Disaster Health Care Research Articles

Fostering Mobile Field Hospitals Collaboration During Disaster Response for Seamless Continuity of Care: A Mini Review

When mobile field hospitals are deployed in response to a disaster, they may sometimes face unprecedented challenges that require collaboration either with other mobile field hospitals or with existing regional hospitals to maintain continuity of care for the impacted populations. This article explores the pivotal role of enhancing healthcare team collaboration to ensure seamless care continuity during disaster response in an austere disaster-stricken environment. To improve patient outcomes during disasters, this study aims to investigate the barriers to care continuity in disaster response and highlight frameworks that can enhance healthcare team collaboration during sudden onset of disasters. Several bibliographical databases, including Pub Med, Science Direct, Web of Science, and Google Scholar were utilized. Articles examined from the databases were focused on state-of-the-art healthcare collaboration frameworks. To shed light on the difficulties and the necessity of implementing a collaborative healthcare disaster response framework, a case study of an American mobile field hospital deployed during the 2010 Haiti earthquake was examined. The literature review highlighted several factors that are responsible for lack of coordination during disaster response especially in an austere setting like Haiti. The review further highlights some frameworks that have the potential to improve care continuity in such an environment. In the event of a disaster, especially in austere settings like Haiti where the usual coordination mechanisms with regional or local government is difficult, deployed mobile hospitals must find alternative frameworks to enable them to work in tandem among themselves and with the local hospitals to improve the affected population’s continuity of care. The five frameworks highlighted have the potential to facilitate care coordination and hence continuity of care in such settings.

Radiological perspective on earthquake trauma: differences in children and adults.

February 2023 saw major earthquakes in Pazarcık and Elbistan, causing significant devastation in Turkey. Patients were transferred to hospitals in neighboring provinces, with multiple traumas-especially fractures and organ injuries-forming the main reasons for hospital admissions. This study aimed to examine earthquake-related injuries in pediatric and adult populations to understand differences. This study analyzed 1,220 adults and 590 pediatric patients with radiological imaging out of 8,704 earthquake trauma cases. Radiological images were assessed independently by two radiologists. Statistical analysis using SPSS examined relationships between variables such as age group and injury type. Results showed 40% of adults and 64% of children had normal radiological findings. Cerebral and extremity traumas were most common in pediatrics, while adults showed more extremity, thoracic, and spinal traumas. Significant differences between adult and pediatric groups were observed in cranial fractures, thoracic and lumbar vertebral fractures, hemopneumothorax, lung contusions, rib fractures, femur and talocalcaneal fractures, and compartment syndrome (p<0.001). Earthquake-related injuries may vary between children and adults. Due to children's more flexible anatomical structure, it is believed that earthquake-related injuries occur less frequently in children. In this study, head traumas were more common in children compared to adults. The rate of cranial fractures was significantly higher in children, with a higher incidence of epidural hematoma compared to adults. Spinal traumas were more frequent in adults than in children, attributed to children's greater flexibility reducing the risk of entrapment under rubble. Pediatric thoracic compliance being significantly higher than in adults often resulted in milder chest traumas. However, compartment syndrome was more common in children, with a lower rate of accompanying bone fractures compared to adults. No significant difference was observed between children and adults in maxillofacial, abdominal, and pelvic traumas. These findings provide insights for future disaster healthcare planning and management.

Developing a healthcare transformational leadership competency framework for disaster resilience and risk management

