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韩国老年医疗福利机构的入院因素:一个横截面机器学习研究

Ji Young Lim¹, Eun Joo Kim², Seong Kwang Kim³

¹Inha University, Incheon, Korea (the Republic of).

|August 31, 2025

概括

韩国老年护理机构的入院是由于失去了非正式的护理和严重的健康状况. 机器学习确定了关键预测因素,为人口老龄化制定政策.

科学领域:

老年学
公共卫生
医疗服务研究

背景情况:

韩国面临着人口快速老龄化,
了解影响医疗福利机构入院的因素对于政策制定至关重要.

研究的目的:

确定并对韩国老年医疗福利机构入院的关键预测因素进行排名.
在老龄化社会中利用机器学习提供基于证据的政策建议.

主要方法:

国家医疗保险局高级数据库的横截面二次数据分析.
在48,614名年龄在60至80岁的老年人中进行分层随机抽样.
随机森林模型使用合成少数过量采样技术进行预测分析.

主要成果:

随机森林模型实现了高预测能力 (平衡精度为0.921).
入院的主要预测因素包括与机构工作人员的同居,缺乏主要照顾者,严重痴呆症和功能障碍 (ADL分数).

结论:

老年人护理机构的入院是多因素,受弱化的非正式护理和健康状况的严重下降的影响.
政策干预应侧重于加强社区护理和支持家庭护理人员,以促进当地老龄化.

关键词:

年龄较大机器学习养老院

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Classification of Illness

Classification of Illness

The meaning of illness is individualized to each person who experiences an alteration in health. In contrast, disease is a medical term indicating a pathological change in the structure and function of the body or mind. It is a condition that has specific symptoms and boundaries.
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...