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Homecare ist ein junger Bereich, der die stationäre Versorgung mit der ambulanten Nachsorge verbindet und sämtliche weitere Versorger koordiniert. In der Praxis scheitert diese Idee derzeit noch häufig an fehlenden oder unpräzisen rechtlichen Rahmenbedingungen sowie Akzeptanzbarrieren. Dieses Buch bietet einen umfassenden Überblick der aktuellen Versorgungssituation im Homecare-Bereich in Deutschland. Es diskutiert den Homecare-Markt und seine Potentiale, die rechtlichen Rahmenbedingungen und gibt einen Überblick über nationale und internationale Studien zur Effektivität von Entlassmanagement und sektorenübergreifender Versorgung. Ein Praxisteil präsentiert Ergebnisse einer umfassenden empirischen Studie, die die Perspektiven von niedergelassenen Ärzten, Kliniken und stationärer sowie ambulanter Pflege zum Thema Homecare untersucht. Die Ergebnisse der Studie geben Aufschluss über die praktische Umsetzung der Homecare-Idee im Versorgungsalltag sowie die Potentiale und Risiken.
Medical --- Medicine --- Health Workforce --- Homecare --- Health Care Management --- Discharge Management --- Ambulante Pflege --- Arzt --- Arztpraxis --- Deutschland --- Entlassmanagement --- Hausarzt --- Krankenhaus
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This revealing look at home care illustrates how elderly and disabled people and the immigrant women workers who assist them in daily activities develop meaningful relationships even when their different ages, abilities, races, nationalities, and socioeconomic backgrounds generate tension.
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Home care services --- Medical telematics --- Telecommunication in medicine --- Home care services. --- Medical telematics. --- Telecommunication in medicine. --- Home Care Services. --- Telemedicine. --- technology --- healthcare --- homecare --- telehealth --- healthcare --- medical technology --- assisted living --- Human medicine
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"In July 1939, at the Royal Courts of Justice in London, fifty-nine-year-old Beatrice Alexander was found incapable of managing her own property and affairs. Although Alexander and those living with her insisted that she was perfectly well, the official solicitor took control of her home and money, evicted her "friends," and hired a live-in companion to watch over her. Alexander remained legally incapable for the next thirty years. In the mid-twentieth century, Alexander was one of about thirty thousand people in England and Wales who were, at any time, legally "incapable" and under the auspices of what is now the Court of Protection. Focusing on the period between the 1920s and the 1960s, Looking After Miss Alexander explains the workings of the court, using Alexander's unusual case to consider the complexities of this aspect of mental health law. Drawing on Court of Protection archives--some of which were made publicly available for the first time in 2019--and micro-historical methods, Janet Weston also highlights the role of chance, subjectivity, and uncertainty in shaping how events unfolded then, and the stories we tell about those events today. An engaging and accessible history of mental capacity law, Looking After Miss Alexander examines ideas of citizenship and welfare, gender and vulnerability, care and control, and the role of the state. It also offers reflections on historical research and writing itself."--
Mental health law. --- British Union of Fascists. --- Dorset. --- Lunacy Office. --- Official Solicitor. --- autonomy. --- capacity. --- care. --- carers. --- chance. --- citizenship. --- common law. --- competence. --- control. --- dementia. --- disability. --- elder abuse. --- exploitation. --- financial abuse. --- friendship. --- gender. --- guardianship. --- homecare. --- imagination. --- incapacity. --- indeterminacy. --- informal care. --- interwar. --- legal history. --- lunacy law. --- mental defect. --- mental health law. --- mental illness. --- microhistory. --- nursing. --- respectability. --- retirement. --- small history. --- social policy. --- socio-legal history. --- subjectivity. --- vulnerability. --- welfare state. --- welfare.
