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基于机器学习算法的中国西部欠发达地区医院医务人员薪酬水平及满意度影响因素分析:以广西壮族自治区为例

Analysis of the factors influencing the salary level and satisfaction of medical staff in hospitals in less developed areas of Western China based on machine learning algorithms: evidence from Guangxi Zhuang Autonomous Region.

作者信息

Xu Xinyi, Gao Qisheng, Wu Tengyan, Zhuang Wenhui, Mo Yejia, Zhang Wenjun, Wei Bo, Tang Zhong, Zhu Pinghua

机构信息

Department of Humanities and Social Sciences, Guangxi Medical University, Shuangyong Road, Qingxiu District, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China.

School of Public Health, Hangzhou Medical College, Binwen Road, Hangzhou, Zhejiang Province, 310059, People's Republic of China.

出版信息

BMC Health Serv Res. 2025 Mar 14;25(1):380. doi: 10.1186/s12913-025-12552-9.

Abstract

BACKGROUND

Compensation plays a critical role in motivating staff and enhancing operational performance and human resource costs in hospitals. This study was aimed at investigating pay levels and the key factors influencing pay satisfaction in secondary and tertiary public hospitals in Guangxi.

METHODS

Questionnaires were distributed to 48 hospitals across 14 prefecture-level cities in Guangxi. Information on personal characteristics, salary levels, work situations and perceptions of current salary conditions was provided by 10,343 staff in secondary and tertiary hospitals. Five machine learning models were employed to identify the most significant influencing factors of salary satisfaction in Guangxi public hospitals.

RESULTS

Overall, the actual total after-tax income in secondary public hospitals in Guangxi ranged from $466.55-$744, while the income of staff in municipal-level tertiary public hospitals ranged from $5,001 to $1,041.75 per month. Among the five models, the support vector machine (SVM) demonstrated the best performance in analyzing the influencing factors of compensation satisfaction. The most influential factors for total compensation satisfaction included the extent to which compensation reflected labor value, salary increases since 2017 compared to peer hospitals, total after-tax income and the difference in compensation between staff within and outside the establishment of hospitals. Satisfaction with salary growth aligned closely with the factors influencing overall compensation satisfaction. Satisfaction with pay equity was also influenced by the ability of salary gaps between different positions to reflect differential effort.

CONCLUSIONS

A relatively low pay level in secondary hospitals in Guangxi was revealed. The factors influencing satisfaction with total pay, pay fairness and pay growth since 2017 varied. SVM outperformed other models in the analysis of the factors influencing pay satisfaction. To enhance pay satisfaction in secondary and tertiary hospitals in Guangxi, it is crucial to establish a salary distribution system aligned with the value of labor across different positions and tailored to the unique characteristics of each hospital.

摘要

背景

薪酬在激励医院员工、提升运营绩效以及控制人力资源成本方面发挥着关键作用。本研究旨在调查广西二级和三级公立医院的薪酬水平以及影响薪酬满意度的关键因素。

方法

向广西14个地级市的48家医院发放问卷。广西二级和三级医院的10343名员工提供了个人特征、薪资水平、工作情况以及对当前薪资状况看法等方面的信息。采用五种机器学习模型来确定广西公立医院薪酬满意度的最重要影响因素。

结果

总体而言,广西二级公立医院员工的实际月税后总收入在466.55美元至744美元之间,市级三级公立医院员工的月收入在5001美元至1041.75美元之间。在这五种模型中,支持向量机(SVM)在分析薪酬满意度影响因素方面表现最佳。总体薪酬满意度的最具影响力因素包括薪酬反映劳动价值的程度、与同级别医院相比2017年以来的薪资增长、月税后总收入以及在编和非在编员工之间的薪酬差异。薪资增长满意度与影响总体薪酬满意度的因素密切相关。薪酬公平性满意度还受到不同职位间薪资差距反映努力程度差异能力的影响。

结论

研究揭示了广西二级医院薪酬水平相对较低的情况。2017年以来影响总体薪酬、薪酬公平性和薪酬增长满意度的因素各不相同。在分析影响薪酬满意度的因素方面,支持向量机的表现优于其他模型。为提高广西二级和三级医院的薪酬满意度,关键在于建立与不同职位劳动价值相匹配、适合每家医院独特特征的薪酬分配体系。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1de3/11908026/459a4406a16d/12913_2025_12552_Fig1_HTML.jpg

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