Climate change-induced hazards increasingly threaten healthcare systems worldwide, amplifying the frequency and severity of disasters and their adverse health effects. This necessitates fortified healthcare leadership and resilient systems capable of delivering quality care amidst escalating environmental challenges and emphasises the need for standardised competency frameworks to enhance disaster readiness and response. As healthcare organisations face evolving challenges, cultivating transformational leadership competencies becomes essential for building adaptive, resilient, and effective disaster management strategies. Purposeof this study: This conceptual paper addresses the research question: "How can healthcare leaders' competencies be developed to support healthcare disaster resilience?". MethodsThe study, conducted in 2023, used a narrative literature review, comparative analysis, and synthesis. It reviewed frameworks on transformational leadership and disaster resilience, employing comparative analysis to examine relationships and leadership competencies. A synthesized framework was developed to clarify dimensions and relationships. ResultsEight ‘domains’ of competencies were identified, in addition to other ‘transferring skills.’ The domains were analysed regarding their component competencies and were broadly classified into knowledge, cognitive and interpersonal skills, and attitudes. This classification is proposed as a ‘Healthcare Transformational Leadership Competency Framework’ (HTLCF) for disaster resilience and risk management. ConclusionThe HTLCF supports leaders in navigating complexities, anticipating risks, and facilitating collaboration, communication, and accountability, leveraging their transformative agency. This study suggests the use of the Healthcare Transformational Leadership Competency Framework to develop a standardised disaster management curriculum and continuous, ongoing training. This would equip leaders to enhance resilience and ensure coordinated, effective disaster responses for healthcare systems.

2024년 의료정책을 둘러싼 제문제에 관한 소고

Collective action, such as strikes in the medical community, has been a social problem that has occurred countless times around the world in various causes and methods. Since human history is based on health, the medical community that has a great relevance to it is surrounded by complex and wide-ranging issues. In the case of the Korean medical community, a small collective action since the 1950s and a huge collective action called the four major doctor strikes since the 2000s have led to a serious health care disaster crisis called a medical chaos. This is the result of insufficient initial responses that overlooked the inadequacies of legal and appropriate solutions and the possibility of enormous social waves. The national crisis caused by the collective action against the promotion of medical policies currently facing must now be fundamentally resolved. Until now, the legitimacy of this collective action in the medical community has been controversial. Doctors may have different interpretations of their legal status depending on individual business owners, workers, and trainees, so their legality as an act of labor dispute may also change. However, if it is directly related to the people's health rights and causes serious violations of life and health, the legitimacy cannot be recognized even if it is any legal method. However, the profession of doctors is also part of the people whose basic rights should not be violated by excessive ethical obligations. Therefore, it is not acceptable to cause a medical gap, maintain an emotional confrontation with the government, lack of willingness to actively consult, or unfair behavior for internal unity, but the government also cannot avoid criticism that it is not mature, with many problems of content, procedures, processes and law in promoting policies, and emotional confrontation with the medical community. The confrontation between the government and the medical community is also a question of the legitimacy of actions based on rights and authority, but regardless, it must be responsible for recovering significant inconveniences to the public health environment due to defects in methods and procedures of realization, which must be fulfilled as an ethical obligation as well as legal and policy. Therefore, we need to make a compromise on the policy content, such as adjusting an increase in medical students and a medical fee for this situation, and introduce various systems to supplement this. ln the process of such compromise and coordination, procedural laws or consultation procedures should be prepared, and furthermore, it is emphasized that legalization of positions, procedures, and special cases that can clearly bear the responsibility for the results is necessary while clarifying legal status.

Strategies for Healthcare Disaster Management in the Context of Technology Innovation: the Case of Bulgaria

In Bulgaria, integrating technology and innovation is crucial for advancing sustainable healthcare disaster management, enhancing disaster response and recovery, and minimizing long-term environmental and social impacts. The purpose of the study is to assess the impact of modern technological innovations on the effectiveness of disaster management in health care in Bulgaria with a focus on Health Information Systems (HIS), Telemedicine, Telehealth, e-Health, Electronic Health Records, Artificial Intelligence (AI), Public Communication Platforms, and Data Security and Privacy. These innovations, when integrated effectively, can significantly strengthen Bulgaria's preparedness and response capabilities, improving efficiency and reducing the environmental footprint of disaster interventions. Collaboration with technology experts, research institutions, and international organizations is essential for successful implementation. The research aims to assess how these technologies can enhance disaster management efficacy, adopting a methodical approach using Systematic Literature Reviews (SLRs). Systematic Literature Reviews (SLRs) utilize precise criteria for research selection and evaluation to reduce bias, systematically compiling and analyzing data from various studies to offer evidence-based insights. They are crucial for uncovering research gaps, indicating areas needing further exploration. Findings highlight the transformative potential of technology integration in streamlining communication, data management, and operational efficiency. The study underscores the urgent need for an integrated approach and a culture of innovation within the healthcare sector, emphasizing ongoing assessment and adaptation of technology-based strategies. While acknowledging limitations and calling for further research, the study provides valuable insights into Bulgaria's healthcare disaster management strategies and sets the stage for future investigations to refine and expand upon these strategies. It advocates for a strategic framework guiding the efficient integration of technology into disaster management, aiming for resilient and patient-centric healthcare systems.

