Abstract - In emergency medical situations, timely monitoring and rapid medical decision-making are critical for saving lives. This project presents a Smart Health Monitoring System for Ambulances, an IoT- and Machine Learning–based solution designed to continuously monitor a patient’s vital signs during transit and transmit them to healthcare professionals in real time. The system integrates biomedical sensors to measure essential parameters such as heart rate, blood pressure, SpO₂, body temperature, and ECG signals. These sensors are interfaced with an ESP32 microcontroller, which collects, processes, and wirelessly transmits the data to a cloud-based platform using Wi-Fi connectivity. A Machine Learning model analyzes the received data to assess the patient’s health condition and classifies it into categories such as stable, moderate, or critical. This real-time analysis enables doctors at the hospital to monitor the patient remotely and prepare necessary medical interventions before the ambulance arrives. The automated system reduces the workload on paramedics, minimizes human error, and improves the accuracy of emergency diagnosis. Overall, the proposed system enhances pre-hospital care by enabling continuous monitoring, early detection of critical conditions, and faster medical response. By combining IoT, cloud computing, and machine learning, this project contributes to the advancement of smart healthcare and improves patient survival rates during emergency transportation. Key Words: Smart Health Monitoring, Ambulance System, Internet of Things (IoT), ESP32, Machine Learning, Biomedical Sensors, Real-Time Monitoring, Emergency Healthcare, Cloud Computing, Telemedicine

Abstract - In emergency medical situations, timely monitoring and rapid medical decision-making are critical for saving lives. This project presents a Smart Health Monitoring System for Ambulances, an IoT- and Machine Learning–based solution designed to continuously monitor a patient’s vital signs during transit and transmit them to healthcare professionals in real time. The system integrates biomedical sensors to measure essential parameters such as heart rate, blood pressure, SpO₂, body temperature, and ECG signals. These sensors are interfaced with an ESP32 microcontroller, which collects, processes, and wirelessly transmits the data to a cloud-based platform using Wi-Fi connectivity. A Machine Learning model analyzes the received data to assess the patient’s health condition and classifies it into categories such as stable, moderate, or critical. This real-time analysis enables doctors at the hospital to monitor the patient remotely and prepare necessary medical interventions before the ambulance arrives. The automated system reduces the workload on paramedics, minimizes human error, and improves the accuracy of emergency diagnosis. Overall, the proposed system enhances pre-hospital care by enabling continuous monitoring, early detection of critical conditions, and faster medical response. By combining IoT, cloud computing, and machine learning, this project contributes to the advancement of smart healthcare and improves patient survival rates during emergency transportation. Key Words: Smart Health Monitoring, Ambulance System, Internet of Things (IoT), ESP32, Machine Learning, Biomedical Sensors, Real-Time Monitoring, Emergency Healthcare, Cloud Computing, Telemedicine

In Indonesia, weaknesses in the neonatal emergency referral and transport system have been identified as important factors in preventable neonatal deaths. To address this, a bottleneck analysis study was conducted in Surabaya using the modified Tanahashi model to identify bottlenecks in four key domains: supply, demand, quality, and the enabling environment. A mixed-method approach was employed. Qualitative data from interviews and focus groups identified gaps and underlying causes. Tracer indicators were used for targeted quantitative data collection through Health Facility Assessments and secondary data review to measure the gap extent. Primary health care facilities lacked trained staff, and bed shortages delayed transfers. Nonstandardized processes hindered transfer efficiency and affected neonatal care at specialized hospitals. Systemic weaknesses were found in data collection, monitoring, interagency coordination, and policy implementation. The bottleneck analysis framework effectively identified critical gaps and guided strategic prioritization for system improvement. Findings highlight the need for reviewing facility standards, modifying staff training, streamlining referral processes, establishing clear oversight roles for referral and prioritizing systematic monitoring and evaluation. The selected tracer indicators offer a framework for assessing neonatal emergency referral systems in other resource-limited settings, supporting efforts to improve neonatal survival through more effective referral and transport mechanisms.

