Search results for: smart hospital

Authors: Wegene Demisie Jima

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Leather is a durable and flexible material used for various purposes including clothing, footwear, upholstery and gloves. However, the use of leather for smart product applications is a challenge since it is electrically insulating material. Here, we report a simple method to produce conducting glove leathers using an in-situ polymerization of pyrrole. The concentrations of pyrrole, ferric chloride and anthraquinone-2-sulfonic acid sodium salt monohydrate were optimized to produce maximum conductivity in the treated leathers. The coating of polypyrrole in the treated leathers was probed using FT-IR, X-ray diffraction and electron microscopic analysis. FTIR confirms that the formation of polypyrrole on the leather surface as well as presence of prominent N-C stretching band. X-ray diffraction analysis suggests para-crystallinity in the PPy-treated leathers.We further demonstrate that the treated leathers, with maximum conductivity of 7.4 S/cm, can be used for making conductive gloves for operating touch-screen devices apart from other smart product applications.

Keywords: electrical conductivity, in-situ polymerization, pyrrole, smart product

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Authors: Bouami Hind, Millot Patrick

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The implementation of automated devices in life-critical systems such as hospitals can bring a new set of challenges related to automation malfunctions. While automation has been identified as great leverage for the medication dispensing system’s security and efficiency, it also increases the complexity of the organization. In particular, the installation and operation stage of automated devices can be complex when malfunctions related to automated systems occur. This paper aims to document operators’ situation awareness about the malfunctions of automated drug delivery systems (ADCs) during their implementation through Saint Brieuc hospital’s feedback. Our evaluation approach has been deployed in Saint Brieuc hospital center’s pharmacy, which has been equipped with automated nominative drug dispensing systems since January of 2021. The analysis of Saint Brieuc hospital center pharmacy’s automation revealed numerous malfunctions related to the implementation of Automated Delivery Cabinets. It appears that the targeted performance is not reached in the first year of implementation in this case study. Also, errors have been collected in patients' automated treatments’ production such as lack of drugs in pill boxes or nominative carnets, excess of drugs, wrong location of the drug, drug blister damaged, non-compliant sachet, or ticket errors. Saint Brieuc hospital center’s pharmacy is doing a tremendous job of setting up and monitoring performance indicators from the beginning of automation and throughout ADC’s operation to control ADC’s malfunctions and meet the performance targeted by the hospital. Health professionals, including pharmacists, biomedical engineers and directors of work, technical services and safety, are heavily involved in an automation project. This study highlights the importance of the evaluation of ADCs’ performance throughout the implementation process and the hospital’s team involvement in automation supervision and management.

Keywords: life-critical systems, situation awareness, automated delivery cabinets, implementation, risks and malfunctions

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Authors: Ismail Bile Hassan, Masrah Azrifah Azmi Murad

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This study discovers a novel framework of individual level technology adoption known as I-P (Individual- Privacy) towards Smart National Identity Card health information application. Many countries introduced smart national identity card (SNIC) with various applications such as health information application embedded inside it. However, the degree to which citizens accept and use some of the embedded applications in smart national identity remains unknown to many governments and application providers as well. Moreover, the previous studies revealed that the factors of trust, perceived risk, privacy concern and perceived credibility need to be incorporated into more comprehensive models such as extended Unified Theory of Acceptance and Use of Technology known as UTAUT2. UTAUT2 is a mainly widespread and leading theory existing in the information system literature up to now. This research identifies factors affecting the citizens’ behavioural intention to use health information application embedded in SNIC and extends better understanding on the relevant factors that the government and the application providers would need to consider in predicting citizens’ new technology acceptance in the future. We propose a conceptual framework by combining the UTAUT2 and Privacy Calculus Model constructs and also adding perceived credibility as a new variable. The proposed framework may provide assistance to any government planning, decision, and policy makers involving e-government projects. The empirical study may be conducted in the future to provide proof and empirically validate this I-P framework.

Keywords: unified theory of acceptance and use of technology (UTAUT) model, UTAUT2 model, smart national identity card (SNIC), health information application, privacy calculus model (PCM)

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Authors: Dedie Tooy, Rio Kolibu, Rio Putra, Herry Frits Pinatik, Daniel P. M. Ludong

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This study presents the design and development of a smart greenhouse prototype tailored to optimize Pak choi (Brassica chinensis L.) cultivation in tropical rural climates. Pak choi, a high-demand leafy vegetable in Indonesia, often experiences suboptimal growth due to elevated temperatures and humidity. The objective of this research is to design and develop an intelligent greenhouse to optimize pak choi cultivation in tropical rural climates. The design of a smart greenhouse provides a controlled environment to stabilize these conditions, but managing fluctuating temperature, humidity, and light in tropical regions remains challenging. This system regulates critical environmental factors, including temperature, humidity, irrigation system, and light, creating optimal conditions for Pak Choi. The prototype's effectiveness was evaluated by monitoring growth indicators such as leaf weight, freshness, and moisture content, alongside the consistency of the internal climate compared to external conditions. Results indicate that the smart greenhouse supports superior crop growth, enhances yield quality, and reduces environmental resource consumption. The irrigation control system test was carried out for 40 days. Researchers observed the results of the automatic system working according to the sensor value readings. The results of the temperature control system test work: when the air temperature in the greenhouse is more than 33 degrees, the condensation pump will turn on, and when the temperature is below 32 degrees, the pump will automatically turn itself off. The cycle repeats continuously. The results achieved pak coy can live up to 40 days. As part of our ongoing research, we are actively considering integrating double-layered roofs to improve insulation and reduce external temperature fluctuations, which could further enhance the effectiveness of the smart greenhouse.