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"Elana D. Buch's "Inequalities of Aging: Paradoxes of Independence in American Home Care" focuses on the topic of American home care and explores various contradictions and points of tension within the industry. It also raises awareness of the problematic inequality that exists in the American home care industry and argues for the creation of a more sustainable system."--
Aged. --- Vulnerable Populations. --- Health Services for the Aged. --- Home Care Services. --- Home Health Aides. --- Older people --- Home care services --- Home care --- United States. --- Medicaid. --- aging in America. --- aging population. --- aging. --- care workforce. --- caring economy. --- contemporary care work. --- daily care practices. --- elder care workers. --- elder care. --- elder caregivers. --- elder independence. --- elder well-being. --- elderly. --- ethnographic fieldwork. --- generative labor. --- home care agencies. --- home care agency. --- home care industry. --- home care policy. --- home care workers. --- homecare. --- life spans. --- low-wage work. --- morality and aging. --- older adults. --- personhood and aging. --- poverty and aging. --- reciprocal relationships. --- social hierarchies. --- social policy aging. --- worker shortage.
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"Elana D. Buch's "Inequalities of Aging: Paradoxes of Independence in American Home Care" focuses on the topic of American home care and explores various contradictions and points of tension within the industry. It also raises awareness of the problematic inequality that exists in the American home care industry and argues for the creation of a more sustainable system."--
Aged. --- Vulnerable Populations. --- Health Services for the Aged. --- Home Care Services. --- Home Health Aides. --- Older people --- Home care services --- Home care --- United States. --- Medicaid. --- aging in America. --- aging population. --- aging. --- care workforce. --- caring economy. --- contemporary care work. --- daily care practices. --- elder care workers. --- elder care. --- elder caregivers. --- elder independence. --- elder well-being. --- elderly. --- ethnographic fieldwork. --- generative labor. --- home care agencies. --- home care agency. --- home care industry. --- home care policy. --- home care workers. --- homecare. --- life spans. --- low-wage work. --- morality and aging. --- older adults. --- personhood and aging. --- poverty and aging. --- reciprocal relationships. --- social hierarchies. --- social policy aging. --- worker shortage.
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Smart cities operate under more resource-efficient management and economy than ordinary cities. As such, advanced business models have emerged around smart cities, which led to the creation of smart enterprises and organizations that depend on advanced technologies. This book includes 21 selected and peer-reviewed articles contributed in the wide spectrum of artificial intelligence applications to smart cities. Chapters refer to the following areas of interest: vehicular traffic prediction, social big data analysis, smart city management, driving and routing, localization, safety, health, and life quality.
Information technology industries --- spatio-temporal --- residual networks --- bus traffic flow prediction --- advance rate --- shield performance --- principal component analysis --- ANFIS-GA --- tunnel --- online learning --- extreme learning machine --- cyclic dynamics --- transfer learning --- knowledge preservation --- Feature Adaptive --- optimization --- Bacterial Foraging algorithm --- Swarm Intelligence algorithm --- Isolated Microgrid --- traffic surveillance video --- state analysis --- Grassmann manifold --- neural network --- machine-learning --- quality of life --- Better Life Index --- bagging --- ensemble learning --- pedestrian attributes --- surveillance image --- semantic attributes recognition --- multi-label learning --- large-scale database --- traffic congestion detection --- minimizing traffic congestion --- traffic prediction --- deep learning --- urban mobility --- ITS --- Vehicle-to-Infrastructure --- neural networks --- LSTM --- embeddings --- trajectories --- motion behavior --- smart tourism --- driver’s behavior detection --- texting and driving --- convolutional neural network --- smart car --- smart cities --- smart infotainment --- driver distraction --- cameras --- convolution --- detection --- image recognition --- DSS --- diabetes prediction --- homecare assistance information system --- muti-attribute analysis --- artificial training dataset --- machine learning --- big data --- data analysis --- sensors --- Internet of Things --- vehicular networks --- VDTN --- routing --- message scheduling --- traffic flow prediction --- wavenet --- TrafficWave --- RNN --- GRU --- SAEs --- risk assessment --- neural architecture search --- recurrent neural network --- automated driving vehicle --- decision support system --- artificial intelligence --- disaster management --- Smart city --- program management --- integrated model --- smart city --- intelligence transportation system --- computer vision --- potential pedestrian safety --- data mining --- healthcare --- Apache Spark --- disease detection --- symptoms detection --- Arabic language --- Saudi dialect --- Twitter --- high performance computing (HPC) --- spatial-temporal dependencies --- traffic periodicity --- graph convolutional network --- traffic speed prediction --- vehicular traffic --- surveillance video --- big data analysis --- autonomous driving --- life quality --- pattern recognition
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Smart cities operate under more resource-efficient management and economy than ordinary cities. As such, advanced business models have emerged around smart cities, which led to the creation of smart enterprises and organizations that depend on advanced technologies. This book includes 21 selected and peer-reviewed articles contributed in the wide spectrum of artificial intelligence applications to smart cities. Chapters refer to the following areas of interest: vehicular traffic prediction, social big data analysis, smart city management, driving and routing, localization, safety, health, and life quality.