BackgroundThe aging global population has led to rising emergency department (ED) visits and hospital admissions among older adults, many of whom have complex medical and social backgrounds. A substantial proportion of these visits may be avoidable, particularly among individuals receiving home medical care. Such avoidable hospitalizations can lead to adverse outcomes such as functional decline and iatrogenic complications, while placing additional strain on healthcare systems. Identifying predictive factors for hospital admission in this population is essential for improving care quality, optimizing resource utilization, and guiding decision-making in prehospital settings.MethodsWe conducted a retrospective observational study at the Juntendo University Nerima Hospital in Japan. “Tokyo Rule” (TR), a policy enacted on August 1, 2009, by the Tokyo Metropolitan Government, applies to difficult emergency transport cases and mandates that designated hospitals accept unanticipated ambulances. TR criteria included: (1) the patient’s clinical condition was generally moderate or mild; and (2) ≥ 5 medical institutions refused ambulance transfer requests or 20 min had elapsed since the selection of medical institutions by an emergency medical technician. If the case meets both criterion (1) and criterion (2), it is regarded as a TR case. Our institution proactively accepts patients transferred by ambulance, including those under TR. Patients aged 75 years or older who were receiving house call medical services at home or in a nursing home (NH) and were transported to our hospital by emergency medical service (EMS) were included in this study. Clinical, demographic, and situational data were obtained from electronic medical records. The primary outcome was hospital admission. Univariate analyses were performed to identify potential predictors, followed by multivariate logistic regression analysis to determine independent predictors. A two-tailed significance level of 0.05 was applied.ResultsOf the 853 patients transported to our hospital during the study period, 738 met the inclusion criteria. Among them, 503 were admitted, and 235 were discharged from the ED. In the univariate analysis, factors significantly associated with admission included a lower Glasgow Coma Scale score; higher National Early Warning Score; oxygen therapy in the ED; and suspected diagnoses of infection, cerebrovascular disease, or cardiovascular disease. In the multivariate analysis, independent predictors included suspected infection, cerebrovascular disease, cardiovascular disease, digestive disease, oxygen therapy in the ED, and reduced consciousness. Minor trauma and transient loss of consciousness were associated with lower odds of hospital admission.ConclusionsThis is the first study to identify clinical and situational factors associated with hospital admission among older patients receiving home call medical services at home or in the NH who were transported by EMS. Among these patients, hospital admission was associated with suspected infection; cardiovascular, cerebrovascular, and digestive diseases; oxygen therapy in the ED; and reduced consciousness. These findings may help guide triage and decision-making in emergency care for this vulnerable population.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12873-025-01414-6.

Despite progress in improving access to and use of maternal and newborn health (MNH) services in Ethiopia, challenges persist in ensuring equitable, high-quality care. This study assessed the effective coverage cascade across antepartum and peripartum care (PPC) using formative implementation science research data obtained during July-August 2024. A stratified multistage sampling method recruited 1,922 women with infants (0-11 months), including 1,118 from agrarian and 804 from pastoral regions. The study included facility assessments at 67 primary care facilities and 329 client exit interviews. Service contact was defined as attending at least one antenatal care (ANC) contact and delivering in a health facility. Intervention-adjusted coverage accounted for receipt of key interventions, while readiness- and quality-adjusted coverage incorporated facility input and quality index scores from facility survey readiness assessment and exit interviews. Sampling weights were applied, and household and facility data were linked using ecological methods -that is, by aligning data from the same woreda rather than linking records at the individual level. Mean facility readiness scores for ANC and PPC were 74% and 80%, respectively. The mean care experience score from exit interviews was 83%, while antepartum and peripartum service provision scores were 60% and 61%. Household survey data showed that fewer than three-quarters of women received recommended ANC interventions, while 82% of women received peripartum and newborn interventions. Most facilities had uterotonics, newborn resuscitation bags, and essential maternal health services. However, gaps in trained staff, diagnostics, emergency transport, and dignified care persisted. Missing services-including ultrasound, deworming, maternal depression screening, and postpartum family planning counseling-highlighted critical service delivery challenges. The effective coverage cascade shows significant drop-offs across the continuum of care. For ANC, 81% of women made initial contact, only 63% received care in facilities with essential inputs, 49% received essential interventions, and only 26% ultimately received quality services. A similar pattern was observed for peripartum services: about 74% of women delivered at a health facility, only 59% received PPC in a facility with essential inputs, 49% received essential interventions, and just 26% received quality services. Regional disparities were evident across the cascade. While MNH service access has expanded, substantial cascade losses and inequities persist, particularly between agrarian and pastoral regions. Addressing these challenges requires equity-focused strategies to enhance readiness, improve service quality, integrate care, and strengthen accountability.

