Factors associated with admission to elderly medical-welfare facilities in South Korea: a cross-sectional machine-learning study.

ABSTRACT:

Objectives

To identify the key factors associated with admission to elderly medical-welfare facilities in South Korea and to evaluate their relative importance using machine learning techniques, providing an evidence base for policy in a rapidly ageing society.

Design

A cross-sectional secondary data analysis.

Setting

The analysis was conducted using the National Health Insurance Service -Senior database, a large-scale public dataset constructed to be statistically representative of the elderly population in South Korea.

Participants

A total of 48 614 elderly individuals aged 60-80 years, selected through a scientifically rigorous stratified random sampling method.

Primary and secondary outcome measures

The primary outcome was the binary classification o

SUBMITTER: Lim JY 

PROVIDER: S-EPMC12406814 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature