Search results for: catchment area of healthcare

Authors: A. Drong, K. S. Kerkhoff

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Migration affects women’s sexual and reproductive health and rights. This paper reports on the social constructs of gender, and livelihood pursuits as beauty parlours workers amongst the young Garo women in Bangladesh, and studies changes in their accessibility to the healthcare services due to migration and livelihood. The paper is based on in-depth interviews and participant-led group discussions with 30 women working in various beauty parlours across the city. The data indicate that social perceptions of ‘good’, ‘bad’ and ‘respectable’ determine the expression of sexuality, and often dictates sexual and reproductive practices for these women. This study also reveals that unregulated work conditions, and the current cost of local healthcare services, have a strong impact on the women’s accessibility to the healthcare services; thus often limiting their choices to only customary and/or unqualified practitioners for abortions and child-births. Development programmes on migrant indigenous women’s health must, therefore, take the contextual gender norms and livelihood choices into account.

Keywords: gender, indigenous women, reproductive rights, sexual rights, Garo, migration, livelihood, healthcare

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Authors: Trina Isabel Santiago, Daniel Chua, Jumee Tayaban, Joseph Daniel Timbol, Joshua Yanes

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Numerous instances of human rights violations on healthcare workers have been reported during the COVID-19 pandemic in the Philippines. This brief aims to explore these civil and political rights violations and propose recommendations to address these. Our review shows that a wide range of civic and political human rights violations have been committed by individual citizens and government agencies on individual healthcare workers and health worker groups. These violations include discrimination, red-tagging, evictions, illegal arrests, and acts of violence ranging from chemical attacks to homicide. If left unchecked, these issues, compounded by the pandemic, may lead to the exacerbations of the pre-existing problems of the Philippine healthcare system. Despite all pre-existing reports by human rights groups and public media articles, there still seems to be a lack of government action to condemn and prevent these violations. The existence of government agencies which directly contribute to these violations with the lack of condemnation from other agencies further propagate the problem. Given these issues, this policy brief recommends the establishment of an interagency task force for the protection of human rights of healthcare workers as well as the expedited passing of current legislative bills towards the same goal. For more immediate action, we call for the establishment of a dedicated hotline for these incidents with adequate appointment and training of point persons, construction of clear guidelines, and closer collaboration between government agencies in being united against these issues.

Keywords: human rights violations, healthcare workers, COVID-19 pandemic, Philippines

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Authors: T. Iakovleva

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Present paper suggests a theoretical model that describes the process of the development of responsible innovations on the firm level in health and welfare sectors. There is a need to develop new firm strategies in these sectors. This paper suggests to look on the concept of responsible innovation that was originally developed on the social level and to apply this new concept to the new area of firm strategy. The rapid global diffusion of information and communication technologies has greatly improved access to knowledge. At the same time, communication is cheap, information is a commodity, and global trade increases technological diffusion. As a result, firms and users, including those outside of industrialized nations, get early exposure to the latest technologies and information. General-purpose technologies such as mobile phones and 3D printers enable individuals to solve local needs and customize products. The combined effect of these changes is having a profound impact on the innovation landscape. Meanwhile, the healthcare sector is facing unprecedented challenges, which are magnified by budgetary constraints, an aging population and the desire to provide care for all. On the other hand, patients themselves are changing. They are savvier about their diseases, they expect their relation with the healthcare professionals to be open and interactive, but above all they want to be part of the decision process. All of this is a reflection of what is already happening in other industries where customers have access to large amount of information and became educated buyers. This article addresses the question of how ICT research and innovation may contribute to developing solutions to grand societal challenges in a responsible way. A broad definition of the concept of responsibility in the context of innovation is adopted in this paper. Responsibility is thus seen as a collective, uncertain and future-oriented activity. This opens the questions of how responsibilities are perceived and distributed and how innovation and science can be governed and stewarded towards socially desirable and acceptable ends. This article addresses a central question confronting politicians, business leaders, and regional planners.

Keywords: responsible innovation, ICT, healthcare, welfare sector

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Authors: Josephine Aikpitanyi, Friday Okonofua, Lorrettantoimo, Sandy Tubeuf

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Every day, 800 women die from conditions related to pregnancy and childbirth, resulting in an estimated 300,000 maternal deaths worldwide per year. Over 99 percent of all maternal deaths occur in developing countries, with more than half of them occurring in sub-Saharan Africa. Nigeria being the most populous nation in sub-Saharan Africa bears a significant burden of worsening maternal and child health outcomes with a maternal mortality rate of 917 per 100,000 live births and child mortality rate of 117 per 1,000 live births. While several studies have documented that financial barriers disproportionately discourage poor women from seeking needed maternal and child healthcare, other studies have indicated otherwise. Evidence shows that there are instances where health facilities with skilled healthcare providers exist, and yet maternal, and child health outcomes remain abysmally low, indicating the presence of non-cognitive and behavioural factors that may affect the utilization of healthcare services. This study investigated the influence of locus of control and self-esteem on utilization of maternal and child healthcare services in Nigeria. Specifically, it explored the differences in utilization of antenatal care, skilled birth care, postnatal care, and child vaccination by women having an internal and external locus of control and women having high and low self-esteem. We collected information on non-cognitive traits of 1411 randomly selected women, along with information on utilization of the various indicators of maternal and child healthcare. Estimating logistic regression models for various components of healthcare services utilization, we found that women’s internal locus of control was a significant predictor of utilization of antenatal care, skilled birth care, and completion of child vaccination. We also found that having high self-esteem was a significant predictor of utilization of antenatal care, postnatal care, and completion of child vaccination after adjusting for other control variables. By improving our understanding of non-cognitive traits as possible barriers to maternal and child healthcare utilization, our findings offer important insights for enhancing participant engagement in intervention programs that are initiated to improve maternal and child health outcomes in low-and-middle-income countries.