Keywords: smart greenhouse, horticulture, rural tropical climate, sustainable agriculture

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Authors: Vineet Agrawal, Deepanjali S., Medha R., Subitha L.

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Background. Hospital malnutrition is a highly prevalent issue and is known to increase the morbidity, mortality, length of hospital stay, and cost of care. In India, studies on hospital malnutrition have been restricted to ICU, post-surgical, and cancer patients. We designed this study to assess the impact of hospital malnutrition on 30-day post-discharge and in-hospital mortality in patients admitted in the general medicine department, irrespective of diagnosis. Methodology. All patients aged above 18 years admitted in the medicine wards, excluding medico-legal cases, were enrolled in the study. Nutritional assessment was done within 72 h of admission, using Subjective Global Assessment (SGA), which classifies patients into three categories: Severely malnourished, Mildly/moderately malnourished, and Normal/well-nourished. Anthropometric measurements like Body Mass Index (BMI), Triceps skin-fold thickness (TSF), and Mid-upper arm circumference (MUAC) were also performed. Patients were followed-up during hospital stay and 30 days after discharge through telephonic interview, and their final diagnosis, comorbidities, and cause of death were noted. Multivariate logistic regression and cox regression model were used to determine if the nutritional status at admission independently impacted mortality at one month. Results. The prevalence of malnourishment by SGA in our study was 67.3% among 395 hospitalized patients, of which 155 patients (39.2%) were moderately malnourished, and 111 (28.1%) were severely malnourished. Of 395 patients, 61 patients (15.4%) expired, of which 30 died in the hospital, and 31 died within 1 month of discharge from hospital. On univariate analysis, malnourished patients had significantly higher morality (24.3% in 111 Cat C patients) than well-nourished patients (10.1% in 129 Cat A patients), with OR 9.17, p-value 0.007. On multivariate logistic regression, age and higher Charlson Comorbidity Index (CCI) were independently associated with mortality. Higher CCI indicates higher burden of comorbidities on admission, and the CCI in the expired patient group (mean=4.38) was significantly higher than that of the alive cohort (mean=2.85). Though malnutrition significantly contributed to higher mortality on univariate analysis, it was not an independent predictor of outcome on multivariate logistic regression. Length of hospitalisation was also longer in the malnourished group (mean= 9.4 d) compared to the well-nourished group (mean= 8.03 d) with a trend towards significance (p=0.061). None of the anthropometric measurements like BMI, MUAC, or TSF showed any association with mortality or length of hospitalisation. Inference. The results of our study highlight the issue of hospital malnutrition in medicine wards and reiterate that malnutrition contributes significantly to patient outcomes. We found that SGA performs better than anthropometric measurements in assessing under-nutrition. We are of the opinion that the heterogeneity of the study population by diagnosis was probably the primary reason why malnutrition by SGA was not found to be an independent risk factor for mortality. Strategies to identify high-risk patients at admission and treat malnutrition in the hospital and post-discharge are needed.

Keywords: hospitalization outcome, length of hospital stay, mortality, malnutrition, subjective global assessment (SGA)

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Authors: Panaya Sudta, Wanchalerm Patanacharoenwong, Prachya Bumrungkun

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As With the evolution of smart grids, ensuring the reliability and efficiency of electrical systems in smart cities has become crucial. This paper proposes a distinct approach that combines advanced machine learning techniques to accurately predict electrical failures and address voltage reliability issues. This approach aims to improve the accuracy and efficiency of reliability evaluations in smart cities. The aim of this research is to develop a comprehensive predictive model that accurately predicts electrical failures and voltage reliability in smart cities. This model integrates RFM analysis, K-means clustering, and LSTM networks to achieve this objective. The research utilizes RFM analysis, traditionally used in customer value assessment, to categorize and analyze electrical components based on their failure recency, frequency, and monetary impact. K-means clustering is employed to segment electrical components into distinct groups with similar characteristics and failure patterns. LSTM networks are used to capture the temporal dependencies and patterns in customer data. This integration of RFM, K-means, and LSTM results in a robust predictive tool for electrical failures and voltage reliability. The proposed model has been tested and validated on diverse electrical utility datasets. The results show a significant improvement in prediction accuracy and reliability compared to traditional methods, achieving an accuracy of 92.78% and an F1-score of 0.83. This research contributes to the proactive maintenance and optimization of electrical infrastructures in smart cities. It also enhances overall energy management and sustainability. The integration of advanced machine learning techniques in the predictive model demonstrates the potential for transforming the landscape of electrical system management within smart cities. The research utilizes diverse electrical utility datasets to develop and validate the predictive model. RFM analysis, K-means clustering, and LSTM networks are applied to these datasets to analyze and predict electrical failures and voltage reliability. The research addresses the question of how accurately electrical failures and voltage reliability can be predicted in smart cities. It also investigates the effectiveness of integrating RFM analysis, K-means clustering, and LSTM networks in achieving this goal. The proposed approach presents a distinct, efficient, and effective solution for predicting and mitigating electrical failures and voltage issues in smart cities. It significantly improves prediction accuracy and reliability compared to traditional methods. This advancement contributes to the proactive maintenance and optimization of electrical infrastructures, overall energy management, and sustainability in smart cities.

Keywords: electrical state prediction, smart grids, data-driven method, long short-term memory, RFM, k-means, machine learning

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Authors: M. R. Ebrahimi, B. Mahdaviani

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Conventional electric distribution systems are radial in nature, supplied at one end through a main source. These networks generally have a simple protection system usually implemented using fuses, re-closers, and over-current relays. Recently, great attention has been paid to applying Distributed energy resources (DERs) throughout electric distribution systems. Presence of such generation in a network leads to losing coordination of protection devices. Therefore, it is desired to develop an algorithm which is capable of protecting distribution systems that include DER. On the other hand smart grid brings opportunities to the power system. Fast advancement in communication and measurement techniques accelerates the development of multi agent system (MAS). So in this paper, a new approach for the protection of distribution networks in the presence of DERs is presented base on MAS. The proposed scheme has been implemented on a sample 27-bus distribution network.

