Search Results (35)

Background: Demand for Hamburg’s ambulance rescue system (ARS) in Germany, which is managed by the fire service, increased by more than 10% between 2019 and 2021. This increase was mainly driven by a more than 20% increase in non-critical ambulance rescues, while critical rescues decreased over the same period. Factors contributing to this trend include demographic changes, longer waiting times in primary care and declining quality in out-of-hospital care. To address this issue, the introduction of community emergency paramedics (CEPs)—who provide treatment and advice to patients at home before ambulance services are called—has been proposed as a potential solution to alleviate pressure on the ARS. Methods: In this study, 17 ARS stations in Hamburg, categorized into three operational areas (East, South, West), were analyzed using comprehensive statistical methods such as hypothesis testing, correlation analysis, regression modeling and clustering. Data from 2019 and 2021 were examined to assess the feasibility of integrating CEPs into the existing system. Results: Key findings identified specific stations with high potential for CEP support and optimal mission times (based on time of day, day of week and calendar week) to improve operational efficiency. The impact of regulatory measures introduced during the COVID-19 pandemic was also evident in the 2021 data. Conclusions: Finally, four policy scenarios—taking into account different synergy effects among the 17 stations—are presented, providing projections of the managerial and economic benefits for Hamburg policymakers. These policy implications aim to support the development of a robust CEP strategy to improve the overall efficiency and sustainability of the ARS. Full article

China’s population is aging rapidly, with a large proportion of elderly individuals “aging in place”. In central areas of large cities, the amount of community and home-based elderly care services provided by the government and for-profit organizations are insufficient to meet the demands of these “aging in place” elderly. Taking the core area of Beijing as the spatial scope, this empirical study collects the demand on services of the main types of elderly residents in community and home-based dwelling through questionnaires (n = 242) and employs a mixed-methods approach for analysis. Descriptive statistics and exploratory factor analysis are used to determine the categories and levels of those demands, and machine learning methods (random forest regression model) are used to calculate the importance of various influencing factors (features of the elderly and subdistricts’ built environment) on them. It is shown that elderly residents have a higher demand for psychological and physical condition maintenance services (mean = 3.40), and a lower demand for reconciliation and rights defense services (mean = 3.08). The results also show that the built environment factors are very important for the elderly on choosing demands, especially mean distance of CECSs (community elderly care stations) to downtown landmarks and main roads in subdistricts, and characteristics of CECS. The elderly’s own features also have a relatively important impact, especially their living arrangements, caregivers, and occupations before retirement. This study applies machine learning techniques to sociological survey analysis, helping to understand the intensity of elderly people’s demand for various community and home-based elderly care services. It provides a reference for the allocation of such service resources. Full article

This paper focuses on the perspectives of passengers who were railway users and how railways as a service can be uplifted with technological advancements through the introduction of information and communication technologies (ICTs). For this purpose, a questionnaire was designed comprised of six sections related to information on socio-economic-demographics, travel, station facilities, train facilities, customer care, and familiarity with and benefits of ICTs. A total of 800 respondents were recruited on trains and in railway stations to collect data through a random sampling technique. Data were analyzed through descriptive statistics, factor analysis, bivariate correlation analysis, and ordered logistic regression analysis. The three hypotheses tested showed that (i) there is a correlation between socio-demographic factors, train frequency, and satisfaction levels, (ii) satisfaction with station and train facilities and customer care impacts users’ travel likelihood with the train service, and (iii) users’ familiarity with perceived benefits of ICTs influences passengers’ travel likelihood with the train service. The results indicate that the users’ satisfaction with attributes of station facilities, train facilities, and customer care and perceptions about ICTs significantly influences their travel frequency with the train service. This study is useful for multiple stakeholders, especially for railway management authorities, to provide inclusive services to passengers and to plan for future transportation, which should be well-equipped with ICTs, well-integrated with other transport modes, and well-connected with optimum stops. Full article

One of the key features of mobile networks in this age of mobile communication is seamless communication. Handover (HO) is a critical component of next-generation (NG) cellular communication networks, which requires careful management since it poses several risks to quality-of-service (QoS), including a decrease in average throughput and service disruptions. Due to the dramatic rise in base stations (BSs) and connections per unit area brought about by new fifth-generation (5G) network enablers, such as Internet of things (IoT), network densification, and mm-wave communications, HO management has become more challenging. The degree of difficulty is increased in light of the strict criteria that were recently published in the specifications of 5G networks. In order to address these issues more successfully and efficiently, this study has explored and examined intelligent HO optimization strategies using machine learning models. Furthermore, the significant goal of this review is to present the state of cellular networks as they are now, as well as to talk about mobility and home office administration in 5G alongside the overall features of 5G networks. This work presents an overview of machine learning methods in handover optimization and of the various data availability for evaluations. In the final section, the challenges and future research directions are also detailed. Full article