Keywords: behavioural economics, health-seeking behaviour, locus of control and self-esteem, maternal and child healthcare, non-cognitive traits, and healthcare utilization

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Authors: N. K. Ambujam, V. Sudha

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Reservoirs are being contaminated all around the world with point source and Non-Point Source (NPS) pollution. The most common NPS pollutants are sediments and nutrients. Krishnagiri Reservoir (KR) has been chosen for the present case study, which is located in the tropical semi-arid climatic zone of Tamil Nadu, South India. It is the main source of surface water in Krishnagiri district to meet the freshwater demands. The reservoir has lost about 40% of its water holding capacity due to sedimentation over the period of 50 years. Hence, from the research and management perspective, there is a need for a sound knowledge on the spatial and seasonal variations of KR water quality. The present study encompasses the specific objectives as (i) to investigate the longitudinal heterogeneity and seasonal variations of physicochemical parameters, nutrients and biological characteristics of KR water and (ii) to examine the extent of degradation of water quality in KR. 15 sampling points were identified by uniform stratified method and a systematic monthly sampling strategy was selected due to high dynamic nature in its hydrological characteristics. The physicochemical parameters, major ions, nutrients and Chlorophyll a (Chl a) were analysed. Trophic status of KR was classified by using Carlson's Trophic State Index (TSI). All statistical analyses were performed by using Statistical Package for Social Sciences programme, version-16.0. Spatial maps were prepared for Chl a using Arc GIS. Observations in KR pointed out that electrical conductivity and major ions are highly variable factors as it receives inflow from the catchment with different land use activities. The study of major ions in KR exhibited different trends in their values and it could be concluded that as the monsoon progresses the major ions in the water decreases or water quality stabilizes. The inflow point of KR showed comparatively higher concentration of nutrients including nitrate, soluble reactive phosphorus (SRP), total phosphors (TP), total suspended phosphorus (TSP) and total dissolved phosphorus (TDP) during monsoon seasons. This evidently showed the input of significant amount of nutrients from the catchment side through agricultural runoff. High concentration of TDP and TSP at the lacustrine zone of the reservoir during summer season evidently revealed that there was a significant release of phosphorus from the bottom sediments. Carlson’s TSI of KR ranged between 81 and 92 during northeast monsoon and summer seasons. High and permanent Cyanobacterial bloom in KR could be mainly due to the internal loading of phosphorus from the bottom sediments. According to Carlson’s TSI classification Krishnagiri reservoir was ranked in the hyper-eutrophic category. This study provides necessary basic data on the spatio-temporal variations of water quality in KR and also proves the impact of point and NPS pollution from the catchment area. High TSI warrants a greater threat for the recovery of internal P loading and hyper-eutrophic condition of KR. Several expensive internal measures for the reduction of internal loading of P were introduced by many scientists. However, the outcome of the present research suggests for the innovative algae harvesting technique for the removal of sediment nutrients.

Keywords: NPS pollution, nutrients, hyper-eutrophication, krishnagiri reservoir

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Authors: Laleh Boroumand, Muhammad Shiraz, Abdullah Gani, Rashid Hafeez Khokhar

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Cloud computing being the use of hardware and software that are delivered as a service over a network has its application in the area of health care. Due to the emergency cases reported in most of the medical centers, prompt for an efficient scheme to make health data available with less response time. To this end, we propose a mobile global healthcare village (MGHV) model that combines the components of three deployment model which include country, continent and global health cloud to help in solving the problem mentioned above. In the creation of continent model, two (2) data centers are created of which one is local and the other is global. The local replay the request of residence within the continent, whereas the global replay the requirements of others. With the methods adopted, there is an assurance of the availability of relevant medical data to patients, specialists, and emergency staffs regardless of locations and time. From our intensive experiment using the simulation approach, it was observed that, broker policy scheme with respect to optimized response time, yields a very good performance in terms of reduction in response time. Though, our results are comparable to others when there is an increase in the number of virtual machines (80-640 virtual machines). The proportionality in increase of response time is within 9%. The results gotten from our simulation experiments shows that utilizing MGHV leads to the reduction of health care expenditures and helps in solving the problems of unqualified medical staffs faced by both developed and developing countries.

Keywords: cloud computing (MCC), e-healthcare, availability, response time, service broker policy

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Authors: Jessica Hemberg, Mikaela Miller

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Unreasonable workload and work-related stress can reduce nurse leaders’ job satisfaction and productivity and can increase absence and burnout. Nurse leaders’ workload in public healthcare settings is relatively unresearched. The aim of this study was to investigate nurse leaders’ perceptions of workload and task distribution with relation to leading work tasks in public healthcare. A qualitative explorative design was used. The data material consisted of texts from interviews with nurse leaders in public healthcare (N=8). The method was inspired by content analysis. The COREQ checklist was used. Informed consent was sought from the participants regarding study participation and the storage and handling of data for research purposes. Six main themes were found: Increased and unreasonable workload, Length of work experience as nurse leader affects perception of workload, Number of staff and staff characteristics affect perception of workload, Versatile and flexible task distribution, Working overtime as a way of managing high workload, and Insufficient time for leadership mission. The workload for nurse leaders in a public healthcare setting was perceived to be unreasonable. Common measures for managing high workload included working overtime, delegating work tasks and organizing more staff resources in the form of additional staff. How nurse leaders perceive their workload was linked to both the number of staff and staff characteristics. These should both be considered equally important when determining staff levels and measuring nurse leaders’ workload. Future research should focus on investigating workload and task distribution from nurses’ perspectives.

Keywords: nurse leaders, workload, task distribution, public healthcare, qualitative

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Authors: Huawei Ma, Wencai Du, Shengbin Liang

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Smart Home Healthcare technologies for the elderly represent a transformative paradigm that leverages emerging technologies to provide the elderly’ health indicators and daily life monitoring, emergency calls, environmental monitoring, behavior perception, and other services to ensure the health and safety of the elderly who are aging in their own home. However, the excessive complexity in the main adopted framework has affected the acceptance and adoption of the elderly. Therefore, this paper proposes a lightweight synergy architecture of IoT data and service for elderly home smart health environment. It includes the modeling of IoT applications and their workflows, data interoperability, interaction, and storage paradigms to meet the growing needs of older people so that they can lead an active, fulfilling, and quality life.

Keywords: smart home healthcare, IoT, independent living, lightweight framework

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Authors: Pappu Kumar, Ajai Singh, Anshuman Singh

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There are different water user sectors such as rural, urban, mining, subsistence and commercial irrigated agriculture, commercial forestry, industry, power generation which are present in the catchment in Subarnarekha River Basin and Ranchi city. There is an inequity issue in the access to water. The development of the rural area, construction of new power generation plants, along with the population growth, the requirement of unmet water demand and the consideration of environmental flows, the revitalization of small-scale irrigation schemes is going to increase the water demands in almost all the water-stressed catchment. The WEAP Model was developed by the Stockholm Environment Institute (SEI) to enable evaluation of planning and management issues associated with water resources development. The WEAP model can be used for both urban and rural areas and can address a wide range of issues including sectoral demand analyses, water conservation, water rights and allocation priorities, river flow simulation, reservoir operation, ecosystem requirements and project cost-benefit analyses. This model is a tool for integrated water resource management and planning like, forecasting water demand, supply, inflows, outflows, water use, reuse, water quality, priority areas and Hydropower generation, In the present study, efforts have been made to access the utility of the WEAP model for water supply and demand analysis for Ranchi city. A detailed works have been carried out and it was tried to ascertain that the WEAP model used for generating different scenario of water requirement, which could help for the future planning of water. The water supplied to Ranchi city was mostly contributed by our study river, Hatiya reservoir and ground water. Data was collected from various agencies like PHE Ranchi, census data of 2011, Doranda reservoir and meteorology department etc. This collected and generated data was given as input to the WEAP model. The model generated the trends for discharge of our study river up to next 2050 and same time also generated scenarios calculating our demand and supplies for feature. The results generated from the model outputs predicting the water require 12 million litter. The results will help in drafting policies for future regarding water supplies and demands under changing climatic scenarios.

Keywords: WEAP model, water demand analysis, Ranchi, scenarios

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Authors: Raed Alsufyani, Hissam Tawfik, Victor Chang, Muthu Ramachandran

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This study investigates the factors that influence the decision by players in the healthcare sector to embrace Cloud Business Intelligence Technology with a focus on healthcare organizations in Saudi Arabia. To bring this matter into perspective, this study primarily considers the Technology-Organization-Environment (TOE) framework and the Human Organization-Technology (HOT) fit model. A survey was hypothetically designed based on literature review and was carried out online. Quantitative data obtained was processed from descriptive and one-way frequency statistics to inferential and regression analysis. Data were analysed to establish factors that influence the decision to adopt Cloud Business intelligence technology in the healthcare sector. The implication of the identified factors was measured, and all assumptions were tested. 66.70% of participants in healthcare organization backed the intention to adopt cloud business intelligence system. 99.4% of these participants considered security concerns and privacy risk have been the most significant factors in the adoption of cloud Business Intelligence (CBI) system. Through regression analysis hypothesis testing point that usefulness, service quality, relative advantage, IT infrastructure preparedness, organization structure; vendor support, perceived technical competence, government support, and top management support positively and significantly influence the adoption of (CBI) system. The paper presents quantitative phase that is a part of an on-going project. The project will be based on the consequences learned from this study.

Keywords: cloud computing, business intelligence, HOT-fit model, TOE, healthcare and innovation adoption

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Authors: Teo Hao Jing, Shane Ho Ken Wae, Lee Jin Yu, Burra Venkata Durga Kumar

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Current distributed healthcare systems face the challenge of interoperability of health data. Storing electronic health records (EHR) in local databases causes them to be fragmented. This problem is aggravated as patients visit multiple healthcare providers in their lifetime. Existing solutions are unable to solve this issue and have caused burdens to healthcare specialists and patients alike. Blockchain technology was found to be able to increase the interoperability of health data by implementing digital access rules, enabling uniformed patient identity, and providing data aggregation. Consortium blockchain was found to have high read throughputs, is more trustworthy, more secure against external disruptions and accommodates transactions without fees. Therefore, this paper proposes a blockchain-based model for data management applications. In this model, a consortium blockchain is implemented by using a delegated proof of stake (DPoS) as its consensus mechanism. This blockchain allows collaboration between users from different organizations such as hospitals and medical bureaus. Patients serve as the owner of their information, where users from other parties require authorization from the patient to view their information. Hospitals upload the hash value of patients’ generated data to the blockchain, whereas the encrypted information is stored in a distributed cloud storage.

Keywords: blockchain technology, data management applications, healthcare, interoperability, delegated proof of stake

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Authors: Sinead Impey, Gaye Stephens, Declan O’Sullivan

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Mitigating organisational knowledge loss presents challenges for knowledge managers. Expert knowledge is embodied in people and captured in ‘routines, processes, practices and norms’ as well as in the paper system. These knowledge stores have limitations in so far as they make knowledge diffusion beyond geography or over time difficult. However, technology could present a potential solution by facilitating the capture and management of expert knowledge in a codified and sharable format. Before it can be digitised, however, the knowledge of healthcare experts must be captured. Methods: As a first step in a larger project on this topic, a scoping review was conducted to identify how expert healthcare knowledge is captured digitally. The aim of the review was to identify current healthcare knowledge capture practices, identify gaps in the literature, and justify future research. The review followed a scoping review framework. From an initial 3,430 papers retrieved, 22 were deemed relevant and included in the review. Findings: Two broad approaches –direct and indirect- with themes and subthemes emerged. ‘Direct’ describes a process whereby knowledge is taken directly from subject experts. The themes identified were: ‘Researcher mediated capture’ and ‘Digital mediated capture’. The latter was further distilled into two sub-themes: ‘Captured in specified purpose platforms (SPP)’ and ‘Captured in a virtual community of practice (vCoP)’. ‘Indirect’ processes rely on extracting new knowledge using artificial intelligence techniques from previously captured data. Using this approach, the theme ‘Generated using artificial intelligence methods’ was identified. Although presented as distinct themes, some papers retrieved discuss combining more than one approach to capture knowledge. While no approach emerged as superior, two points arose from the literature. Firstly, human input was evident across themes, even with indirect approaches. Secondly, a range of challenges common among approaches was highlighted. These were (i) ‘Capturing an expert’s knowledge’- Difficulties surrounding capturing an expert’s knowledge related to identifying the ‘expert’ say from the very experienced and how to capture their tacit or difficult to articulate knowledge. (ii) ‘Confirming quality of knowledge’- Once captured, challenges noted surrounded how to validate knowledge captured and, therefore, quality. (iii) ‘Continual knowledge capture’- Once knowledge is captured, validated, and used in a system; however, the process is not complete. Healthcare is a knowledge-rich environment with new evidence emerging frequently. As such, knowledge needs to be reviewed, updated, or removed (redundancy) as appropriate. Although some methods were proposed to address this, such as plausible reasoning or case-based reasoning, conclusions could not be drawn from the papers retrieved. It was, therefore, highlighted as an area for future research. Conclusion: The results described two broad approaches – direct and indirect. Three themes were identified: ‘Researcher mediated capture (Direct)’; ‘Digital mediated capture (Direct)’ and ‘Generated using artificial intelligence methods (Indirect)’. While no single approach was deemed superior, common challenges noted among approaches were: ‘capturing an expert’s knowledge’, ‘confirming quality of knowledge’, and ‘continual knowledge capture’. However, continual knowledge capture was not fully explored in the papers retrieved and was highlighted as an important area for future research. Acknowledgments: This research is partially funded by the ADAPT Centre under the SFI Research Centres Programme (Grant 13/RC/2106) and is co-funded under the European Regional Development Fund.

Keywords: expert knowledge, healthcare, knowledge capture and knowledge management

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Authors: Itamir de Morais Barroca Filho, Cephas A. S. Barreto, Ramon Malaquias, Cezar Miranda Paula de Souza, Arthur Costa Gorgônio, João C. Xavier-Júnior, Mateus Firmino, Fellipe Matheus Costa Barbosa

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Information and Communication Technologies (ICT) in healthcare are crucial for efficiently delivering medical healthcare services to patients. These ICTs are also known as e-health and comprise technologies such as electronic record systems, telemedicine systems, and personalized devices for diagnosis. The focus of e-health is to improve the quality of health information, strengthen national health systems, and ensure accessible, high-quality health care for all. All the data gathered by these technologies make it possible to help clinical staff with automated decisions using machine learning. In this context, we collected patient data, such as heart rate, oxygen saturation (SpO2), blood pressure, respiration, and others. With this data, we were able to develop machine learning models for patients’ risk of death and estimate the length of stay in ICU beds. Thus, this paper presents the methodology for applying machine learning techniques to develop these models. As a result, although we implemented these models on an IoT healthcare platform, helping clinical staff in healthcare in an ICU, it is essential to create a robust clinical validation process and monitoring of the proposed models.

Keywords: ICT, e-health, machine learning, ICU, healthcare

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Authors: Nihar Bheda

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Protecting digital assets such as networks, systems, and data from advanced cyber threats is the aim of Digital Immunity Systems (DIS), which are a subset of cybersecurity. With features like continuous monitoring, coordinated reactions, and long-term adaptation, DIS seeks to mimic biological immunity. This minimizes downtime by automatically identifying and eliminating threats. Traditional security measures, such as firewalls and antivirus software, are insufficient for enterprises, such as healthcare providers, given the rapid evolution of cyber threats. The number of medical record breaches that have occurred in recent years is proof that attackers are finding healthcare data to be an increasingly valuable target. However, obstacles to enhancing security include outdated systems, financial limitations, and a lack of knowledge. DIS is an advancement in cyber defenses designed specifically for healthcare settings. Protection akin to an "immune system" is produced by core capabilities such as anomaly detection, access controls, and policy enforcement. Coordination of responses across IT infrastructure to contain attacks is made possible by automation and orchestration. Massive amounts of data are analyzed by AI and machine learning to find new threats. After an incident, self-healing enables services to resume quickly. The implementation of DIS is consistent with the healthcare industry's urgent requirement for resilient data security in light of evolving risks and strict guidelines. With resilient systems, it can help organizations lower business risk, minimize the effects of breaches, and preserve patient care continuity. DIS will be essential for protecting a variety of environments, including cloud computing and the Internet of medical devices, as healthcare providers quickly adopt new technologies. DIS lowers traditional security overhead for IT departments and offers automated protection, even though it requires an initial investment. In the near future, DIS may prove to be essential for small clinics, blood banks, imaging centers, large hospitals, and other healthcare organizations. Cyber resilience can become attainable for the whole healthcare ecosystem with customized DIS implementations.