Development of a Proof-of-Concept Multi-Method Computer Simulation to Support Rural Healthcare Disaster Preparedness Planning

Due to a lack of resources, rural communities often face challenges when planning catastrophic events. This project involved applying systems thinking and model-based systems engineering to develop a proof-of-concept, multi-method computer simulation and then determining whether the simulation could be used to assess the efficacy of disaster planning approaches on health outcomes in rural communities, as a function of primary healthcare. The project focus was a rural or non-urban healthcare system experiencing a natural hazard. Both system dynamics and discrete event models were incorporated to represent subsystem operations, crucial disaster responses, as well as three key response systems: public health, emergency management, and healthcare. The subsystem models included several components: policies/procedures, communications, resources, exercises/drills/training, healthcare space and staff, and the flow of affected people into and through the system. The combined simulation can serve as a first step to a more comprehensive approach to helping rural communities achieve more efficient and effective healthcare planning for disaster responses.

Disaster healthcare disparities solutions: Part 3-Recovery and mitigation.

The purpose of this study was to explore the potential solutions for disaster healthcare disparities. This paper is the third of a three-part series that was written by the Disaster Healthcare Disparities Workgroup of the American College of Emergency Physicians Disaster Preparedness and Response Committee. The committee conducted a literature review and chose articles most representative and demonstrative of solutions to disaster healthcare disparities found in a past workgroup product. Many solutions for disaster healthcare disparities seen during recovery and mitigation were found. Some of these solutions have been successfully implemented and some remain theoretical. Solutions for disaster healthcare disparities seen during recovery and mitigation are achievable but there is still much work to do. Many of these solutions can be advocated for by nondisaster specialists.

Disaster healthcare disparities solutions: Part 2-Response.

The purpose of this study was to explore the potential solutions for disaster healthcare disparities. This paper is the second of a three-part series that was written by the Disaster Healthcare Disparities Workgroup of the American College of Emergency Physicians Disaster Preparedness and Response Committee. The committee conducted a literature review and chose articles most representative and demonstrative of solutions to disaster healthcare disparities found in a past workgroup product. Many solutions for disaster healthcare disparities during disaster response were found. Some of these solutions have been successfully implemented and some are hypothetical. Solutions for disaster healthcare disparities seen during response are achievable but there is still much work to do. A variety of the proposed solutions can be advocated for by nondisaster specialists leading to better care for all our patients.

Disaster healthcare disparities solutions: Part 1-Preparation.

The purpose of this study was to explore the potential solutions for disaster healthcare disparities. This paper is the first of a three-part series that was written by the Disaster Healthcare Disparities Workgroup of the American College of Emergency Physicians Disaster Preparedness and Response Committee. The committee workgroup conducted a literature review and chose articles most representative and demonstrative of solutions to disaster healthcare disparities found in a past workgroup product exploring disaster healthcare disparities seen in disaster. Many solutions for disaster healthcare disparities during preparation were found. Some of these solutions have been successfully implemented, while others are still theoretical. Solutions for disaster healthcare disparities seen in disaster preparation are achievable, but there is still much work to do. There are a variety of solutions that can be easily advocated for by disaster and nondisaster specialists, leading to better care for our patients.

Assessing primary healthcare disaster preparedness: a study in Northern Italy.

