of the full-scale military invasion of Ukraine by the Russian Federation in 2022, Ukrainian hospitals have been operating under surge capacity - working relentlessly to manage the tidal wave of war-wounded patients. Retrospective analysis of war-wounded casualty surgical admissions in a reconstructive hospital along the Trauma Pathway shows that 90% of casualties present with severe tissue and bone infections, due to sub-optimal surgical interventions, IPC measures and antibiotic usage in the Trauma Stabilization Points and secondary hospitals. Life-saving strategies predominately center around re-amputation with long durations of antibiotics, resulting in long length of hospital stay, excess morbidity and mortality, and delayed progression to rehabilitation.

To support the implementation and evaluation of an infectious disease and antimicrobial stewardship program in a surgical department in a reconstructive hospital along the Ukrainian Trauma Pathway

An INGO supported the Ukrainian tertiary hospital to implement “Antimicrobial stewardship programs in health-care facilities in low-and middle-income countries: a WHO practical toolkit”

The following results were evaluated from March 2023 to September 2023:

• The average duration of antibiotics reduced from 5.18 days to 3.92 days

• The average cost of antibiotics per patient reduced from $31.2 to $19.33 USD and cost of surgical prophylaxis antibiotics per patient reduced from $4.87 to $3.17 USD

Implementing an Antimicrobial Stewardship and Infectious Disease Program in a surgical department of a tertiary hospital could support the quicker movement of patients to rehabilitation, reduce cost to the health facility and support clinicians to more effectively treat war-wounded patients in a conflict zone.