This study examines the link between institutional characteristics and the provision of basic needs services at nonprofit, two- and four-year colleges in a high-poverty U.S. state. Basic needs insecurity, including food and housing instability, significantly affects students' academic success, retention, and well-being. Results show that public, four-year colleges are more likely to offer comprehensive basic needs services than community colleges and private institutions. Interestingly, spending on academic and student services per full-time student strongly relates to the availability of emergency housing, health services, and transportation support. Colleges with a higher percentage of students of color are more likely to provide mental health services. The findings contribute to global discussions about institutional capacity, legitimacy, and equity in higher education.

BackgroundDespite the remarkable burden of snakebite envenoming (SBE) and placement of public health importance of SBE at global and national levels, a huge gap still exists in the first aid of snakebites. Herein, we aimed to evaluate the currently used textbooks to know improvements in advising standard first aid of snakebites in textbooks used in Nepalese schools and universities after a similar study published in 2013.Methodology/Principal FindingsWe evaluated 46 recently edited textbooks used for teaching safety and first aid in Nepal during January–April 2024 involving thematic analytical approach. We performed an analytical review of safety and first aid in textbook. The counts of harmful or useless advice for first aid significantly decreased [p < 0.001] and standard first aid significantly increased [p < 0.001]. But, the proportions of advice for emergency transport, and going to an appropriate healthcare facility provided with anti-snake venom (RAFA) negligibly increased [p = 0.367 (right)]. However, 6–75% errors reflected the persistent use of teaching materials containing non-recommended first aid measures.Conclusions/SignificanceTherefore, it is essential to update these textbooks including evidence-based, standard first aid for snakebites to increase the advice for appropriate care of snakebites at pre-hospital condition. We suggest authors revising those textbooks including the advice for application of pressure-immobilization bandaging (PIB) and local compression-pad immobilization (LCPI) by trained first aider and other first aid that can be applied by general people. PIB delays the onset of systemic neurotoxic venom effects due to krait bites. LCPI delays systemic venom effects and minimize local toxicity (i.e., destruction of tissue at the site of the bite) due to cobra and all viperid snake venoms.

Despite the remarkable burden of snakebite envenoming (SBE) and placement of public health importance of SBE at global and national levels, a huge gap still exists in the first aid of snakebites. Herein, we aimed to evaluate the currently used textbooks to know improvements in advising standard first aid of snakebites in textbooks used in Nepalese schools and universities after a similar study published in 2013. We evaluated 46 recently edited textbooks used for teaching safety and first aid in Nepal during January-April 2024 involving thematic analytical approach. We performed an analytical review of safety and first aid in textbook. The counts of harmful or useless advice for first aid significantly decreased [p < 0.001] and standard first aid significantly increased [p < 0.001]. But, the proportions of advice for emergency transport, and going to an appropriate healthcare facility provided with anti-snake venom (RAFA) negligibly increased [p = 0.367 (right)]. However, 6-75% errors reflected the persistent use of teaching materials containing non-recommended first aid measures. Therefore, it is essential to update these textbooks including evidence-based, standard first aid for snakebites to increase the advice for appropriate care of snakebites at pre-hospital condition. We suggest authors revising those textbooks including the advice for application of pressure-immobilization bandaging (PIB) and local compression-pad immobilization (LCPI) by trained first aider and other first aid that can be applied by general people. PIB delays the onset of systemic neurotoxic venom effects due to krait bites. LCPI delays systemic venom effects and minimize local toxicity (i.e., destruction of tissue at the site of the bite) due to cobra and all viperid snake venoms.

This paper investigates the motion planning problem for symmetric UAV cooperative lifting in confined spaces. A dynamic model of the symmetric UAV cooperative lifting system is established, and differential flatness analysis is employed to transform nonlinear dynamics into constraints on flat outputs, thereby simplifying the motion planning process. The planning framework consists of two levels: path planning and trajectory planning. For path planning, a reinforcement learning-based bidirectional RRT (RLDB-BiRRT) method is proposed, which integrates the random tree expansion mechanism with the DDPG algorithm to achieve adaptive directional bias. This approach effectively mitigates the issues of low search efficiency and excessive redundant nodes inherent in traditional RRT algorithms. For trajectory planning, an adaptive safe flight corridor (SFC) construction method is introduced, combining symmetric ellipsoids and convex polyhedra to generate high-quality linear constraints. Building upon the proposed motion planning method and leveraging differential flatness analysis, a unified planning framework is developed that seamlessly integrates the reinforcement learning-enhanced path planning with adaptive safe corridor construction and differential-flatness-based trajectory optimization, specifically designed for symmetric UAV cooperative lifting tasks in confined spaces. This integrated approach enhances corridor space utilization and ensures trajectory continuity. Simulation experiments validate the effectiveness of the proposed methods, demonstrating their capability to generate dynamically feasible, smooth, and safe transportation trajectories in confined environments, while effectively constraining load swing and UAV attitude angles. This study provides theoretical foundations and practical references for the application of symmetric UAV cooperative lifting in low-altitude logistics and emergency transportation scenarios.

