Analysis of Satisfaction to Community-based Integrated Medical and Nursing Services and its Influencing Factors among Elders in Chengdu
Authors: 
Li Bing, Hu Rui, Peijia TianAuthors Info & Claims
Pages 129 - 133
Abstract
To examine the satisfaction to community-based integrated medical and nursing services among elderly in Chengdu city of Sichuan province and its influencing factors, to provide a basis for improving the quality and efficiency of community medical and nursing services in the future. Based on the stratified random sampling method, a questionnaire survey is conducted among 392 elderly people living in the 5 main urban districts in Chengdu. The principal component analysis method was used to obtain four key factors of satisfaction with community medical care, service personnel, life and environment, and spatial superiority. The comprehensive satisfaction score of the elderly in Chengdu is (2.62±0.547) points. The results of multi-factor logistic regression analysis showed that regional differences, health self-assessment, whether they have received community health management services, life care services, and smart elderly care services are the influencing factors of elderly satisfaction (P<0.05). The overall satisfaction of the elderly in Chengdu with community medical care and elderly care services is good. The government should focus on improving the community's basic public health services, increasing the accessibility of services, and focusing on the application of smart elderly care technology and family doctor team building.
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Index Terms
- Analysis of Satisfaction to Community-based Integrated Medical and Nursing Services and its Influencing Factors among Elders in Chengdu
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Published In
April 2020
640 pages
ISBN:9781450376457
DOI:10.1145/3436286
- Conference Chairs:
- M. James C. Crabbe,
- Rita Yi Man Li,
- Rebecca Kechen Dong,
- Otilia Manta,
- Ubaldo Comite
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Association for Computing Machinery
New York, NY, United States
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Published: 04 January 2021
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ISBDAI '20
ISBDAI '20: 2020 2nd International Conference on Big Data and Artificial Intelligence
April 28 - 30, 2020
Johannesburg, South Africa
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