Keywords: digital immunity system, cybersecurity, healthcare data, emerging technology

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Authors: Erina Wulansari, Bambang Soemardiono, Ispurwono Soemarno

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Designing sustainable tourism area is defined as an attempt to design an area, that brings the natural environmental conditions as components are available with a wealth of social conditions and the conservation of natural and cultural heritage. To understanding tourism area in this study is not only focus on the location of the tourist object, but rather to a tourist attraction around the area, tourism objects such as the existence of residential area (settlement), a commercial area, public service area, and the natural environmental area. The principle of success in designing a sustainable tourism area is able to integrate and balance between the limited space and the variety of activities that’s always continuously to growth up. The limited space in this area of tourism needs to be managed properly to minimize the damage of environmental as a result of tourism activities hue. This research aims to identify space in this area of tourism through land suitability approach as an effort to create a sustainable design, especially in terms of ecological. This study will be used several analytical techniques to achieve the research objectives as superimposing analysis with GIS 9.3 software and Analysis Hierarchy Process. Expected outcomes are in the form of classification and criteria of usable space in designing embodiment tourism area. In addition, this study can provide input to the order of settlement patterns as part of the environment in the area of sustainable tourism.

Keywords: sustainable tourism area, land suitability, limited space, environment, criteria

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Authors: Abeer A. Aljohani

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COVID-19 virus spread has been one of the extreme pandemics across the globe. It is also referred to as coronavirus, which is a contagious disease that continuously mutates into numerous variants. Currently, the B.1.1.529 variant labeled as omicron is detected in South Africa. The huge spread of COVID-19 disease has affected several lives and has surged exceptional pressure on the healthcare systems worldwide. Also, everyday life and the global economy have been at stake. This research aims to predict COVID-19 disease in its initial stage to reduce the death count. Machine learning (ML) is nowadays used in almost every area. Numerous COVID-19 cases have produced a huge burden on the hospitals as well as health workers. To reduce this burden, this paper predicts COVID-19 disease is based on the symptoms and medical history of the patient. This research presents a unique architecture for COVID-19 detection using ML techniques integrated with feature dimensionality reduction. This paper uses a standard UCI dataset for predicting COVID-19 disease. This dataset comprises symptoms of 5434 patients. This paper also compares several supervised ML techniques to the presented architecture. The architecture has also utilized 10-fold cross validation process for generalization and the principal component analysis (PCA) technique for feature reduction. Standard parameters are used to evaluate the proposed architecture including F1-Score, precision, accuracy, recall, receiver operating characteristic (ROC), and area under curve (AUC). The results depict that decision tree, random forest, and neural networks outperform all other state-of-the-art ML techniques. This achieved result can help effectively in identifying COVID-19 infection cases.

Keywords: supervised machine learning, COVID-19 prediction, healthcare analytics, random forest, neural network

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Authors: Sagar Shiwakoti, Narendra Man Shakya

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The lumped conceptual hydrological model HBV is applied to the Karnali River Basin to estimate runoff at several gauging stations and to analyze the changes in catchment hydrology and future flood magnitude due to climate change. The performance of the model is analyzed to assess its suitability to simulate streamflow in snow fed mountainous catchments. Due to the structural complexity, the model shows difficulties in modeling low and high flows accurately at the same time. It is observed that the low flows were generally underestimated and the peaks were correctly estimated except for some sharp peaks due to isolated precipitation events. In this study, attempt has been made to evaluate the importance of snow melt discharge in the runoff regime of the basin. Quantification of contribution of snowmelt to annual, summer and winter runoff has been done. The contribution is highest at the beginning of the hot months as the accumulated snow begins to melt. Examination of this contribution under conditions of increased temperatures indicate that global warming leading to increase in average basin temperature will significantly lead to higher contributions to runoff from snowmelt. Forcing the model with the output of HadCM3 GCM and the A1B scenario downscaled to the station level show significant changes to catchment hydrology in the 2040s. It is observed that the increase in runoff is most extreme in June - July. A shift in the hydrological regime is also observed.

Keywords: hydrological modeling, HBV light, rainfall runoff modeling, snow melt, climate change

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Authors: Tianyi Wang, Hieyong Jeong, An Guo, Yuko Ohno

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Healthcare robot for assisting sit-to-stand (STS) performance had aroused numerous research interests. To author’s best knowledge, knowledge about how evaluating healthcare robot is still unknown. Robot should be labeled as fault if users feel demanding during STS when they are assisted by robot. In this research, we aim to propose a method to evaluate sit-to-stand assist robot through center of pressure (CoP), then classify different STS performance. Experiments were executed five times with ten healthy subjects under four conditions: two self-performed STSs with chair heights of 62 cm and 43 cm, and two robot-assisted STSs with chair heights of 43 cm and robot end-effect speed of 2 s and 5 s. CoP was measured using a Wii Balance Board (WBB). Bayesian classification was utilized to classify STS performance. The results showed that faults occurred when decreased the chair height and slowed robot assist speed. Proposed method for fault classification showed high probability of classifying fault classes form others. It was concluded that faults for STS assist robot could be detected by inspecting center of pressure and be classified through proposed classification algorithm.