Keywords: distributed energy resource, distribution network, protection, smart grid, multi agent system

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Authors: Maciej Jedrzejczyk, Karolina Marzantowicz

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Traditional utility value chain is being transformed during last few years into unbundled markets. Increased distributed generation of energy is one of considerable challenges faced by Smart Grid networks. New sources of energy introduce volatile demand response which has a considerable impact on traditional middlemen in E&U market. The purpose of this research is to search for ways to allow near-real-time electricity markets to transact with surplus energy based on accurate time synchronous measurements. A proposed framework evaluates the use of secure peer-2-peer (P2P) communication and distributed transaction ledgers to provide flat hierarchy, and allow real-time insights into present and forecasted grid operations, as well as state and health of the network. An objective is to achieve dynamic grid operations with more efficient resource usage, higher security of supply and longer grid infrastructure life cycle. Methods used for this study are based on comparative analysis of different distributed ledger technologies in terms of scalability, transaction performance, pluggability with external data sources, data transparency, privacy, end-to-end security and adaptability to various market topologies. An intended output of this research is a design of a framework for safer, more efficient and scalable Smart Grid network which is bridging a gap between traditional components of the energy network and individual energy producers. Results of this study are ready for detailed measurement testing, a likely follow-up in separate studies. New platforms for Smart Grid achieving measurable efficiencies will allow for development of new types of Grid KPI, multi-smart grid branches, markets, and businesses.

Keywords: autonomous agents, Distributed computing, distributed ledger technologies, large scale systems, micro grids, peer-to-peer networks, Self-organization, self-stabilization, smart grids

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Authors: Ali Mohammad Mobaser Azad, Alireza Akhlaghinia

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Blockchain is changing our world and launching a new generation of decentralized networks. Meanwhile, Blockchain-based networks like Ethereum have been created and they will facilitate these processes using tools like smart contracts. The Ethereum has fundamental structures, each of which affects the activity of the nodes. Our purpose in this paper is to review similar research and examine various components to demonstrate the performance of the Ethereum network and to do this, and we used the data published by the Ethereum Foundation in different time spots to examine the number of changes that determine the status of network performance. This will help other researchers understand better Ethereum in different situations.

Keywords: blockchain, ethereum, smart contract, decentralization consensus algorithm

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Authors: Saurav Dhawan, Sanchit Bansal

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Background T-MACS is a computer-based decision aid that ‘rules in’ and ‘rules out’ ACS using a combination of the presence or absence of six clinical features with only one biomarker measured on arrival: hs-cTnT. T-MACS had 99.3% negative predictive value and 98.7% sensitivity for ACS, ‘ruling out’ ACS in 40% of patients while ‘ruling in’ 5% at the highest risk. We aim at benchmarking the use of T-MACS which could help to conserve healthcare resources, facilitate early discharges, and ensure safe practice. Methodology Randomized retrospective data collection (n=300) was done from ED electronic records across 3 hospital sites within MFT over a period of 2 months. Data was analysed and compared by percentage for the usage of T-MACS, number of admissions/discharges, and in days for length of stay in hospital. Results MRI A&E had the maximum compliance with the use of T-MACS in the trust at 66%, with minimum admissions (44%) and an average length of stay of 1.825 days. NMG A&E had an extremely low compliance rate (8 %), with 75% admission and 3.387 days as the average length of stay. WYT A&E had no TMACS recorded, with a maximum of 79% admissions and the longest average length of stay at 5.07 days. Conclusion All three hospital sites had a RAG rating of ‘RED’ as per the compliance levels. The assurance level was calculated as ‘Very Limited’ across all sites. There was a positive correlation observed between compliance with TMACS and direct discharges from ED, thereby reducing the average length of stay for patients in the hospital.

Keywords: ACS, discharges, ED, T-MACS

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Authors: Julian Donovan, Jessica Brealey, Matthew Bowker, Marianne Feghali, Gregory Smith, Lee Thompson, Deborah Henderson

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This article details the development of the X-ray response team (XRT), a service that utilises innovative technology to safely deliver acute and elective imaging and medical assessment service in the pre-hospital and community setting. This involves a partnership between Northumbria Healthcare NHS Foundation Trust’s Radiology and Emergency Medicine departments and the North East Ambulance Service to create a multidisciplinary prehospital team. The team committed to the delivery of a two-day acute service every week, alongside elective referrals, starting in November 2020. The service was originally made available to a 15-mile radius surrounding the Northumbria Hospital. Due to demand, this was expanded to include the North Tyneside and Northumberland regions. The target population was specified as frail and vulnerable patients, as well as those deemed to benefit from staying in their own environment. Within the first two months, thirty-six percent of patients assessed were able to stay at home due to the provision of off-site imaging. In the future, this service aims to allow patient transfer directly to an appropriate ward or clinic, bypassing the emergency department to improve the patient journey and reduce emergency care pressures.