PurposeThe Saga Fall-related Injury Risk Model (SFIRM) was developed in an acute care hospital to predict fall-related injuries based on six factors upon admission: age, sex, emergency transport, medical referral letters, history of falls, and bedriddenness ranks. This study aims to validate the applicability of the model across various hospitals through external validation using data from multiple hospitals. Additionally, the common predictors of fall-related injuries across these hospitals were explored.Patients and MethodsThis multicenter, retrospective, observational study included patients aged 20 years and older who were admitted to 8 hospitals (chronic-care, acute-care, and tertiary acute-care) between April 2018 and March 2021. A calculated sample size of patients was selected and the area under the curve (AUC) of the SFIRM was determined for fall-related injuries during hospitalization. Multivariate analyses were conducted for each hospital using the surveyed factors as covariates and fall-related injuries as outcomes. The significant factors associated with fall-related injuries were compared across hospitals.ResultsFrom 144,777 patients, 2376 were randomly sampled and analyzed. Among them, 51 patients (2.1%) experienced falls during hospitalization and 35 (1.5%) sustained fall-related injuries. The AUC of SFIRM was 0.617 (95% confidence interval 0.534–0.701). In multivariate analyses by hospital, age and bedriddenness ranks were significantly associated with fall-related injuries in five hospitals, whereas male sex, history of falls, and diabetes were significantly associated with fall-related injuries in four hospitals.ConclusionThe SFIRM demonstrated low discrimination in a population from various hospitals. The predictive models for fall-related injuries require redevelopment and validation to suit various hospitals. In the multivariate analyses across hospitals, age, bedriddenness ranks, male sex, history of falls, and diabetes mellitus were common and significant factors associated with fall-related injuries. These factors are most favorable for developing a predictive model for fall-related injuries.

Abstract Background The burden on healthcare systems from the utilisation of emergency transportation (ET) is increasing worldwide. Particularly care-dependent individuals and long-term care recipients are affected. Objective We aim to investigate the factors contributing to ET utilisation, particularly in these care-related groups and settings. Methods Using claims data on ET utilisation in conjunction with long-term care (LTC) insurance data, we identified 561,322 ET events from 2018–2022 in insured individuals of AOK Saxony-Anhalt, Germany. Age-standardised incidence rates (ASIR) were calculated with the duration of insurance as time at risk. Negative binomial regression assessed factors influencing ET utilisation. Results ET utilisation remained stable over 5 years, with an ASIR of 112.59 per 1000 insured person–years. High care dependency level correlates with higher ET rates, both in terms of IR and in the regression model. This correlation strengthens when combined with LTC settings involving formal caregivers, such as nursing homes and formal home care. Multimorbidity is suggested as a potential contributing factor, particularly for individuals with care levels 4 and 5, but did not fully explain the observed patterns. Conclusion Care dependency and professional care are strongly associated with increased ET utilisation. The findings suggest a need for structural improvements in LTC, clearer legal frameworks, and better competencies across all care providers, including enhanced training and education, to address unmet needs and reduce potentially avoidable ET events. Further research should explore these relationships in more depth to inform interventions aimed at relieving pressure on emergency services.