Keywords: center of pressure, fault classification, healthcare robot, sit-to-stand movement

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Authors: Qing Wu, Xuchun Ye, Kirsten Corazzini

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Objective: It is increasingly recognized that patients’ rational and meaningful engagement in healthcare could make important contributions to their health care and safety management. However, recent evidence indicated that patients' actual roles in healthcare didn’t match their desired roles, and many patients reported a less active role than desired, which suggested that patient engagement in healthcare may be influenced by various factors. This study aimed to analyze influencing factors on patient engagement and explore the influence mechanism, which will be expected to contribute to the strategy development of patient engagement in healthcare. Methods: On the basis of analyzing the literature and theory study, the research framework was developed. According to the research framework, a cross-sectional survey was employed using the behavior and willingness of patient engagement in healthcare questionnaire, Chinese version All Aspects of Health Literacy Scale, Facilitation of Patient Involvement Scale and Wake Forest Physician Trust Scale, and other influencing factor related scales. A convenience sample of 580 patients was recruited from 8 general hospitals in Shanghai, Jiangsu Province, and Zhejiang Province. Results: The results of the cross-sectional survey indicated that the mean score for the patient engagement behavior was (4.146 ± 0.496), and the mean score for the willingness was (4.387 ± 0.459). The level of patient engagement behavior was inferior to their willingness to be involved in healthcare (t = 14.928, P ＜ 0.01). The influencing mechanism model of patient engagement in healthcare was constructed by the path analysis. The path analysis revealed that patient attitude toward engagement, patients’ perception of facilitation of patient engagement and health literacy played direct prediction on the patients’ willingness of engagement, and standard estimated values of path coefficient were 0.341, 0.199, 0.291, respectively. Patients’ trust in physician and the willingness of engagement played direct prediction on the patient engagement, and standard estimated values of path coefficient were 0.211, 0.641, respectively. Patient attitude toward engagement, patients’ perception of facilitation and health literacy played indirect prediction on patient engagement, and standard estimated values of path coefficient were 0.219, 0.128, 0.187, respectively. Conclusions: Patients engagement behavior did not match their willingness to be involved in healthcare. The influencing mechanism model of patient engagement in healthcare was constructed. Patient attitude toward engagement, patients’ perception of facilitation of engagement and health literacy posed indirect positive influence on patient engagement through the patients’ willingness of engagement. Patients’ trust in physician and the willingness of engagement had direct positive influence on the patient engagement. Patient attitude toward engagement, patients’ perception of physician facilitation of engagement and health literacy were the factors influencing the patients’ willingness of engagement. The results of this study provided valuable evidence on guiding the development of strategies for promoting patient rational and meaningful engagement in healthcare.

Keywords: healthcare, patient engagement, influencing factor, the mechanism

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Authors: Partha Saha, Uttam Kumar Banerjee

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Maternal and Child Healthcare (MCH) has always been regarded as one of the important issues globally. Reduction of maternal and child mortality rates and increase of healthcare service coverage were declared as one of the targets in Millennium Development Goals till 2015 and thereafter as an important component of the Sustainable Development Goals. Over the last decade, worldwide MCH indicators have improved but could not match the expected levels. Progress of both maternal and child mortality rates have been monitored by several researchers. Each of the studies has stated that only less than 26% of low-income and middle income countries (LMICs) were on track to achieve targets as prescribed by MDG4. Average worldwide annual rate of reduction of under-five mortality rate and maternal mortality rate were 2.2% and 1.9% as on 2011 respectively whereas rates should be minimum 4.4% and 5.5% annually to achieve targets. In spite of having proven healthcare interventions for both mothers and children, those could not be scaled up to the required volume due to fragmented health systems, especially in the developing and under-developed countries. In this research, a knowledge discovery based interactive Decision Support System (DSS) has been developed on web platform which would assist healthcare policy makers to develop evidence-based policies. To achieve desirable results in MCH, efficient resource planning is very much required. In maximum LMICs, resources are big constraint. Knowledge, generated through this system, would help healthcare managers to develop strategic resource planning for combatting with issues like huge inequity and less coverage in MCH. This system would help healthcare managers to accomplish following four tasks. Those are a) comprehending region wise conditions of variables related with MCH, b) identifying relationships within variables, c) segmenting regions based on variables status, and d) finding out segment wise key influential variables which have major impact on healthcare indicators. Whole system development process has been divided into three phases. Those were i) identifying contemporary issues related with MCH services and policy making; ii) development of the system; and iii) verification and validation of the system. More than 90 variables under three categories, such as a) educational, social, and economic parameters; b) MCH interventions; and c) health system building blocks have been included into this web-based DSS and five separate modules have been developed under the system. First module has been designed for analysing current healthcare scenario. Second module would help healthcare managers to understand correlations among variables. Third module would reveal frequently-occurring incidents along with different MCH interventions. Fourth module would segment regions based on previously mentioned three categories and in fifth module, segment-wise key influential interventions will be identified. India has been considered as case study area in this research. Data of 601 districts of India has been used for inspecting effectiveness of those developed modules. This system has been developed by importing different statistical and data mining techniques on Web platform. Policy makers would be able to generate different scenarios from the system before drawing any inference, aided by its interactive capability.