Keywords: frailty, imaging, pre-hospital, X-ray

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Authors: Y. Y. Babanyara, D. B. Ibrahim, T. Garba

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Proper management of medical waste is a crucial issue for maintaining human health and the environment. The waste generated in the hospitals has the potential for spreading infections and causing diseases. The study is aimed at assessing the medical waste management practices in Nigeria. Three instruments, questionnaire administration, in-depth interview and observation method for data collection were adopted in the study. The results revealed that the hospital does not quantify medical waste. Segregation of medical wastes is not conducted according to definite rules and standards. Wheeled trolleys are used for on-site transportation of waste from the points of production to the temporary storage area. Offsite transportation of the hospital waste is undertaken by a private waste management company. Small pickups are mainly used to transport waste daily to an off-site area for treatment and disposal. The main treatment method used in the final disposal of infectious waste is incineration. Non-infectious waste is disposed off using land disposal method. The study showed that the hospital does not have a policy and plan in place for managing medical waste. The study revealed number of problems the hospital faces in terms of medical waste management, including; lack of necessary rules, regulations and instructions on the different aspects of collections and disposal of waste, failure to quantify the waste generated in reliable records, lack of use of coloured bags by limiting the bags to only one colour for all waste, the absence of a dedicated waste manager, and no committee responsible for monitoring the management of medical waste. Recommendations are given with the aim of improving medical waste management in the hospital.

Keywords: medical waste, treatment, disposal, public health

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Authors: Murtadha Kareem, Oliver Faust

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Wearable biosensor systems can be designed and developed for health monitoring. There is much interest in both scientific and industrial communities established since 2007. Fundamentally, the cost of healthcare has increased dramatically and the world population is aging. That creates the need to harvest technological improvements with small bio-sensing devices, wireless-communication, microelectronics and smart textiles, that leads to non-stop developments of wearable sensor based systems. There has been a significant demand to monitor patient's health status while the patient leaves the hospital in his/her personal environment. To address this need, there are numerous system prototypes which has been launched in the medical market recently, the aim of that is to provide real time information feedback about patient's health status, either to the patient himself/herself or direct to the supervising medical centre station, while being capable to give a notification for the patient in case of possible imminent health threatening conditions. Furthermore, wearable health monitoring systems comprise new techniques to address the problem of managing and monitoring chronic heart diseases for elderly people. Wearable sensor systems for health monitoring include various types of miniature sensors, either wearable or implantable. To be specific, our proposed system able to measure essential physiological parameter, such as heart rate signal which could be transmitted through Bluetooth to the cloud server in order to store, process, analysis and visualise the data acquisition. The acquired measurements are connected through internet of things to a central node, for instance an android smart phone or tablet used for visualising the collected information on application or transmit it to a medical centre.

Keywords: Wearable sensor, Heart rate, Internet of things, Chronic heart disease

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Authors: Nida Amin, Fahad Tanveer, Hina Shabbir, Ayesha Saeed, Attiqa Riaz

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The gradual progression of corneal disorder keratoconus significantly impairs eyesight and quality of life, increasing the likelihood of depression. Using the Hospital Anxiety and Depression Scale (HADS) at the AL-Ibrahim Eye Hospital in Karachi, this study aimed to evaluate the occurrence of depression and anxiety symptoms in patients with keratoconus and to suggest better treatment. A descriptive-analytical study was conducted at Al-Ibrahim Eye Hospital Karachi from March to April 2022, and patients diagnosed with symptomatic keratoconus were recruited using a non-probability convenient sampling technique. After obtaining written informed consent from patients, keratoconus severity was assessed using visual acuity and corneal topography. Symptoms of anxiety and depression were assessed using the Hospital Anxiety and Depression (HADS) Scale. The data were analyzed using SPSS version 20.0. Spearman correlation coefficient. Of the 108 participants, 60 (56%) were female and 48 (44%) were male. Using the HADS scale, 44 (40.7%) patients were classified as normal with a HADS score of (0-7), 23 (21.3%) as borderline with a HADS score of (8-10) and 41 (38%) patients were diagnosed with anxiety and depression with a HADS score of (11-21). Depression and anxiety are highly prevalent among patients in advanced stages of the disease.

Keywords: cornea, keratoconus, anxiety, depression, corneal topography, mental health

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Authors: Yonathan Audhitya Suthihono, Ratih Dyah Kusumastuti

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The radiology department in a tertiary referral hospital faces service operation challenges such as huge and various patient arrival, which can increase the probability of patient queuing. During the COVID-19 pandemic, it is mandatory to apply social distancing protocol in the radiology department. A strategy to prevent the accumulation of patients at one spot would be required. The aim of this study is to identify an alternative solution which can reduce the patient’s waiting time in radiology department. Discrete event simulation (DES) is used for this study by constructing several improvement scenarios with Arena simulation software. Statistical analysis is used to test the validity of the base case scenario model and to investigate the performance of the improvement scenarios. The result of this study shows that the selected scenario is able to reduce patient waiting time significantly, which leads to more efficient services in a radiology department, be able to serve patients more effectively, and thus increase patient satisfaction. The result of the simulation can be used by the hospital management to improve the operational performance of the radiology department.

Keywords: discrete event simulation, hospital management patient queuing model, radiology department services

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Authors: Safwan Mawlood Hussien

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Internet of Things (IoT) is a promising technology has received considerable attention in different fields such as health, industry, defence, and agro, etc. Due to the limitation capacity of computing, storage, and communication, IoT objects are more vulnerable to attacks. Many solutions have been proposed to solve security issues, such as key management using symmetric-key ciphers. This study provides a scalable group distribution key management based on ECcryptography; with less transmitted messages The method has been validated through simulations in OMNeT++.