spatio-temporal --- residual networks --- bus traffic flow prediction --- advance rate --- shield performance --- principal component analysis --- ANFIS-GA --- tunnel --- online learning --- extreme learning machine --- cyclic dynamics --- transfer learning --- knowledge preservation --- Feature Adaptive --- optimization --- Bacterial Foraging algorithm --- Swarm Intelligence algorithm --- Isolated Microgrid --- traffic surveillance video --- state analysis --- Grassmann manifold --- neural network --- machine-learning --- quality of life --- Better Life Index --- bagging --- ensemble learning --- pedestrian attributes --- surveillance image --- semantic attributes recognition --- multi-label learning --- large-scale database --- traffic congestion detection --- minimizing traffic congestion --- traffic prediction --- deep learning --- urban mobility --- ITS --- Vehicle-to-Infrastructure --- neural networks --- LSTM --- embeddings --- trajectories --- motion behavior --- smart tourism --- driver’s behavior detection --- texting and driving --- convolutional neural network --- smart car --- smart cities --- smart infotainment --- driver distraction --- cameras --- convolution --- detection --- image recognition --- DSS --- diabetes prediction --- homecare assistance information system --- muti-attribute analysis --- artificial training dataset --- machine learning --- big data --- data analysis --- sensors --- Internet of Things --- vehicular networks --- VDTN --- routing --- message scheduling --- traffic flow prediction --- wavenet --- TrafficWave --- RNN --- GRU --- SAEs --- risk assessment --- neural architecture search --- recurrent neural network --- automated driving vehicle --- decision support system --- artificial intelligence --- disaster management --- Smart city --- program management --- integrated model --- smart city --- intelligence transportation system --- computer vision --- potential pedestrian safety --- data mining --- healthcare --- Apache Spark --- disease detection --- symptoms detection --- Arabic language --- Saudi dialect --- Twitter --- high performance computing (HPC) --- spatial-temporal dependencies --- traffic periodicity --- graph convolutional network --- traffic speed prediction --- vehicular traffic --- surveillance video --- big data analysis --- autonomous driving --- life quality --- pattern recognition
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Smart cities operate under more resource-efficient management and economy than ordinary cities. As such, advanced business models have emerged around smart cities, which led to the creation of smart enterprises and organizations that depend on advanced technologies. This book includes 21 selected and peer-reviewed articles contributed in the wide spectrum of artificial intelligence applications to smart cities. Chapters refer to the following areas of interest: vehicular traffic prediction, social big data analysis, smart city management, driving and routing, localization, safety, health, and life quality.