The aim of this paper is to outline the steps taken to develop an operational checklist to assess primary healthcare (PHC) all-hazards disaster preparedness. It then describes a study testing the applicability of the checklist. A PHC approach is an essential foundation for health emergency and disaster risk management (H-EDRM) because it can prevent and mitigate risks prior to disasters and support an effective response and recovery, thereby contributing to communities' and countries' resilience across the continuum of the disaster cycle. This approach is in line with the H-EDRM framework, published by the World Health Organization (WHO) in 2019, which emphasizes a whole-of-health system approach in disaster management and highlights the importance of integrating PHC into countries' H-EDRM. Nevertheless, literature focusing on how to practically integrate PHC into disaster management, both at the facility and at the policy level, is in its infancy. As of yet, there is no standardized, validated way to assess the specific characteristics that render PHC prepared for disasters nor a method to evaluate its role in H-EDRM. The checklist was developed through an iterative process that leveraged academic literature and expert consultations at different stages of the elaboration process. It was then used to assess primary care facilities in a province in Italy. The checklist offers a practical instrument for assessing and enhancing PHC disaster preparedness and for improving planning, coordination, and funding allocation. The study identified three critical areas for improvement in the province's PHC disaster preparedness. First, primary care teams should be more interdisciplinary. Second, primary care services should be more thoroughly integrated into the broader health system. Third, there is a notable lack of awareness of H-EDRM principles among PHC professionals. In the future, the checklist can be elaborated into a weighted tool to be more broadly applicable.

An Effective Machine Learning Approach for Diabetes Prediction

Diabetes is a chronic condition that could lead to a global health care disaster. 382 million people worldwide have diabetes, according to the International Diabetes Federation. This will double to 592 million by 2035. Diabetes is a condition brought on by elevated blood glucose levels. The symptoms of this elevated blood sugar level include frequent urination, increased thirst, and increased hunger. One of the main causes of stroke, kidney failure, heart failure, amputations, blindness, and kidney failure is diabetes. Our bodies convert food into sugars, such as glucose, when we eat. Our pancreas is then expected to release insulin. Insulin acts as a key to unlock our cells, allowing glucose to enter and be used by us as fuel. However, this mechanism does not function in diabetes. The most prevalent forms of the disease are type 1 and type 2, but there are other varieties as well, including gestational diabetes, which develops during pregnancy. Data science has an emerging topic called machine learning that studies how machines learn from experience. The goal of this study is to create a system that, by fusing the findings of several machine learning approaches, can more accurately conduct early diabetes prediction for a patient. K closest neighbour, Logistic Regression, Random Forest, Support Vector Machine, and Decision Tree are some of the techniques employed. Each algorithm's accuracy is calculated along with the model's accuracy. The model for predicting diabetes is then chosen from those with good accuracy.

The Application of Model-Based Systems Engineering to Rural Healthcare System Disaster Planning: A Scoping Review

Disasters and other emergency events have complex effects on human systems, particularly if the events are severe or prolonged. When these types of events happen in rural communities, the resources of the local public health, healthcare, and emergency response organizations can be quickly depleted or overwhelmed. Planning for emergencies can help to mitigate their impact. Model-based systems engineering (MBSE) methods, including computer simulations, can provide insight on how best to prepare for these events and to explore the effects of varying approaches and resource utilization. To best apply these methods for improving disaster management in rural settings, a synthesis of the current body of evidence in this field is needed. The objective of this scoping review was to provide a descriptive overview of the application of computer simulation based on MBSE approaches to disaster preparedness and response for rural healthcare systems. Six studies met inclusion criteria, and varied in terms of MBSE method used, healthcare setting, and disaster type and context considered. We identified a gap in the research regarding the application of MBSE approaches to support rural healthcare disaster preparedness planning efforts. Model-based systems engineering and systems thinking, therefore, represent novel methods for developing tools and computational simulations that could assist rural communities better prepare for disasters.