Keywords: elliptic curves, Diffie–Hellman, discrete logarithm problem, secure key exchange, WSN security, IoT security, smart-agro

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Authors: Guo Yu, Haoming Ma, Peiru Zhou

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BACKGROUND: In addition to hyperglycemia, hypoglycemia, and glycemic variability, a decrease in the time in the targeted blood glucose range (TIR) may be associated with an increased risk of death for critically ill patients. However, the relationship between the TIR and mortality may be influenced by the presence of diabetes and glycemic variability. METHODS: A total of 998 diabetic and non-diabetic patients with severe diseases in the ICU were selected for this retrospective analysis. The TIR is defined as the percentage of time spent in the target blood glucose range of 3.9–10.0 mmol/L within 24 hours. The relationship between TIR and in-hospital in diabetic and non-diabetic patients was analyzed. The effect of glycemic variability was also analyzed. RESULTS: The binary logistic regression model showed that there was a significant association between the TIR as a continuous variable and the in-hospital death of severely ill non-diabetic patients (OR=0.991, P=0.015). As a classification variable, TIR≥70% was significantly associated with in-hospital death (OR=0.581, P=0.003). Specifically, TIR≥70% was a protective factor for the in-hospital death of severely ill non-diabetic patients. The TIR of severely ill diabetic patients was not significantly associated with in-hospital death; however, glycemic variability was significantly and independently associated with in-hospital death (OR=1.042, P=0.027). Binary logistic regression analysis of comprehensive indices showed that for non-diabetic patients, the C3 index (low TIR & high CV) was a risk factor for increased mortality (OR=1.642, P<0.001). In addition, for diabetic patients, the C3 index was an independent risk factor for death (OR=1.994, P=0.008), and the C4 index (low TIR & low CV) was independently associated with increased survival. CONCLUSIONS: The TIR of non-diabetic patients during ICU hospitalization was associated with in-hospital death even after adjusting for disease severity and glycemic variability. There was no significant association between the TIR and mortality of diabetic patients. However, for both diabetic and non-diabetic critically ill patients, the combined effect of high TIR and low CV was significantly associated with ICU mortality. Diabetic patients seem to have higher blood glucose fluctuations and can tolerate a large TIR range. Both diabetic and non-diabetic critically ill patients should maintain blood glucose levels within the target range to reduce mortality.

Keywords: severe disease, diabetes, blood glucose control, time in targeted blood glucose range, glycemic variability, mortality

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Authors: Caroline Correia, Stefani Perna, John Gaughan, Elizabeth Cerceo

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Introduction: The COVID-19 pandemic has brought unprecedented changes to how hospitals function on a daily basis. Increased personal protective equipment (PPE) usage and measures to pre-package, separate, and decontaminate have the potential to increase the waste load. However, limiting non-essential surgeries drastically reduces operating room (OR) waste, and restricting visitation policies to contain outbreaks may help conserve resources. The impact of these policy changes with increased disposable PPE usage on hospital production of waste is unknown. Methods: Waste produced in pounds (lbs) was measured for January through June during both 2019 and 2020 through Stericycle in Cooper University Hospital in Camden, NJ. This timeframe was selected since the pandemic began in January 2020 in the US. The total waste produced during this time was 328,623 lbs in 2019 and 306,454 lbs in 2020. Using Poisson counts (α=.05), less waste was produced in 2020 (p < 0.001). The amount of sharps and regulated medical waste (grossly bloody items) were both significantly decreased as well (p < 0.0001, p=0.0002), and these account for 10-15% of the total waste produced. Discussion: Despite the increased usage of disposable PPE, overall hospital waste was decreased during the pandemic as compared to prior. As surgeries are estimated to be responsible for up to one-half of waste produced by hospitals, it is possible that constraint on elective procedures contributed to the decreased waste in all three categories; estimates of a 35% decrease in surgical volume would be expected to impact waste production. The effects of the pandemic on waste production should continue to be monitored to understand the environmental impact as health systems resume backlogged surgeries at a higher volume.

Keywords: COVID-19, hospital, surgery, waste

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Authors: G. R. Constantine, M.C.K. Thilakasiri, V.S. Mohottala, T.V. Soundaram, D.S. Rathnayake, E.G.H.E. De Silva, A.L.S. Mohamed, V.R. Weerasekara

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Orthostatic hypotension is prevalent in the elderly population, and it is an important risk factor contributing to falls in the elderly. This study aims to evaluate the prevalence of orthostatic hypotension in hospitalized elderly patients, changes in blood pressure during the hospital stay, morbidities associated with it and its association with falls in the elderly. A cross-sectional descriptive study was conducted in the National Hospital of Sri Lanka (NHSL) in a sample of 120 patients of age 65 years or above who were admitted to the medical wards. The demographic, clinical data was obtained by an interviewer-administered questionnaire. Two validated questionnaires were used to assess symptoms and effects of orthostatic hypotension and risk factors associated with falls. Orthostatic hypotension on admission and after 3 days of hospital stay was measured by bed-side mercury sphygmomanometer. Prevalence of orthostatic hypotension among the study population was 63.3%(76 patients). But no significant change in the orthostatic hypotension noted after 3 days of hospital admission (SND 0.61, SE= 5.59, p=0.27). There was no significant association found between orthostatic hypotension and its symptoms (dizziness and vertigo, vision problems, malaise, fatigue, poor concentration, neck stiffness), impact on standing or walking and non-communicable diseases. Falls were experienced by 27.5 % (33 patients) of the study population and prevalence of patients with orthostatic hypotension who had experienced falls was 25.9% (28 patients). In conclusions, orthostatic hypotension is more prevalent among elderly patients, but It wasn’t associated with symptoms, and non-communicable diseases, or as a risk factor for falls in elderly.

Keywords: orthostatic hypotension, elderly falls, emergency geriatric, Sri Lanka

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Authors: Eu Tteum Ha, Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

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The smart home environment backed up by IoT (internet of things) technologies enables intelligent services based on the awareness of the situation a user is currently in. One of the convenient sensors for recognizing the situations within a home is the smart meter that can monitor the status of each electrical appliance in real time. This paper aims at learning a Bayesian network that models the causal relationship between the user situations and the status of the electrical appliances. Using such a network, we can infer the current situation based on the observed status of the appliances. However, learning the conditional probability tables (CPTs) of the network requires many training examples that cannot be obtained unless the user situations are closely monitored by any means. This paper proposes a method for learning the CPT entries of the network relying only on the user feedbacks generated occasionally. In our case study with a robot vacuum cleaner, the feedback comes in whenever the user gives an order to the robot adversely from its preprogrammed setting. Given a network with randomly initialized CPT entries, our proposed method uses this feedback information to adjust relevant CPT entries in the direction of increasing the probability of recognizing the desired situations. Simulation experiments show that our method can rapidly improve the recognition performance of the Bayesian network using a relatively small number of feedbacks.