The construction of community elderly care facilities (CECF) is pivotal for promoting healthy aging and “aging in place” for older people. This study focuses on the low utilization rates of community elderly care facilities in the Dongcheng and Xicheng Districts, core areas of Beijing. The explainable machine learning method is used to analyze data across three dimensions: the elderly’s individual attributes, characteristics of the community elderly care station (CECS), and features of the built environment around CECS and subdistrict, to identify the important factors that influence the usage frequency of overall CECS and its different functional spaces, and also the correlation between factors and usage frequency of CECS. It shows that the most important factors are the features of CSCF, including the degree of space acceptance and satisfaction with services provided, which influence the usage frequency of nine functional spaces (R² ≥ 0.68) and overall (R² = 0.56). In addition, older people’s individual factors, such as age and physical condition, significantly influence the usage of specific spaces such as rehabilitation therapy rooms and assistive bathing rooms. The influence of built environment characteristics is relatively low, with factors such as the density of bus stations and housing prices within the subdistrict and the mean distance from CECF to the nearest subway stations being more important. These findings provide a reference for the construction of indoor environments, management of service quality, and optimal site selection for future community elderly care facilities. Full article

In the field of modern healthcare, technology plays a crucial role in improving patient care and ensuring their safety. One area where advancements can still be made is in alert systems, which provide timely notifications to hospital staff about critical events involving patients. These early warning systems allow for swift responses and appropriate interventions when needed. A commonly used patient alert technology is nurse call systems, which empower patients to request assistance using bedside devices. Over time, these systems have evolved to include features such as call prioritization, integration with staff communication tools, and links to patient monitoring setups that can generate alerts based on vital signs. There is currently a shortage of smart systems that use sensors to inform healthcare workers about the activity levels of patients who are confined to their beds. Current systems mainly focus on alerting staff when patients become disconnected from monitoring machines. In this technical note, we discuss the potential of utilizing cost-effective sensors to monitor and evaluate typical movements made by hospitalized bed-bound patients. To improve the care provided to unaware patients further, healthcare professionals could benefit from implementing trigger alert systems that are based on detecting patient movements. Such systems would promptly notify mobile devices or nursing stations whenever a patient displays restlessness or leaves their bed urgently and requires medical attention. Full article

Deinstitutionalization of psychiatric care has been associated with increased homelessness, crime, and suicide, partly owing to insufficient, adequate, and accessible community resources. Therefore, appropriate resource placement is a key deinstitutionalization issue. The study’s aim was to identify residential group homes for people with mental illness in Kochi Prefecture, Japan, and the social resources necessary for social reintegration using a geographic information system (GIS). Everyday living areas (ELAs), as defined by the Japanese Community-Based Integrated Care System for People with Mental Illness (CICSM), were assessed using ELA location simulations. We used GIS to determine the spatial distribution of group homes, visiting nursing stations, psychiatric hospitals, daycare centers, and employment support offices. Following the CICSM definition of ELAs, we identified areas that people with mental illness could reach within 30 min on foot/by bicycle and counted the number of social resources in them. The ELA location simulation results suggest that policymakers should avoid uniform distribution of ELAs according to the CICSM definition. Establishing ELAs in suburban areas requires careful consideration of the available community resources, number of people with mental illness, existing support systems, and feasibility of the location. Full article

Plasmodium vivax cases represent more than 50% of a diminishing malaria case load in Vietnam. Safe and effective radical cure strategies could support malaria elimination by 2030. This study investigated the operational feasibility of introducing point-of-care quantitative glucose-6-phosphate dehydrogenase (G6PD) testing into malaria case management practices. A prospective interventional study was conducted at nine district hospitals and commune health stations in Binh Phuoc and Gia Lai provinces in Vietnam over the period of October 2020 to October 2021. The STANDARD™ G6PD Test (SD Biosensor, Seoul, Republic of Korea) was incorporated to inform P. vivax case management. Case management data and patient and health care provider (HCP) perspectives, as well as detailed cost data were collected. The G6PD test results were interpreted correctly by HCP and the treatment algorithm was adhered to for the majority of patients. One HCP consistently ran the test incorrectly, which was identified during the monitoring and resulted in provision of refresher training and updating of training materials and patient retesting. There was wide acceptability of the intervention among patients and HCP albeit with opportunities to improve the counseling materials. Increasing the number of facilities to which the test was deployed and decreases in the malaria cases resulted in higher per patient cost for incorporating G6PD testing into the system. Commodity costs can be reduced by using the 10-unit kits compared to the 25 unit kits, particularly when the case loads are low. These results demonstrate intervention feasibility while also highlighting specific challenges for a country approaching malaria elimination. Full article