Keywords: maternal and child heathcare, decision support systems, data mining techniques, low and middle income countries

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Authors: Hend Albassam, Nouf Alrumaih

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Nowadays we are in the age of technologies and communication and there is no doubt that technologies such as the Internet can offer many advantages for many business fields, and the health field is no execution. In fact, using the Internet provide us with a new path to improve the quality of health care throughout the world. The e-healthcare offers many advantages such as: efficiency by reducing the cost and avoiding duplicate diagnostics, empowerment of patients by enabling them to access their medical records, enhancing the quality of healthcare and enabling information exchange and communication between healthcare organizations. There are many problems that result from using papers as a way of communication, for example, paper-based prescriptions. Usually, the doctor writes a prescription and gives it to the patient who in turn carries it to the pharmacy. After that, the pharmacist takes the prescription to fill it and give it to the patient. Sometimes the pharmacist might find difficulty in reading the doctor’s handwriting; the patient could change and counterfeit the prescription. These existing problems and many others heighten the need to improve the quality of the healthcare. This project is set out to develop a distributed e-healthcare system that offers some features of e-health and addresses some of the above-mentioned problems. The developed system provides an electronic health record (EHR) and enables communication between separate health care organizations such as the clinic, pharmacy and laboratory. To develop this system, the Service Oriented Architecture (SOA) is adopted as a design approach, which helps to design several independent modules that communicate by using web services. The layering design pattern is used in designing each module as it provides reusability that allows the business logic layer to be reused by different higher layers such as the web service or the website in our system. The experimental analysis has shown that the project has successfully achieved its aims toward solving the problems related to the paper-based healthcare systems and it enables different health organization to communicate effectively. It implements four independent modules including healthcare provider, pharmacy, laboratory and medication information provider. Each module provides different functionalities and is used by a different type of user. These modules interoperate with each other using a set of web services.

Keywords: e-health, services oriented architecture (SOA), web services, interoperability

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Authors: Yajing Jiang, Jing Wu

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Residential area construction links many problems such as population resources, ecology, social values, public services and transportation in the city. After Chinese housing reform, a large number of residential area development accompanied by the loss of agricultural and ecological land. To explore the future of Chinese urban residential area, this article concentrates on how the 'Compact Settlement' behaves in improving the living environment and saving the resources. Through the research of residential area in Hangzhou, there are some determines that increasing the development intensity of the area can indeed bring some improvement in the overall environment. In conclusion, possible design alternatives are discussed for leading Chinese urban development towards a more sustainable path.

Keywords: compact city development, environmental sustainability, residential area, Hangzhou

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Authors: Abdessamad Dali-Ali, Houaria Beldjillali, Fouzia Agag, Asmaa Oukebdane, Ramzi Tidjani, Arslane Bettayeb, Khadidja Meddeber, Radia Dali-Yahia, Nori Midoun

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Healthcare-associated infections are a real public health problem, especially in intensive care units. The aim of our study was to describe the epidemiological profile and to estimate the incidence of these infections at the intensive care unit of our teaching hospital. A prospective study was conducted, from June 2012 to December 2013. During this period, 305 patients having a duration of hospitalization equal or more than 48 hours were included in the study. In terms of the incidence of healthcare associated infections, nosocomial pneumonia occupied the first position with a cumulative incidence rate of 20.0%, followed by bacteremia (5.6%), central venous catheter infections (4%), and urinary tract infections (3%). In the case of isolated microorganisms, Gram-negative bacilli not enterobacteriaceae occupied the first place with 48.5%, followed by enterobacteria (32.1%). Acinetobacter baumannii was the most common germ (27.6%). Our study showed that the rate of health-care-associated infections was relatively high in the intensive care unit. A control program to reduce all infections is a priority for the Infection Control Associated Committee.

Keywords: epidemiological profile, healthcare associated infections, intensive care units, teaching hospital of Oran, Algeria

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Authors: Mohd Zuhair, Ram Babu Roy

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This paper presents an overview of the accessibility, design, and functioning of health insurance plans launched by state governments in India. In recent years, the governments of several states in India have come forward to provide health insurance coverage for the low-income group and rural population to reduce the out of pocket expenditure (OPE) on healthcare. Different health insurance schemes have different structures and offerings which differ in the different demographic factors. This study will portray a comparative analysis of the various health insurance schemes by analyzing different offerings and finance generation of the schemes. The comparative analysis will explain the lesson to be learned from these schemes and extend the existing knowledge of the health insurance in India. This would help in recognizing tension between various drivers and identifying issues pertaining to the sustainability of health insurance schemes in India.

Keywords: health insurance, out of pocket expenditure, universal healthcare, sustainability

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Authors: Umair Shafique, Hafiz Usman Zia, Fiaz Majeed, Samina Naz, Javeria Ahmed, Maleeha Zainab

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The Internet of Things (IoT) has become a hot topic for the last couple of years. This innovative technology has shown promising progress in various areas, and the world has witnessed exponential growth in multiple application domains. Researchers are working to investigate its aptitudes to get the best from it by harnessing its true potential. But at the same time, IoT networks open up a new aspect of vulnerability and physical threats to data integrity, privacy, and confidentiality. It's is due to centralized control, data silos approach for handling information, and a lack of standardization in the IoT networks. As we know, blockchain is a new technology that involves creating secure distributed ledgers to store and communicate data. Some of the benefits include resiliency, integrity, anonymity, decentralization, and autonomous control. The potential for blockchain technology to provide the key to managing and controlling IoT has created a new wave of excitement around the idea of putting that data back into the hands of the end-users. In this manuscript, we have proposed a model that combines blockchain and IoT networks to address potential security and privacy issues in the healthcare domain. Then we try to describe various application areas, challenges, and future directions in the healthcare sector where blockchain platforms merge with IoT networks.