Development of the “Conductor Type Human Resources Development” program for Disaster Medicine and Health Care by Tohoku University and Fukushima Medical University

Introduction:On March 11, 2011, the Great East Japan Earthquake with a 9.0 magnitude struck the northeastern coast of Japan. The death toll reached 15,892 and 2,576 people were reported missing. Tohoku University and Fukushima Medical University, both of which are located in the affected prefectures, responded massively to the disaster.Method:To deal with the next disaster, both universities established the “Conductor type Human Resources Development” (CHRD) program for Disaster Medicine and Health Care in 2019, not only for doctors, but also other medical professionals (such as dentists, nurses, pharmacists, etc.) supported by the Japanese government. The main course of CHRD program, “Disaster Management course,” which is also a certification program at Tohoku University, comprises 14 practical educational contents (seven practical trainings and seven lectures) based on the work experience of both universities in collaboration with various organizations.Results:To date, 59 students have enrolled in the Disaster Management course, two students are enrolled in the board-certified physician in public health and social medicine acquisition course, three students are enrolled in the master's course, a Tohoku University Graduate School of Medicine course, and two students are enrolled in the doctoral course. Until October 2022, a total of 17 people were certified to have completed the "Disaster Management course," and one person completed the board-certified physician in public health and social medicine acquisition course. A total of 68 practical trainings and lectures were held until 2021, the total number of times this program was attended by students until 2021 was 916. Average comprehension rate and satisfaction rate with practical trainings and lectures by students are 97.2% and 98.3%, respectively.Conclusion:All the students who complete the CHRD program are believed to acquire comprehensive skills related to disaster health and medical care and will be able to respond effectively in all phases.

Changing the Scene: Lessons Learned and Actioned into General Practice from Australian Flood Fire Drought &amp; Heat through Primary Health Networks

Introduction:General Practitioners (GPs) manage the majority of usual healthcare needs in a community. These healthcare needs do not cease in disasters; they increase and expand. However, inclusion of GPs in disaster healthcare systems is only just beginning. Systematic review of the health effects of disasters over days, months, and years, shows the major burden of healthcare needs associated with disasters is within the realm of usual general practice. In Australia, Primary Health Networks (PHNs) represent local GPs in each region. They offer the best option for systematic linkage of GPs to the broader DHM system.Method:A systematic review of the literature on the health effects of disasters and three qualitative studies reviewing the current experiences, barriers and facilitators to GP involvement in DHM systems were undertaken through a PhD at the Australian National University in 2022. A knowledge to action framework was developed and utilized to provide a systematic strategy to guide efforts to diffuse, disseminate, and implement the research as it emerged, with a focus on sustaining those changes through integration of PHNs into Australian DHM systems.Results:Integration of GPs, through PHNs, is evolving, through systematic inclusion in planning and policy in local health districts. Over time, evidence-based knowledge of disaster healthcare needs has been incorporated into GP disaster planning and preparedness, and resource development, and utilized by GPs during the recent 2019 Black Summer Bushfires, and East coast Floods.Conclusion:As our knowledge of the healthcare needs of disasters continues to reflect our increasingly challenging and complex world, the proven benefit of active involvement in holistic, comprehensive continuity of healthcare through General Practice in DHM systems through PHN linkage becomes more urgent.

Improved healthcare disaster decision-making utilizing information extraction from complementary social media data during the COVID-19 pandemic

Managing an extreme event like a healthcare disaster requires accurate information about the event's circumstances to comprehend the full consequences of acting. However, information quality is rarely optimal since it takes time to determine the information of relevance. The COVID-19 pandemic showed that even official data sources are far from optimal since they suffer from reporting delays that slow decision-making. To support decision-makers with timely information, we utilize data from online social networks to propose an adaptable information extraction solution to create indices helping to forecast COVID-19 case numbers and hospitalization rates. We show that combining heterogeneous data sources like Twitter and Reddit can leverage these sources' inherent complementarity and yield better predictions than those using a single data source alone. We further show that the predictions run ahead of the official COVID-19 incidences by up to 14 days. Additionally, we highlight the importance of model adjustments whenever new information becomes available or the underlying data changes by observing distinct changes in the presence of specific symptoms on Reddit.