Introduction Diffuse Correlation Spectroscopy (DCS) is a non‐invasive optical technique that measures cerebral blood flow (CBF) based on dynamic scattering of coherent light from moving red blood cells. It remains largely untested in the pre‐hospital phase, despite this window being critical for patients with acute neurological emergencies such as stroke.We aimed to determine whether DCS can provide accurate, robust, and continuous CBF measurements during emergency transport, establishing its role as a practical frontline tool in acute stroke care. Methods Cerebral blood flow was non‐invasively monitored using diffuse correlation spectroscopy (DCS). The DCS system (built at MGH) used a fiber optical probe placed on the left side of the subject's forehead with a 25 mm source‐detector separation. A blood flow index (BFi) was derived from the autocorrelation of detected light intensity fluctuations. The probe was secured using Tegaderm and covered with dark silicone material for light shielding. A head band was also used in some subjects. Simultaneous continuous arterial blood pressure was collected using a Finometer device (Finapres Medical Systems, Enschede, Netherlands) and a three‐axis accelerometer was used to record any motion of the probe.18 healthy subjects were monitored in a mobile stroke unit (MSU) in Fowler's position, first with the vehicle at rest, then while driving on city streets near the Texas Tech University Health Sciences Center in El Paso. A 20 second breath‐hold (BH) and an 8 second carotid compression (transient hyperemic response test ‐ THRT) were done both at rest, and during motion. DCS BFi time courses were averaged over 3 second intervals to increase the signal to noise ratio (SNR). Subjects were excluded from the group average if they were unable to properly perform the maneuver, if there was missing data or if the stationary measurement SNR was too low. Results Figure 1 shows normalized group‐averaged responses (vs. a 9‐second baseline period). The maneuver responses agreed well with and without MSU motion. Absolute DCS BFi values at rest were the same when the MSU was stationary or in motion in 75% of the subjects where only Tegadem was used, with mild elevations in others. Nevertheless, even in these cases the maneuver responses remained consistent. Conclusions These findings demonstrate the feasibility of employing DCS in emergency pre‐hospital settings. We obtained repeatable, physiologically plausible CBF measurements when compared to published in‐lab studies, supporting the robustness of DCS against motion artifacts for real‐time cerebral perfusion monitoring in acute stroke care. image

Background Reperfusion with endovascular thrombectomy (EVT) improves functional outcomes for acute ischemic stroke patients with large vessel occlusion (LVO). According to the American Heart Association's Target Stroke Guidelines, when an LVO stroke patient presents to a non‐thrombectomy capable hospital, the time from hospital arrival until transfer out for EVT (door‐in‐door‐out [DIDO] time) should not exceed 90 minutes. However, the average DIDO time in the United States in 2023 was 174 minutes. We report DIDO times within our hospital system pre‐ and post‐implementation of a protocolized system‐wide LVO transfer process. Methods Our hospital system consists of seven spoke hospitals and two hub hospitals which perform EVT. LVO stroke patients presenting to spoke hospitals are emergently evaluated, treated (including intravenous thrombolysis), and triaged via telestroke by a university‐based stroke team. The stroke team, in conjunction with a multidisciplinary neurointerventional team, also determine if the patient would benefit from EVT and should be emergently transferred..Pre‐implementation, the LVO transfer process was initiated and driven by each spoke hospital on a case‐by‐case basis in coordination with the system operations center (SOC). As part of a hospital system quality improvement initiative, a unified regional LVO transfer model was implemented. Key interventions included: 1) assigning one hub hospital to be the primary transfer destination for each spoke hospital, 2) the SOC was no longer required to confirm the availability of a post‐procedure inpatient bed prior to initiating transfer, and 3) assigning transfer coordination tasks (e.g., arranging emergency transportation and alerting the neurointerventional team) to specific provider, nursing, and support staff roles. We retrospectively reviewed all LVO patients who were transferred for EVT between 1/8/2022‐8/14/2023. The regional LVO transfer model was implemented 8/28/2023. Exclusion criteria were: code stroke not activated, contrast allergy, or obtaining MRI. We report patient demographics descriptively (Table 1). To assess DIDO times pre‐ and post‐implementation, we utilized Wilcoxon Rank‐Sum testing. Results 70 LVO patients pre‐implementation and 55 LVO patients post‐implementation met our inclusion criteria. Patient characteristics, including age, sex, race, and baseline NIHSS, are summarized in Table 1. Median DIDO time decreased from 117 minutes to 90 minutes (P &lt; 0.001) following implementation of the regional LVO transfer model. The interquartile range decreased from 48 minutes to 24 minutes post‐implementation, reflecting decreased variability in the transfer process. Conclusion Implementation of a standardized, protocol‐driven regional LVO transfer model across our hospital system significantly reduced DIDO times. image

The Impact of the Bypass Transport Method on Clinical Outcomes After Large Vessel Occlusion: A Pooled-Proportion Meta-Analysis.