Recently, micro base station antennas have begun to play a more important role in 5G wireless communication, with the rapid development of modern smart medical care, the Internet of things, and portable electronic devices. Meanwhile, in response to the global commitment to long-term carbon neutrality, graphene film has received significant attention in the field of antennas due to its low carbon environmental impact and high electrical conductivity properties. In this work, a conformal array antenna based on highly conductive graphene films (CGF) is proposed for 5G millimeter-wave (MMW) applications. The proposed antenna consists of three antenna arrays, with eight patch elements in each array, operating at 24 GHz, with linear polarization. Each antenna array’s current amplitude distribution coefficient is constructed by synthesizing a series-feeding linear array using the Chebyshev method. The measurement results demonstrated that the proposed CGF antenna exhibits a peak realized gain higher than 8 dBi in the bandwidth of 23.0–24.7 GHz. The proposed antenna achieves three independent beams from bore-sight to ±37° in conformal installations, with a cylinder radius of 30 mm, showing excellent beam-pointing performance. These characteristics indicate that the CGF can be used for the design of MMW micro base station antennas, fulfilling the requirements of the conformal carrier platform for a lightweight and compact antenna. Full article

There is a need to integrate advancements in biomedical, information, and communication technologies with care processes within the framework of the inpatient safety program to support effective risk management of adverse events occurring in the hospital environment and to improve inpatient safety. In this respect, this work presents the development of a software platform using the Scrum methodology and the integrated technology of the Internet of Things for monitoring and managing inpatient safety. A modular solution is developed under a hexagonal architecture, using PHP as the backend language through the Laravel framework. A MySQL database was used for the data layer, and Vue.js was used for the user interface. This work implemented an RFID-based nurse call system using Internet of Things (IoT) concepts. The system enables nurses to respond to each inpatient within a given time limit and without the inpatient or a family member having to approach the nursing station. The system also provides reports and indicators that help evaluate the quality of inpatient care and helps to take measures to improve inpatient safety during care. In addition, diet management is integrated to reduce the occurrence of adverse events. A LoRa and Wi-Fi-based IoT network was implemented using a LoRa transceiver and the ESP32 MCU, chosen for its low power consumption, low cost, and wide availability. Bidirectional communication between hardware and software is handled through an MQTT Broker. The system integrates temperature and humidity sensors and smoke sensors, among others. Full article

Wireless body area networks (WBANs) are a new advance utilized in recent years to increase the quality of human life by monitoring the conditions of patients inside and outside hospitals, the activities of athletes, military applications, and multimedia. WBANs consist of intelligent micro- or nano-sensors capable of processing and sending information to the base station (BS). Sensors embedded in the bodies of individuals can enable vital information exchange over wireless communication. Network forming of these sensors envisages long-term medical care without restricting patients’ normal daily activities as part of diagnosing or caring for a patient with a chronic illness or monitoring the patient after surgery to manage emergencies. This paper reviews WBAN, its security challenges, body sensor network architecture and functions, and communication technologies. The work reported in this paper investigates a significant security-level challenge existing in WBAN. Lastly, it highlights various mechanisms for increasing security and decreasing energy consumption. Full article

Multiservice cellular in Radio Access Network (RAN) Slicing has recently attained huge interest in enhancing isolation and flexibility. However, RAN slicing in heterogeneous networks (HetNet) architecture is not adequately explored. This study proposes a pairing-network slicing (NS) approach for Multiservice RAN that cares about quality of service (QoS), baseband resources, capacities of wireless fronthaul and backhaul links, and isolation. This intriguing approach helps address the increased need for mobile network traffic produced by a range of devices with various QoS requirements, including improved dependability, ultra-reliability low-latency communications (uRLLC), and enhanced broadband Mobile Services (eMBB). Our study displays a unique RAN slicing framework for user equipment (UE) for joint user-association. Multicell non-orthogonal multiple access (NOMA)-based resource allocation across 5G HetNet under successive interference cancelation (SIC) is seen to achieve the best performance. Joint user-slice pairing and association are optimization problems to maximize eMBB UE data rates while fulfilling uRLLC latency and reliability criteria. This is accomplished by guaranteeing the inter- and intra-isolation property of slicing to eliminate interferences between eMBB and uRLLC slices. We presented the UE-slice association (U-S. A) algorithm as a one-to-many matching game to create a stable connection between UE and one of the base stations (BSs). Next, we use the UE-slice pairing (U-S. P) algorithm to find stable uRLLC-eMBB pairs that coexist on the same spectrum. Numerical findings and performance analyses of the submitted association and pairing technique show they can all be RAN slicing criteria. We prove that the proposed algorithm optimizes system throughput while decreasing uRLLC latency by associating and pairing every uRLLC user in mini slots. Full article