Healthcare Impacts Associated with Federally Declared Disasters—Hurricanes Gustave and Ike

People impacted by disasters may have adverse non-communicable disease health effects associated with the disaster. This research examined the independent and joint impacts of federally declared disasters on the diagnosis of hypertension (HTN), diabetes (DM), anxiety, and medication changes 6 months before and after a disaster. Patients seen in zip codes that received a federal disaster declaration for Hurricanes Gustave or Ike in 2008 and who had electronic health records captured by MarketScan® were analyzed. The analysis included patients seen 6 months before or after Hurricanes Gustav and Ike in 2008 and who were diagnosed with HTN, DM, or anxiety. There was a statistically significant association between post-disaster and diagnosis of hypertension, X2 (1, n = 19,328) = 3.985, p = 0.04. There was no association post-disaster and diabetes X2 (1, n = 19,328) = 0.778, p = 0.378 or anxiety, X2 (1, n = 19,328) = 0.017, p = 0.898. The research showed that there was a change in the diagnosis of HTN after a disaster. Changes in HTN are an additional important consideration for clinicians in disaster-prone areas. Data about non-communicable diseases help healthcare disaster planners to include primary care needs and providers in the plans to prevent the long-term health impacts of disasters and expedite recovery efforts.

Report on the Project on the Implementation of Continuity Operations in Disaster-Affected Healthcare Facilities Using Gensai Calendar HDMG and COOP Flow Diagram

Based on the lessons learned from past disasters, the Japanese Ministry of Health, Labour and Welfare has notified the establishment of disaster base hospitals and ensured medical care continuity based on business continuity plan (BCP). Following these, we created a disaster management training program with 45 items, the Disaster Mitigation (Gensai) Calendar for Healthcare Disaster Management Guide (HDMG)* (“Gensai Calendar”) in 2018. Thereafter, a three-year multicenter project was launched at the Tokyo Metropolitan Hospital Organization to introduce the “Gensai Calendar” and assess its merits as a self-learning material through tests based on it. The project also aimed at establishing a common operating procedure (COOP) for medical continuity at affected healthcare facilities using annual comprehensive disaster drills. The numbers of participants and hospitals recruited for the test over the three-year period were 4,281 in six hospitals, 6,179 in ten hospitals, and 6,216 in seven hospitals. The total of 55 questions were asked in the e-learning format in the first and second years, and 11 in the third year. Questions with less than 70% correct rate were same for three years. Through the drills, a COOP flow diagram was constructed based on the initial responses in the wards. Furthermore, the crisis management system of each hospital was unified, and each BCP was revised into a standard document along the “COOP Flow Diagram.” A COOP system combining the “Gensai Calendar” learnings, annual “COOP Flow Diagram” drill, and standard documentation can be a viable system for medical continuity. This system could also be versatile and introduced to many healthcare facilities. * This is also the abbreviation for the Hiroo Disaster Management Group, which has a double meaning. The group consists of disaster prevention staff from the Tokyo Metropolitan Hiroo Hospital, Komagome Hospital, and Bokutoh Hospital, and is responsible for planning and managing disaster mitigation measures.

Review on the Evaluation and Development of Artificial Intelligence for COVID-19 Containment.

Artificial intelligence has significantly enhanced the research paradigm and spectrum with a substantiated promise of continuous applicability in the real world domain. Artificial intelligence, the driving force of the current technological revolution, has been used in many frontiers, including education, security, gaming, finance, robotics, autonomous systems, entertainment, and most importantly the healthcare sector. With the rise of the COVID-19 pandemic, several prediction and detection methods using artificial intelligence have been employed to understand, forecast, handle, and curtail the ensuing threats. In this study, the most recent related publications, methodologies and medical reports were investigated with the purpose of studying artificial intelligence's role in the pandemic. This study presents a comprehensive review of artificial intelligence with specific attention to machine learning, deep learning, image processing, object detection, image segmentation, and few-shot learning studies that were utilized in several tasks related to COVID-19. In particular, genetic analysis, medical image analysis, clinical data analysis, sound analysis, biomedical data classification, socio-demographic data analysis, anomaly detection, health monitoring, personal protective equipment (PPE) observation, social control, and COVID-19 patients' mortality risk approaches were used in this study to forecast the threatening factors of COVID-19. This study demonstrates that artificial-intelligence-based algorithms integrated into Internet of Things wearable devices were quite effective and efficient in COVID-19 detection and forecasting insights which were actionable through wide usage. The results produced by the study prove that artificial intelligence is a promising arena of research that can be applied for disease prognosis, disease forecasting, drug discovery, and to the development of the healthcare sector on a global scale. We prove that artificial intelligence indeed played a significantly important role in helping to fight against COVID-19, and the insightful knowledge provided here could be extremely beneficial for practitioners and research experts in the healthcare domain to implement the artificial-intelligence-based systems in curbing the next pandemic or healthcare disaster.