The global acceleration of population aging, especially in developed countries, has led to increased demands on emergency medical services. In Tokyo, Japan's largest city, over half of all emergency transports involve older adults aged 65 and older, a figure that continues to rise annually. These patients often present with complex medical conditions, require intensive prehospital interventions, and have higher hospitalization rates compared to younger populations. Despite these trends, there is a scarcity of studies examining the characteristics of older adults patients transported by ambulance and the factors associated with their hospitalization. We conducted a retrospective study using emergency transport data from the Tokyo Fire Department (2017-2021), targeting patients aged 65 and older. We excluded non-transported cases, unknown severity assessments, and those deceased on initial evaluation. Patients were categorized into hospitalized (moderate to critical) and non-hospitalized (mild) groups. We analyzed demographics, accident type, location, prehospital care, and diagnosis. Logistic regression and inverse probability weighting were used to estimate risk differences (RDs) with 95% confidence intervals. This study analyzed 1.2 million older adults emergency transports in Tokyo, with 61% resulting in hospitalization. Hospitalized patients were older, more often male, and more frequently from care facilities. Cerebral diseases showed the highest risk difference for hospitalization (RD = 4.96), followed by cardiac and respiratory diseases. Cases with unspecified diagnoses accounted for 62% and were strongly associated with non-hospitalization (RD = 0.77). Severity profiles varied by disease, with moderate severity most common in cerebral cases and high severity in cardiac cases. Across all groups, emergency calls peaked between 9 and 10 a.m. This study identified disease-specific associations with hospitalization among older adults using emergency transport data in Tokyo. Even after adjustment, cerebral diseases remained strongly associated with hospitalization, while unspecified diagnoses were linked to non-hospitalization. These findings highlight the importance of prehospital assessment and may inform strategic improvements in triage and transport decision-making.

During a declared emergency, states may temporarily implement regulatory relief of overweight commercial motor vehicles to better assist emergency response activities. Often, emergencies go beyond state boundaries, with a need to harmonize activities with surround states, creating issues for freight and the trucking industry. The objectives of this research were to assist state truck permitting offices to (1) develop consistent definitions of emergencies, emergency commodities (classification/type), and other concepts; (2) identify successful practices, procedures, and processes for increasing weight limits during emergencies, including coordination and harmonization with neighboring jurisdictions; (3) develop a decision framework that considers different emergency scenarios that are linked with successful practices, procedures, and processes; and (4) highlight successful communication practices and training opportunities to conduct before emergencies occur. This paper focuses on issues faced by state oversize/overweight truck permitting agencies when trying to successfully implement regulatory relief of overweight commercial motor vehicle requirements during emergencies.

Improving survival and quality of life after cardiac arrest requires integrated systems of people, protocols, policies, and resources along with ongoing data acquisition and review. Such systems of care, which are highly influenced by the environment in which they operate, produce efficiency and effectiveness in responding to cardiac arrest. Part 4 of the 2025 American Heart Association Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care focuses on systems of care, emphasizing elements that are relevant to a broad range of resuscitation situations. The chapter follows the Chain of Survival, beginning with prevention and preparedness to resuscitate, proceeding to early identification of cardiac arrest, and moving to effective resuscitation through to post-cardiac arrest care, survivorship, and recovery. This Part provides cardiac arrest systems of care guidelines on how to train specific personnel, protocols that have been demonstrated to be effective, as well as the incorporation of nonhuman resources to optimize cardiac arrest care with ongoing debriefing and quality improvement strategies. Specific to out-of-hospital cardiac arrest, included are recommendations about emergency medical services team composition and transport recommendations, community initiatives to promote lay rescuer response, public access defibrillation and naloxone, and an enhanced role for emergency telecommunicators. Germane to in-hospital cardiac arrest are recommendations about cardiac arrest prevention and code team composition. Specific recommendations about extracorporeal membrane oxygenation cardiopulmonary resuscitation, transport to specialized cardiac arrest centers, organ donation, survivorship systems, and performance measurement across the continuum of resuscitation situations are also included.