Keywords: Bayesian network, IoT, learning, situation -awareness, smart home

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Authors: Karina Peron, Ricardo Ghelman, Monica Taminato, Katia R. Oliveira, Debora C. A. Rodrigues, Juliana R. C. Mumme, Olga K. M. Sunakozaua, Georg Seifert, Vicente O. Filho

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The nurse is the most available health professional for the interventions of support in the integrative approach in hospital environment, therefore a professional group key to changes in the model of care. The central components in the performance of anthroposophic nursing procedures are direct physical contact, promotion of proper rhythm, thermal regulation and the construction of a calm and empathic atmosphere, safe for patients and their caregivers. The procedures of anthroposophic external therapies (AET), basically composed of the application of compresses and the use of natural products, provide an opportunity to intensify the therapeutic results through an innovative, complementary and integrative model in the university hospital. The objective of this work is to report the implementation of a program of nursing techniques (AET) through a partnership between the Pediatric Oncology Sector of the Department of Pediatrics of the Faculty of Medicine of the University of Sao Paulo and Charite University of Berlin, with lecturers from Berlin's Integrative Hospital Havelhöhe and Witten-Herdecke Integrative Hospital, both in Germany. Intensive training activities of the Hospital's nursing staff and a survey on AET needs were developed based on the most prevalent complaints in pediatric oncology patients in the three environments of the Hospital of Pediatric Oncology: Bone Marrow Transplantation Unit, Intensive Care Unit and Division of Internal Patients. We obtained the approval of the clinical protocol of external anthroposophic therapies for nursing care by the Ethics Committee and the Academic Council of the Hospital. With this project, we highlight the key AET needs that will be part of the standard program of pediatric oncology care with appropriate scientific support. The results of the prevalent symptoms were: vomiting, nausea, pain, difficulty in starting sleep, constipation, cold extremities, mood disorder and psychomotor agitation. This project was the pioneer within the Integrative Pediatrics Program, as an innovative concept of Medicine and Integrative Health presented at scientific meetings.

Keywords: integrative health care, integrative nursing, pediatric nursing, pediatric oncology

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Authors: Ihaddadene Thanina, Haraoubia Imane, Baouni Tahar

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Urban mobility is one of the first challenges of cities; it is becoming more and more problematic because it is perceived as the cause of many dysfunctions; it is not only to facilitate accessibility but also to ensure vast benefits. For this reason, several cities in the world have thought about alternatives to smart mobility and sustainable transport. Today, the sustainable city has many cards at its disposal, and a new mode is entering the urban scene: aerial cable transport; it has imposed itself as an effective mode of public transport and a real solution for the future. This electric mobility brings a new dimension, not only to collective daily travel but also to the urban space. It has an excellent capacity to redevelop the public space; it is a catalyst that allows one to appreciate the view from the sky and to discover different large-scale projects that bring an important attractiveness to the city. With regard to the cities in the world which use these systems of transport: Algeria does not escape this reality; it is the country which has the greatest number of devices of urban transport by cable in the world, with installations in many cities such as Tlemcen, Constantine, Blida, Oran, Tizi-Ouzou, Annaba, Skikda. The following study explores the role of cable transport in the transformation of the city of Algiers into a smart city. The methodology used in this work is based on the development of a set of indicators using a questionnaire survey. The main objective of this work is to shed light on cable transport as a key issue in designing the sustainable city of tomorrow, to evaluate its role in the city of Algiers, and its ability to integrate into the urban transport network.

Keywords: Algiers, cable transport, indicators, smart city

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Authors: Afolakemi Helen Olaleye, Ogunjobi A. O

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Since coronavirus disease 2019 (COVID-19) was first reported in Nigeria, the virus has spread to virtually all sub-Saharan Africa (SSA) countries. In Nigeria, government agencies came together to create a goal-driven taskforce in improving our response against the virus. As COVID-19 international spread has been curtailed, community spread became rampant locally, leading to many health authorities raising concerns over the scarcity of medical consumables and supplies. Here at Lagos university teaching Hospital (LUTH), we present data analysis of COVID-19 infections offered at our Hospital (LUTH) and the surrounding communities. In addition, the adopted innovative solution to control the spread of infection, methods used in filling shortages of consumables, personal protective equipment (PPE), and use of mobile video technology in patient’s consultation. The management style and strategy adopted has led to a decline in infection rates in our community and among our front line staff. The current COVID -19 crisis has created an opportunity to test and demonstrate our pandemic response and control of infectious disease along with the revealed unknown potential in our community.

