基于集群分析和机器学习的老年人长期护理服务需求分类系统的构建:中国中部的一个多中心,横截面的研究
Fang Li1, Weihong Huang2, Yuting Zeng3
1Teaching and Research Section of Clinical Nursing, Xiangya Hospital, Central South University, Changsha, Hunan, China; National Clinical Research Centre for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China; Department of Cardiology, Xiangya Hospital Central South University, China.
International journal of nursing studies
|January 31, 2026
概括
使用机器学习的新分类系统根据长期护理需求准确识别了五个不同的老年人群. 该系统有助于优化对可持续老年护理服务的资源配置.
科学领域:
- 老年学与公共卫生
- 医疗保健服务研究 医疗服务研究
- 医疗保健中的人工智能
背景情况:
- 全球人口老龄化增加了对老年护理服务的需求.
- 目前的长期护理系统面临着资源限制.
- 有效的分类对于量身定制的资源分配至关重要.
研究的目的:
- 开发一个对老年人长期护理需求的分类系统.
- 使用集群分析和机器学习进行分类.
- 为可持续的老年护理提供指南资源分配.
主要方法:
- 在中国的多中心,横截面研究.
- 分析了1270名老年参与者 (≥65岁).
- 使用集群分析和机器学习模型 (随机森林).
主要成果:
- 确定了五个不同的长期护理需求集群.
- 群体之间的人口结构和需求的显著差异.
- 随机森林模型显示出卓越的预测性能.
结论:
- 开发的分类系统准确地区分了老年人的护理需求.
- 促进最佳的服务分配和资源管理.
- 支持长期护理系统的可持续发展.
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