Managing Home Care for the Elderly: Lessons from Community-Based Agencies.

1987 ◽  
Vol 16 (1) ◽  
pp. 65
Author(s):  
Linda J. Redford ◽  
Anabel O. Pelham ◽  
William F. Clark
1986 ◽  
Vol 1 (2) ◽  
pp. 94-103
Author(s):  
C. Bielawska ◽  
G.S. Rai

Author(s):  
Frank J. Elgar ◽  
Graham Worrall ◽  
John C. Knight

ABSTRACTAs the demand for home care services increases, health care agencies should be able to predict the intake capacity of community-based long-term care (CBLTC) programs. Two hundred and thirty-seven clients entering a CBLTC program were assessed for activities of daily living (ADL) and cognitive and affective functioning and were then followed to monitor attrition and reasons why clients left the program. Compromised ADL functioning at baseline increased likelihood of death and institutionalization by 2 per cent each year. Over a 10-year period, reduced cognitive functioning at baseline increased the risk of death by 9 per cent and decreased the likelihood of leaving the program due to improvement by 18 per cent. Reduced affective functioning at baseline increased the risk of institutionalization during the course of the study by 3 per cent. Routine functional assessments with the elderly may help in the management of similar home care programs.


2011 ◽  
Vol 2 ◽  
Author(s):  
Barbara Fersch ◽  
Per H Jensen

Processes of privatization in home care for the elderly in Denmark have primarily taken the form of outsourcing public-care provisions. The content and quality of services have in principle remained the same, but the providers of services have changed. The welfare state has continued to bear the major responsibility for the provision of elderly care, while outsourcing has allowed clients to choose between public and private providers of care. The major aim of outsourcing has been to empower the frail elderly by providing them with exit-opportunities through a construction of this group as consumers of welfare-state provisions. The central government in Denmark has produced the public-service reform, but the municipalities bear the administrative and financial responsibility for care for the elderly. Further, national policymakers have decided that local authorities (municipalities) must provide to individuals requiring care the opportunities to choose. With this background in mind, this article analyses how national, top-down ideas and the ‘politics of choice' have created tensions locally in the form of municipal resistance and blockages. The article draws on case studies in two Danish municipalities, whereby central politicians and administrative leaders have been interviewed. We have identified four areas of tensions: 1) those between liberal and libertarian ideas and values versus local political orientations and practices; 2) new tensions and lines of demarcation among political actors, where old political conflicts no longer holds; 3) tensions between promises and actual delivery, due to insufficient control of private contractors; and 4) those between market principles and the professional ethics of care providers.


Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4192
Author(s):  
Leyuan Liu ◽  
Yibin Hou ◽  
Jian He ◽  
Jonathan Lungu ◽  
Ruihai Dong

A fall detection module is an important component of community-based care for the elderly to reduce their health risk. It requires the accuracy of detections as well as maintains energy saving. In order to meet the above requirements, a sensing module-integrated energy-efficient sensor was developed which can sense and cache the data of human activity in sleep mode, and an interrupt-driven algorithm is proposed to transmit the data to a server integrated with ZigBee. Secondly, a deep neural network for fall detection (FD-DNN) running on the server is carefully designed to detect falls accurately. FD-DNN, which combines the convolutional neural networks (CNN) with long short-term memory (LSTM) algorithms, was tested on both with online and offline datasets. The experimental result shows that it takes advantage of CNN and LSTM, and achieved 99.17% fall detection accuracy, while its specificity and sensitivity are 99.94% and 94.09%, respectively. Meanwhile, it has the characteristics of low power consumption.


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