Keywords: COVID-19, preparedness, response, Lagos university teaching hospital

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Authors: Caroline Atef Shoukry Tadros

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Massive Urbanization growth threatens the sustainability of cities and the quality of city life. This raised the need for an alternate model of sustainability, so we need to plan the future cities in a smarter way with smarter mobility. Smart Mobility planning applications are solutions that use digital technologies and infrastructure advances to improve the efficiency, sustainability, and inclusiveness of urban transportation systems. They can contribute to meeting the needs of Urbanization growth by addressing the challenges of traffic congestion, pollution, accessibility, and safety in cities. Some example of a Smart Mobility planning application are Mobility-as-a-service: This is a service that integrates different transport modes, such as public transport, shared mobility, and active mobility, into a single platform that allows users to plan, book, and pay for their trips. This can reduce the reliance on private cars, optimize the use of existing infrastructure, and provide more choices and convenience for travelers. MaaS Global is a company that offers mobility-as-a-service solutions in several cities around the world. Traffic flow optimization: This is a solution that uses data analytics, artificial intelligence, and sensors to monitor and manage traffic conditions in real-time. This can reduce congestion, emissions, and travel time, as well as improve road safety and user satisfaction. Waycare is a platform that leverages data from various sources, such as connected vehicles, mobile applications, and road cameras, to provide traffic management agencies with insights and recommendations to optimize traffic flow. Logistics optimization: This is a solution that uses smart algorithms, blockchain, and IoT to improve the efficiency and transparency of the delivery of goods and services in urban areas. This can reduce the costs, emissions, and delays associated with logistics, as well as enhance the customer experience and trust. ShipChain is a blockchain-based platform that connects shippers, carriers, and customers and provides end-to-end visibility and traceability of the shipments. Autonomous vehicles: This is a solution that uses advanced sensors, software, and communication systems to enable vehicles to operate without human intervention. This can improve the safety, accessibility, and productivity of transportation, as well as reduce the need for parking space and infrastructure maintenance. Waymo is a company that develops and operates autonomous vehicles for various purposes, such as ride-hailing, delivery, and trucking. These are some of the ways that Smart Mobility planning applications can contribute to meeting the needs of the Urbanization growth. However, there are also various opportunities and challenges related to the implementation and adoption of these solutions, such as the regulatory, ethical, social, and technical aspects. Therefore, it is important to consider the specific context and needs of each city and its stakeholders when designing and deploying Smart Mobility planning applications.

Keywords: smart mobility planning, smart mobility applications, smart mobility techniques, smart mobility tools, smart transportation, smart cities, urbanization growth, future smart cities, intelligent cities, ICT information and communications technologies, IoT internet of things, sensors, lidar, digital twin, ai artificial intelligence, AR augmented reality, VR virtual reality, robotics, cps cyber physical systems, citizens design science

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Authors: Ngozi N. Sydney-Agbor, Chioma N. Ihegboro

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Stress and personality as factors influencing nurses’ aggressive behaviour were investigated. The participants comprised of one hundred and fifty nurses selected through convenience sampling technique from four (4) private hospitals in Imo State, Nigeria; namely: Eastern Summit Specialist Clinics and Maternity, St. David Hospital, New Cross Hospital, and Christian Teaching Hospital. The nurses were all females with ages between 20–35 and a mean age of 25.10 years and a standard deviation of 4.15. The participants were administered with Job Related Tension Scale, Type A Behaviour Scale and Buss- Perry Aggressive Behaviour Scale. Two hypotheses were postulated and tested. Cross- sectional survey and Regression Analysis were adopted as design and statistics respectively. Results showed that as stress increased, nurses aggression also increased. Personality also predicted nurses aggressive behaviour with Type As’ exhibiting higher aggression than Type Bs’.The study recommended that hospital management board should improve the welfare of the nurses and their morale should be boosted by involving them in policy-making concerning their welfare and care of their patients, this will help minimise situations capable of increasing aggressive behaviour. There should also be sensitization on the negative impact of aggressive behaviour to patients especially amongst the personality Type A’s who are more susceptible to aggression.

Keywords: aggressive behaviour, nurses, personality, stress

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Authors: Mariana Floria, Elena-Diana Năfureanu, Diana-Mihaela Gălăţanu, Anca-Ecaterina Grumeza, Cristina Gorea-Bocîncă, Diana-Elena Iov, Aurelian-Corneliu Moraru, Dragoș-Marian Popescu

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SARS-CoV-2 is the most deadly and devastating virus of the last one hundred years, being more highly contagious than EBOLA, HIV, Swine Influenza, Severe Acute Respiratory Syndrome, or Middle Eastern Respiratory Syndrome. After two years of pandemic, planning and budgeting for use of healthcare resources and services is very important. The aim of this study was to analyze the costs for hospital stay in patients with predominantly moderate forms of COVID-19 in a support military hospital located in Nord-East of Romania. Inpatient COVID-19 hospitalizations costs, regardless of ICD-10 procedure codes (DRG payment), in a Covid-19 support military hospital were analyzed. From August 2020 through June 2021, 241 patientswere hospitalized. Our national protocol for the treatment of Covid-19 infection was applied. The main COVID-19 manifestations were: 69% respiratory (18% with severe pneumonia, 2.9% with pulmonary embolism, diagnosed by angio-computed tomography), 3.3% cardiac, 28% digestive, and 33% psychiatric (most common anxiety) manifestations. According to COVID-19 severity, most of the patients had moderate (104 patients – 43%) and severe (50 patients - 21%) forms. Seven patients with severe form died because of multiple comorbidities, and 30 patients were transferred in hospitals with COVID-19 intensive care units.Only two patients have had procalcitonin>10 ng/mL (high probability of severe sepsis or septic shock), and 1 patient had moderate risk for septic shock (0.5 - 2 ng/mL). The average estimated costs were about 3000€/patient, without significantly differences depending on disease severity. Equipment costs were 2 times higher than for drugs and 4 times than for laboratory tests. In a Covid-19 support military hospital that took care for predominantly moderate forms of COVID-19, the costs for equipment were much higher than that for treatment. Therefore, new criteria for hospitalization of these forms of COVID-19 deserve to be analyzed to avoid useless costs.

