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基于随机森林模型的流动人口住院费用报销影响因素及公平性分析:一项来自中国的横断面研究

Analysis of influencing factors and equity in hospitalization expense reimbursement for mobile populations based on random forest model: a cross-sectional study from China.

作者信息

Shen Lisheng, Lu Xinan, Zhang Yanyun, Fei Lin, Dong Bo

机构信息

Department of Medical Insurance Affiliated Cixi Hospital, Wenzhou Medical University, Ningbo, China.

Department of Respiratory and Critical Care Medicine, Affiliated Cixi Hospital, Wenzhou Medical University, Ningbo, China.

出版信息

Front Public Health. 2025 Aug 18;13:1626310. doi: 10.3389/fpubh.2025.1626310. eCollection 2025.

Abstract

BACKGROUND

Continuously improving the accessibility of hospitalization expense reimbursement and reducing the medical expense burden on the migrant population are crucial objectives of China's health insurance system reform. Existing research lacks comprehensive analyses of the current status of hospitalization expense reimbursement for the migrant population, and insufficiently addresses the factors influencing reimbursement and equity. The study aims to identify the key factors influencing the hospitalization expense reimbursement for China's migrant population and to further analyze the equity of this reimbursement.

METHODS

Data were obtained from the 2018 China Migrants Dynamic Survey. After data cleaning, a sample of 3,186 individuals who incurred hospitalization expenses was selected for analysis. First, the current status of hospitalization expense reimbursement (occurrence, location, method, and amount) was analyzed using percentages and chi-square tests. Secondly, the random forest algorithm was applied to evaluate the importance of the factors influencing hospitalization expense reimbursement. Third, the regression analysis was used to quantify the key factors. Finally, the concentration index was utilized to assess the equity of hospitalization expense reimbursement for the migrant population and the contribution of key factors to this equity.

RESULTS

Regarding reimbursement rates, 69.83% of the migrant population chose to reimburse hospitalization expenses, while 30.17% still did not. In terms of reimbursement location, 55.69% reimbursed hospitalization expenses at their place of household registration, and 44.31% at their place of inflow. Regarding reimbursement method, 88.36% chose the Basic Medical Insurance System for Urban and Rural Residents, while 11.64% used the Basic Medical Insurance for Urban Employees. The mean of total hospitalization expenses for the migrant population was 3,058.7 (USD), with health insurance reimbursing 1,213.4 (USD) and individuals paying 1,845.3 (USD) out-of-pocket. The health insurance reimbursement ratio was 39.67%, and the out-of-pocket share was 60.33%. The results of random forest analysis identified the key factors affecting whether the reimbursement occurred as: education, health, age, income, and local insurance enrollment. Key factors affecting the level of reimbursement were: health status, insurance type, total medical expenditure, illness status, and mobility scope. Equity analysis revealed pro-rich inequity (favoring high-income groups) in both the probability and level of hospitalization expense reimbursement. Factors contributing to hospitalization cost reimbursement probability inequity, listed in descending order of impact are education (42.3%), income (34.1%), health (12.4%), age (8.2%), and enrollment location (3.0%); factors contributing to the level of hospitalization reimbursement inequity, listed in descending order of impact are health (58.12%), mobility range (21.74%), total healthcare expenditures (9.35 %), type of healthcare coverage (9.28%), and illness (1.51%).

CONCLUSION

There is still much room for improvement in the reimbursement rate of hospitalization expenses for the migrant population. Future efforts to strengthen protection should: (1) further improve the coordination level of medical insurance to narrow the treatment differences between different regions; (2) encourage migrant populations to enroll locally (in the inflow area) and participate in the Basic Medical Insurance for Urban Employees to increase reimbursement levels; and (3) simplify reimbursement policies, optimize information dissemination channels, and enhance the policy comprehensibility and acceptance to narrow accessibility gaps.

摘要

背景

持续提高住院费用报销的可及性,减轻流动人口的医疗费用负担,是中国医疗保险制度改革的重要目标。现有研究缺乏对流动人口住院费用报销现状的全面分析,对影响报销及公平性的因素探讨不足。本研究旨在识别影响中国流动人口住院费用报销的关键因素,并进一步分析该报销的公平性。

方法

数据来源于2018年中国流动人口动态监测调查。经过数据清理,选取3186名有住院费用支出的个体作为分析样本。首先,采用百分比和卡方检验分析住院费用报销现状(发生率、地点、方式和金额)。其次,应用随机森林算法评估影响住院费用报销因素的重要性。第三,采用回归分析量化关键因素。最后,利用集中指数评估流动人口住院费用报销的公平性以及关键因素对该公平性的贡献。

结果

在报销比例方面,69.83%的流动人口选择报销住院费用,30.17%仍未报销。在报销地点方面,55.69%在户籍所在地报销住院费用,44.31%在流入地报销。在报销方式方面,88.36%选择城乡居民基本医疗保险制度,11.64%使用城镇职工基本医疗保险。流动人口住院总费用均值为3058.7美元,医疗保险报销1213.4美元,个人自付1845.3美元。医疗保险报销比例为39.67%,自付比例为60.33%。随机森林分析结果确定影响报销是否发生的关键因素为:教育程度、健康状况、年龄、收入和当地参保情况。影响报销水平的关键因素为:健康状况、保险类型、总医疗支出、疾病状况和流动范围。公平性分析显示,住院费用报销的概率和水平均存在有利于高收入群体的富人受益不公平现象。导致住院费用报销概率不公平的因素,按影响程度降序排列为:教育程度(42.3%)、收入(34.1%)、健康状况(12.4%)、年龄(8.2%)和参保地点(3.0%);导致住院费用报销水平不公平的因素,按影响程度降序排列为:健康状况(58.12%)、流动范围(21.74%)、总医疗支出(9.35%)、医保覆盖类型(9.28%)和疾病(1.51%)。

结论

流动人口住院费用报销率仍有很大提升空间。未来加强保障的努力方向应包括:(1)进一步提高医疗保险统筹层次,缩小不同地区间的待遇差异;(2)鼓励流动人口在当地(流入地)参保并参加城镇职工基本医疗保险,提高报销水平;(3)简化报销政策,优化信息传播渠道,增强政策的可理解性和接受度,缩小可及性差距。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c31/12399711/57523e9d41ec/fpubh-13-1626310-g0001.jpg

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