Evaluating Risk Factors Affecting Employee Overload in Healthcare Institutions Using Machine Learning Models: Predictions Based on Health Screening Indicators

淡江大學機構典藏 > 商管學院 > 企業管理學系暨研究所 > 會議論文 > Item 987654321/127028

請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/127028

題名:	Evaluating Risk Factors Affecting Employee Overload in Healthcare Institutions Using Machine Learning Models: Predictions Based on Health Screening Indicators
作者:	Chen, Ming-shu;Yang, Wen-jen;Yang, Chih-te;Liu, Tzu-chi;Yang, Ching-tan;Lu, Chi-jie
關鍵詞:	healthcare institutions;overload assessment;employee workload;machine learning;health screening
日期:	2025-01-22
上傳時間:	2025-03-20 12:07:08 (UTC+8)
摘要:	Taiwan’s National Health Insurance (NHI) system only utilizes 6-7% of the nation's GDP, yet it provides high healthcare quality and highly affordable services. However, healthcare staff are under considerable pressure, further exacerbating the strained workforce. This study applies six machine learning algorithms to explore important risk factors related to the excessive workload (overload) of healthcare institution staff, highlighting the significance of understanding these factors. Workload overload refers to the physiological state caused by long-term high stress, a serious 21st-century health issue. In Taiwan, the standard for recognizing overwork is based on workload during the six months and before the onset of illness, as outlined by the "Guidelines for Preventing Diseases Triggered by Abnormal Workload" from the Occupational Safety and Health Administration (OSHA) of the Ministry of Labor, Taiwan. These guidelines serve as a reference for defining working hours and overwork for both employers and employees. The Ministry of Labor mandates annual health checkups for workers across various industries in Taiwan, which includes an assessment of employee overload using the "Employee Overwork Assessment Scale.".
顯示於類別:	[企業管理學系暨研究所] 會議論文

文件中的檔案:

沒有與此文件相關的檔案.

在機構典藏中所有的資料項目都受到原著作權保護.

TAIR相關文章

資料載入中.....