A Collaborative Framework with Artificial Intelligence for Long-term Care

The trend of aging population among working families has made health care services for sub-healthy people more important. In Taiwan, caregivers are often hired by human resource agencies to provide long-term care, and they are the main supervisors responsible for the care of the sub-healthy people....

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Bibliographic Details
Published in:IEEE access 2020-01, Vol.8, p.1-1
Main Author: Chou, Hsien-Ming
Format: Article
Language:English
Subjects:
Artificial intelligence
Buildings
Caregivers
Collaboration
Collaborative Framework
Diseases
Hospitals
Human resources
Long term care insurance
Long term health care
Long-term Care
Mapping
Physiology
Sub-healthy People
Supervisors
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Summary:The trend of aging population among working families has made health care services for sub-healthy people more important. In Taiwan, caregivers are often hired by human resource agencies to provide long-term care, and they are the main supervisors responsible for the care of the sub-healthy people. However, most agencies only consider the cost of their caregivers and have insufficient staff to take care of the sub-healthy people, leading to the failure of the long-term care system. The lack of an effective collaborative framework for long-term care leads to sub-healthy people being at high risks. Existing frameworks for long-term care are still in the early stages of capturing suitability information dynamically. This paper proposes a new framework that includes all possible features suitable to support the needs of all sub-healthy people and provides a solution for the issue of determining suitable features for collaboration. This study applies association rules to long-term care to handle the mapping process and uses artificial intelligence technology to solve the issues of adjusting human variability dynamically based on the mapping result of sub-healthy people.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.2977043