The Community Care Station (CCS) service was initiated by the Taiwanese government as a part of its elderly social services programs. This study aimed to investigate the effects of using an inexpensive exercise toolkit, containing a stick, theraband, sandbag and a small ball, led by a physical therapist among community-dwelling older adults participating in CCS. A total of 90 participants (aged 77.0 ± 6.8 years) were recruited and divided into an intervention group (n = 45) and a comparison group (n = 45). The intervention group regularly participated in a health promotion program with the exercise toolkit for approximately 90 min per twice-weekly session for 3 months, and the comparison group maintained their usual CCS activity program. Both groups were assessed before and after the 3-month intervention period. Outcome measures included the Short Physical Performance Battery (SPPB), one-leg stance, functional reach (FR), Timed Up and Go (TUG), and 10 m walk tests; 83 participants completed the study. No significant between-group differences were found at baseline in general characteristics or outcome variables. After 3 months, the intervention group showed the significant group x time interaction effects in SPPB, one-leg stance, FR, TUG and 10 m walk tests compared to the comparison group (p < 0.05).; A structured group-based health promotion program using a low-cost exercise toolkit could be effective in improving the physical performances, balance, and walking ability of community-dwelling older adults receiving CCS program services. Furthermore, the comparison group maintained most of their physical performances, even showing significant progress on FR. Full article

SDG 10 stipulates that inequality within and between countries can be reduced by governmental policies that focus on the allocation of fiscal resources and social protection strategies to improve equity. The sustainability of community-based care stations is a crucial support network for achieving the goal of active aging. Unequal allocation would occur only if the populations of administrative districts are considered. Comprehensive policies, in accordance with data and sustainable goals, must consider multiple factors. Hence, this study used multicriteria decision making (MCDM) to investigate how nine criteria-related socioeconomic statuses (SES) and demographic characteristics are prioritized in community resource and funding allocation. Thirty-four community care and aging experts were invited to complete a questionnaire based on the modified Delphi method and the analytical hierarchy process (AHP) method. The assessment criteria for the allocation of community resources are prioritized in the following order: disability level, age, household composition, identity of social welfare, family income, ethnicity, marital status, educational attainment, and gender. Quantitative indices can be used to determine the importance of resource allocation policymaking. The benefit of this study lies in decision makers’ application of ranking and weighting values in public funding allocation ratios for community-based care resources for health equity in Taiwan. Full article

COVID-19 is a disease caused by a new coronavirus called SARS-CoV-2 and is an accidental global public health threat. Because of this, WHO declared the COVID-19 outbreak a pandemic. The pandemic is spreading unprecedently in Addis Ababa, which results in extraordinary logistical and management challenges in response to the novel coronavirus in the city. Thus, management strategies and resource allocation need to be vulnerability-oriented. Though various studies have been carried out on COVID-19, only a few studies have been conducted on vulnerability from a geospatial/location-based perspective but at a wider spatial resolution. This puts the results of those studies under question while their findings are projected to the finer spatial resolution. To overcome such problems, the integration of Geographic Information Systems (GIS) and Multi-Criteria Decision Analysis (MCDA) has been developed as a framework to evaluate and map the susceptibility status of the infection risk to COVID-19. To achieve the objective of the study, data like land use, population density, and distance from roads, hospitals, bus stations, the bank, markets, COVID-19 cases, health care units, and government offices are used. The weighted overlay method was used; to evaluate and map the susceptibility status of the infection risk to COVID-19. The result revealed that out of the total study area, 32.62% (169.91 km²) falls under the low vulnerable category (1), and the area covering 40.9% (213.04 km²) under the moderate vulnerable class (2) for infection risk of COVID-19. The highly vulnerable category (3) covers an area of 25.31% (132.85 km²), and the remaining 1.17% (6.12 km²) is under an extremely high vulnerable class (4). Thus, these priority areas could address pandemic control mechanisms like disinfection regularly. Health sector professionals, local authorities, the scientific community, and the general public will benefit from the study as a tool to better understand pandemic transmission centers and identify areas where more protective measures and response actions are needed at a finer spatial resolution. Full article