Keywords: IoT, blockchain, cryptocurrency, healthcare, consensus, data

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Authors: Ruzanna Muradyan

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Medical data mining is a crucial field in contemporary healthcare that offers cutting-edge tactics with enormous potential to transform patient care. This abstract examines how sophisticated data mining techniques could transform the healthcare industry, with a special focus on how they might improve patient outcomes. Healthcare data repositories have dynamically evolved, producing a rich tapestry of different, multi-dimensional information that includes genetic profiles, lifestyle markers, electronic health records, and more. By utilizing data mining techniques inside this vast library, a variety of prospects for precision medicine, predictive analytics, and insight production become visible. Predictive modeling for illness prediction, risk stratification, and therapy efficacy evaluations are important points of focus. Healthcare providers may use this abundance of data to tailor treatment plans, identify high-risk patient populations, and forecast disease trajectories by applying machine learning algorithms and predictive analytics. Better patient outcomes, more efficient use of resources, and early treatments are made possible by this proactive strategy. Furthermore, data mining techniques act as catalysts to reveal complex relationships between apparently unrelated data pieces, providing enhanced insights into the cause of disease, genetic susceptibilities, and environmental factors. Healthcare practitioners can get practical insights that guide disease prevention, customized patient counseling, and focused therapies by analyzing these associations. The abstract explores the problems and ethical issues that come with using data mining techniques in the healthcare industry. In order to properly use these approaches, it is essential to find a balance between data privacy, security issues, and the interpretability of complex models. Finally, this abstract demonstrates the revolutionary power of modern data mining methodologies in transforming the healthcare sector. Healthcare practitioners and researchers can uncover unique insights, enhance clinical decision-making, and ultimately elevate patient care to unprecedented levels of precision and efficacy by employing cutting-edge methodologies.

Keywords: data mining, healthcare, patient care, predictive analytics, precision medicine, electronic health records, machine learning, predictive modeling, disease prognosis, risk stratification, treatment efficacy, genetic profiles, precision health

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Authors: Abhay Vir Singh Kanwar

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The pharmaceutical industry today is a multi-billion dollar business and yet disadvantages people in many corners of the globe who are still dying in large numbers from curable illnesses for lack of access to drugs. The astronomical prices of essential and life-saving drugs is not just an economic problem that can be settled through clever market strategies but is an ethical issue, given the accumulated wealth of today’s humanity and the sense of global justice that it increasingly comes to share. In this paper, I make a very practical argument for what I shall call ‘the ethical healthcare paradigm’, which, I propose, can replace the economistic paradigm that can still drive the healthcare sector without creating spillover effects on the market. Taking off from the ethical-philosophical argument for recognizing every individual’s right to capability to be healthy, I shall come to the focused practical proposal of the cost-rationalization and universal availability of essential, life-saving drugs through the undertaking of research and development funding for drug innovation by the business establishment as such in terms of the concept of CSR. The paper will first expose the concepts of basic and fundamental capabilities in relation to education and health, after which it will focus on the right to capability to be healthy of every person. In the third section, it will discuss the ‘ethical healthcare paradigm’ as opposed to the economistic health paradigm and will argue that the patient will have to be considered the primary stakeholder of this paradigm or the very ‘subject’ of healthcare. The next section will be on an ethical-historical critique of the pharmaceutical industry’s profit driven economism. The section after that will look at the business operation and the stages in the life cycle of a drug that comes to the market in order to understand the risks, strengths and problems of the pharmaceutical industry. Finally, the paper will discuss the concept of CSR in relation to the ethical healthcare paradigm in order to propose CSR funding in research and development for innovation on drugs so that life-saving drugs can be made available to every sick person cost-effectively.

Keywords: capability approach, healthcare, CSR, patient

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Authors: Mrigakshi Das

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The private sector investments and quantum of money required in this sector critically hinges on the financial risk and returns the sector offers to providers of capital. Therefore, it becomes important to understand financial performance of hospitals. Financial Analysis is useful for decision makers in a variety of settings. Consider the small proprietary hospitals, say, Physicians Clinic. The managers of such clinic need the information that financial statements provide. Attention to Financial Statements of healthcare Organizations can provide answers to questions like: How are they doing? What is their rate of profit? What is their solvency and liquidity position? What are their sources and application of funds? What is their Operational Efficiency? The researcher has studied Financial Statements of 5 Private Healthcare Organizations in Guwahati City.

Keywords: not-for-profit organizations, financial analysis, ratio analysis, profitability analysis, liquidity analysis, operational efficiency, capital structure analysis

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Authors: Sandeep Reddy, Sonia Allan, Simon Coghlan, Paul Cooper

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Artificial Intelligence (AI) and its application in medicine has generated ample interest amongst policymakers and clinicians. Successes with AI in medical imaging interpretation and clinical decision support are paving the way for its incorporation into routine healthcare delivery. While there has been a focus on the development of ethical principles to guide its application in healthcare, challenges of this application go beyond what ethics principles can address thus requiring robust governance frameworks. Also, while ethical challenges of medical artificial intelligence are being discussed, the ethics of deploying AI in lower-income countries receive less attention than in other developed economies. This creates an imperative not only for sound ethical guidelines but also for robust governance frameworks to regulate AI in medicine around the world. In this article, we discuss what components need to be considered in developing these governance frameworks and who should lead this worldwide effort.

Keywords: artificial intelligence, global health, governance, ethics

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Authors: Y. Atilgan Şengül

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Health information technologies promise higher quality, safer care and much more for both patients and professionals. Despite their promise, they are costly to develop and difficult to implement. On the other hand, user acceptance and usage determine the success of implemented information technology in healthcare. This study provides a model to understand health professionals’ perception and expectation of health information technology. Extensive literature review has been conducted to determine the main factors to be measured. A questionnaire has been designed as a measurement model and submitted to the personnel of an in vitro fertilization clinic. The respondents’ degree of agreement according to five-point Likert scale was 72% for convenient access to data and 69.4% for the importance of data security. There was a significant difference in acceptance of electronic data storage for female respondents. Also, other significant differences between professions were obtained.

Keywords: healthcare, health informatics, medical record system, questionnaire

Procedia PDF Downloads 146