Racial Differences and Injury Pattern Variation: Impact of COVID-19 on a Bronx Trauma Center.

New York City (NYC) became the epicenter of the COVID-19 pandemic in 2020. The Bronx, with the highest rates of poverty and violent crime of all NYC boroughs and a large Black and Hispanic population, was at increased risk of COVID-19 and its sequelae. We aimed to identify temporal associations among COVID-19 and trauma admission volume, demographics, and mechanism of injury (MOI). A retrospective review of prospectively collected data was conducted from a Level II trauma center in the Bronx. January 1st-September 30th for both 2019 (Pre-COVID) and 2020 (COVID) were compared. Pre-COVID and COVID cohorts were subdivided into EARLY (March-May) and LATE (June-September) subgroups. Demographics and trauma outcomes were compared. Trauma admissions were similar between Pre-COVID and COVID. During COVID, there was an increased percentage of Black patients (Black Hispanic 20.1% vs 15.2% and Black Non-Hispanic 39.4% vs 34.1%, P < .05), younger patients (26-35years old: 22.6% vs 17.6%, P < .05), and out-of-pocket payors (6.0% vs 1.6%, P < .05). Trauma severity outcomes were mixed-some measures supported increased severity; others showed no difference or decreased severity. During COVID, there was a rise in total penetrating injuries (27.4% vs 20.8%, P < .05), MVC (13.2% vs 7.1, P < .05), and firearm injuries (11.6% vs 6.0%, P < .05). Additionally, during LATE COVID, there was a resurgence of total penetrating, total blunt, MVC, falls, cyclists/pedestrians struck, and firearm injuries. Our results emphasize MOI variations and racial differences of trauma admissions to a Level II trauma center in the Bronx during COVID-19. These findings may help trauma centers plan during pandemics and encourage outreach between trauma centers and community level organizations following future healthcare disasters.

Evaluating post-earthquake functionality and surge capacity of hospital emergency departments using discrete event simulation

Past earthquakes have illustrated the impacts of reduced hospital functionality due to physical damage resulting in a health service deficit immediately after a major seismic event. In this article, a methodology was developed to quantify the deficit in health care anticipated due to a loss of functionality of a hospital emergency department (ED) and a surge in demand due to regional damage in an earthquake scenario. Earthquake-induced patient arrivals were calculated using multi-severity casualty estimation for the catchment area of the hospital. The surge in patients (demand) was then compared to the ability of the hospital to treat patients (capacity) based on anticipated functionality. Nonlinear response history analysis of the hospital building was performed using simplified structural models, and the structural and non-structural component damage was estimated based on FEMA P-58. Expected damage was linked to the post-earthquake functionality of the ED service areas on each floor by incorporating the fault-tree analysis method. Finally, discrete event simulation was used to evaluate the ED surge capacity, providing hospital performance metrics, such as wait times (WTs) and length of stay (LOS) for patients of ranging acuity. A case study of a hospital in the City of Vancouver subjected to an Mw9.0 Cascadia Subduction Zone scenario earthquake was presented. Emergency rooms (ERs) were identified as the ED bottleneck during the emergency response. The mean ER WT exceeded its limit of 2 h and reached up to 17 h in the most unfavorable simulation. Likewise, the mean LOS nearly doubled from 6.5 to 12 h, also exceeding the established target of 10 h. The deployment of field hospitals for less severe patients as an emergency plan to mitigate the ED overcrowding was also analyzed to demonstrate that the methodology can be used as a decision support tool to improve healthcare disaster planning.