Keywords: Covid-19, costs, hospital stay, military hospital

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Authors: Phan Minh Trang, Joacim Rocklöv, Kim Bao Giang, Gunnar Kullgren, Maria Nilsson

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There are recent studies from high income countries reporting an association between heat waves and hospital admissions for mental health disorders. It is not previously studied if such relations exist in sub-tropical and tropical low- and middle-income countries. In this study from Vietnam, the assumption was that hospital admissions for mental disorders may be triggered, or exacerbated, by heat exposure and heat waves. A database from Hanoi Mental Hospital with mental disorders diagnosed by the International Classification of Diseases 10, spanning over five years, was used to estimate the heatwave-related impacts on admissions for mental disorders. The relationship was analysed by a Negative Binomial regression model accounting for year, month, and days of week. The focus of the study was heat-wave events with periods of three or seven consecutive days above the threshold of 35oC daily maximum temperature. The preliminary study results indicated that heat-waves increased the risks for hospital admission for mental disorders (F00-79) from heat-waves of three and seven days with relative risks (RRs) of 1.16 (1.01–1.33) and 1.42 (1.02–1.99) respectively, when compared with non-heat-wave periods. Heatwave-related admissions for mental disorders increased statistically significantly among men, among residents in rural communities and in elderly. Moreover, cases for organic mental disorders including symptomatic illnesses (F0-9) and mental retardation (F70-79) raised in high risks during heat waves. The findings are novel studying a sub-tropical middle-income city, facing rapid urbanisation and epidemiological and demographic transitions.

Keywords: mental disorders, admissions for F0-9 or F70-79, maximum temperature, heat waves

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Authors: Scott Ashby, Emily Granger, Mark Connellan

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Objectives: 1) To identify if emergency coronary angiography improves outcomes in studies examining OHCA from assumed cardiac aetiology? 2) If so, is it indicated in all patients resuscitated following OHCA, and if not, who is it indicated for? 3) How effective are investigations for screening for the appropriate patients? Background: Out-of-hospital cardiac arrest is one of the leading mechanisms of death, and the most common causative pathology is coronary artery disease. In-hospital treatment following resuscitation greatly affects outcomes, yet there is debate over the most effective protocol. Methods: A literature search was conducted over multiple databases to identify all relevant articles published from 2005. An inclusion criterion was applied to all publications retrieved, which were then sorted by type. Results: A total of 3 existing reviews and 29 clinical studies were analysed in this review. There were conflicting conclusions, however increased use of angiography has shown to improve outcomes in the majority of studies, which cover a variety of settings and cohorts. Recommendations: Currently, emergency coronary angiography appears to improve outcomes in all/most cases of OHCA of assumed cardiac aetiology, regardless of ECG findings. Until a better tool for screening is available to reduce unnecessary procedures, the benefits appear to outweigh the costs/risks.

Keywords: out of hospital cardiac arrest, coronary angiography, resuscitation, emergency medicine

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Authors: Fikiru Temesgen Gelata

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Food security, adaptation, and climate change mitigation are all problems that can be resolved simultaneously with Climate-Smart Agriculture (CSA). This study examines determinants of climate-smart agriculture (CSA) practices among smallholder farmers, aiming to understand the factors guiding adoption decisions and evaluate the impact of CSA on smallholder farmer income in the study areas. For this study, three-stage sampling techniques were applied to select 230 smallholders randomly. Mann-Kendal test and multinomial endogenous switching regression model were used to analyze trends of decrease or increase within long-term temporal data and the impact of CSA on the smallholder farmer income, respectively. Findings revealed education level, household size, land ownership, off-farm income, climate information, and contact with extension agents found to be highly adopted CSA practices. On the contrary, erosion exerted a detrimental impact on all the agricultural practices examined within the study region. Various factors such as farming methods, the size of farms, proximity to irrigated farmlands, availability of extension services, distance to market hubs, and access to weather forecasts were recognized as key determinants influencing the adoption of CSA practices. The multinomial endogenous switching regression model (MESR) revealed that joint adoption of crop rotation and soil and water conservation practices significantly increased farm income by 1,107,245 ETB. The study recommends that counties and governments should prioritize addressing climate change in their development agendas to increase the adoption of climate-smart farming techniques.

Keywords: climate-smart practices, food security, Oincome, MERM, Ethiopia

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Authors: Mohammed Agbali, Claudia Trillo, Yusuf Arayici, Terrence Fernando

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The wide-spread adoption of the Smart City concept has introduced a new era of computing paradigm with opportunities for city administrators and stakeholders in various sectors to re-think the concept of urbanization and development of healthy cities. With the world population rapidly becoming urban-centric especially amongst the emerging economies, social innovation will assist greatly in deploying emerging technologies to address the development challenges in core sectors of the future cities. In this context, sustainable health-care delivery and improved quality of life of the people is considered at the heart of the healthy city agenda. This paper examines the Boston innovation landscape from the perspective of smart services and innovation ecosystem for sustainable development, especially in transportation and healthcare. It investigates the policy implementation process of the Healthy City agenda and eHealth economy innovation based on the experience of Massachusetts’s City of Boston initiatives. For this purpose, three emerging areas are emphasized, namely the eHealth concept, the innovation hubs, and the emerging technologies that drive innovation. This was carried out through empirical analysis on results of public sector and industry-wide interviews/survey about Boston’s current initiatives and the enabling environment. The paper highlights few potential research directions for service integration and social innovation for deploying emerging technologies in the healthy city agenda. The study therefore suggests the need to prioritize social innovation as an overarching strategy to build sustainable Smart Cities in order to avoid technology lock-in. Finally, it concludes that the Boston example of innovation economy is unique in view of the existing platforms for innovation and proper understanding of its dynamics, which is imperative in building smart and healthy cities where quality of life of the citizenry can be improved.

Keywords: computing paradigm, emerging technologies, equitable healthcare, healthy cities, open data, smart city, social innovation

Procedia PDF Downloads 336