Information technology industries --- spatio-temporal --- residual networks --- bus traffic flow prediction --- advance rate --- shield performance --- principal component analysis --- ANFIS-GA --- tunnel --- online learning --- extreme learning machine --- cyclic dynamics --- transfer learning --- knowledge preservation --- Feature Adaptive --- optimization --- Bacterial Foraging algorithm --- Swarm Intelligence algorithm --- Isolated Microgrid --- traffic surveillance video --- state analysis --- Grassmann manifold --- neural network --- machine-learning --- quality of life --- Better Life Index --- bagging --- ensemble learning --- pedestrian attributes --- surveillance image --- semantic attributes recognition --- multi-label learning --- large-scale database --- traffic congestion detection --- minimizing traffic congestion --- traffic prediction --- deep learning --- urban mobility --- ITS --- Vehicle-to-Infrastructure --- neural networks --- LSTM --- embeddings --- trajectories --- motion behavior --- smart tourism --- driver’s behavior detection --- texting and driving --- convolutional neural network --- smart car --- smart cities --- smart infotainment --- driver distraction --- cameras --- convolution --- detection --- image recognition --- DSS --- diabetes prediction --- homecare assistance information system --- muti-attribute analysis --- artificial training dataset --- machine learning --- big data --- data analysis --- sensors --- Internet of Things --- vehicular networks --- VDTN --- routing --- message scheduling --- traffic flow prediction --- wavenet --- TrafficWave --- RNN --- GRU --- SAEs --- risk assessment --- neural architecture search --- recurrent neural network --- automated driving vehicle --- decision support system --- artificial intelligence --- disaster management --- Smart city --- program management --- integrated model --- smart city --- intelligence transportation system --- computer vision --- potential pedestrian safety --- data mining --- healthcare --- Apache Spark --- disease detection --- symptoms detection --- Arabic language --- Saudi dialect --- Twitter --- high performance computing (HPC) --- spatial-temporal dependencies --- traffic periodicity --- graph convolutional network --- traffic speed prediction --- vehicular traffic --- surveillance video --- big data analysis --- autonomous driving --- life quality --- pattern recognition --- spatio-temporal --- residual networks --- bus traffic flow prediction --- advance rate --- shield performance --- principal component analysis --- ANFIS-GA --- tunnel --- online learning --- extreme learning machine --- cyclic dynamics --- transfer learning --- knowledge preservation --- Feature Adaptive --- optimization --- Bacterial Foraging algorithm --- Swarm Intelligence algorithm --- Isolated Microgrid --- traffic surveillance video --- state analysis --- Grassmann manifold --- neural network --- machine-learning --- quality of life --- Better Life Index --- bagging --- ensemble learning --- pedestrian attributes --- surveillance image --- semantic attributes recognition --- multi-label learning --- large-scale database --- traffic congestion detection --- minimizing traffic congestion --- traffic prediction --- deep learning --- urban mobility --- ITS --- Vehicle-to-Infrastructure --- neural networks --- LSTM --- embeddings --- trajectories --- motion behavior --- smart tourism --- driver’s behavior detection --- texting and driving --- convolutional neural network --- smart car --- smart cities --- smart infotainment --- driver distraction --- cameras --- convolution --- detection --- image recognition --- DSS --- diabetes prediction --- homecare assistance information system --- muti-attribute analysis --- artificial training dataset --- machine learning --- big data --- data analysis --- sensors --- Internet of Things --- vehicular networks --- VDTN --- routing --- message scheduling --- traffic flow prediction --- wavenet --- TrafficWave --- RNN --- GRU --- SAEs --- risk assessment --- neural architecture search --- recurrent neural network --- automated driving vehicle --- decision support system --- artificial intelligence --- disaster management --- Smart city --- program management --- integrated model --- smart city --- intelligence transportation system --- computer vision --- potential pedestrian safety --- data mining --- healthcare --- Apache Spark --- disease detection --- symptoms detection --- Arabic language --- Saudi dialect --- Twitter --- high performance computing (HPC) --- spatial-temporal dependencies --- traffic periodicity --- graph convolutional network --- traffic speed prediction --- vehicular traffic --- surveillance video --- big data analysis --- autonomous driving --- life quality --- pattern recognition
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