Objectives In 2019, the Centers for Medicare and Medicaid Services (CMS) announced the Emergency Triage, Treat, and Transport (ET3) Model, an innovative care model aimed at increasing the quality and lowering the cost of emergency service care through telehealth services and alternative destination options for low-acuity cases. New York City (NYC) implemented ET3 protocols to enable broad adoption in the 9-1-1 system. The purpose of this study is to identify the characteristics, disposition of patients and challenges of the ET3 program in a single 9-1-1 emergency medical service (EMS) system. Methods Retrospective chart review of program data from one urban EMS service in NYC as per the inclusion/exclusion criteria in the local prehospital protocol including 1) rates of patients meeting criteria for an ET3 encounter; 2) rates of acceptance of ET3 telehealth treat-in-place encounters, 3) disposition of cases; 4) rates of return visits within 72 h. Results From August 2022–December 2023, 133,646 9-1-1 calls were answered. Of these, 78,911 (59%) were triaged for ET3, of which only 2,130 (3%) met inclusion criteria. Telehealth ET3 encounters were not offered to 1556 (73%). Of the remaining, 524 (92%) refused to participate in ET3 encounters, and 50 (9%) accepted. Of those who accepted, 31 (62%) were treated in place with telehealth, 15 (30%) were transported to the emergency department (ED), and 3 (6%) refused medical attention. Only 4 (13%) of those treated in place subsequently encountered an ED within 72 h. Conclusions The NYC EMS launch of the ET3 pilot was met with very low acceptance from eligible participants. The pilot helped to identify implementation challenges including proper personnel training, public outreach and awareness, and technological barriers. There is promise in avoiding transportation to the ED among those willing to participate with an even smaller rate of those requiring further unscheduled acute care. Our findings highlight limited offerings of ET3 encounters, and poor patient participation once offered. Further initiatives may consider workflow improvements and education to the public to improve willingness to participate.

To assess the association of patient and transport characteristics with mortality and morbidity of neonates who require interfacility transport in central Switzerland. We conducted a retrospective single-centre cohort study including neonates transported by the neonatal transport service of the Bern University Children՚s Hospital between January 2019 and December 2022. We reviewed the transport protocols and electronic patient charts of the hospitalisation after transport, and investigated the association of patient characteristics, clinical management before transport and transport characteristics (transport mode, transport times, adverse events) with outcomes. The primary outcome was death or impairment; secondary outcomes were lengths of stay in the intensive care unit and hospital, inotrope-free days and respiratory support-free days following transport. Of 807 neonates who were included, 105 (13%) showed an unfavourable outcome (death: 25 patients, impairment at time of discharge: 80). We observed a significant association between patients' diagnosis and primary outcome (p <0.001). Patients with a primary neurological disorder (n = 120, 14.9%) had a significantly higher risk of an unfavourable outcome (odds ratio [OR]: 5, 95% confidence interval [CI]: 2.46-10.9) compared to patients with a cardiac diagnosis. Death or impairment (primary outcome) was more likely to be observed in ground-transported patients than in air-transported patients (crude OR: 2.12, 95% CI: 1.20-4.07, p = 0.009). This effect remained significant after adjustment for the potential confounding effect of a selection of patient and administrative characteristics (adjusted OR: 2.23, 95% CI: 1.14-4.68, p = 0.018). Emergency transports, extended medical support before transport, a five-minute APGAR score <6 and a Sarnat score ≥2 were associated with an unfavourable outcome in the crude analysis, but not in the adjusted analysis. There was no significant association between stabilisation time or total transport time and primary outcome. Our study illustrates potential risk factors for morbidity and mortality in neonates requiring transport from the birth facility to a specialised neonatal care centre. The relevance of the primary diagnosis should influence logistical transport decision-making in the future. In particular, children with neurological diseases require special attention. As ground transport showed a worse outcome than air transport, the helicopter service might be considered more frequently. Transport times seem to be of less importance in regions with short transport distances, but optimising dispatch and call to arrival times would probably improve transport efficiency.

Quantum spin transport in integrable systems reveals a rich nonequilibrium phenomena that challenges the conventional hydrodynamic framework. Recent advances in ultracold atom experiments with state preparation and single-site addressing have enabled the understanding of this anomalous behavior. Particularly, the full universality characterization of exotic initial states, as well as their measurement representation, remain unknown. By employing tensor network and contrast methods, we systematically investigate spin transport in the quantum XXZ spin chain and extract dynamical scaling exponents emerging from two paradigmatic and experimentally attainable initial states, i.e., multi-periodic domain-wall (MPDW) and spin-helix (SH) states. Our results using different values of anisotropic parameters demonstrate the evident impeded transport and the difference between the two states with increasing values. Large-scale and consistent simulations confirm the contrast method as a viable scaling extraction approach for exotic states with periodicity within experimentally accessible timescales. Our work establishes a foundation for studying initial memory and the corresponding relations of emergent transport behavior in nonequilibrium quantum systems, opening avenues for the identification of their unique universality classes.