Identification of Factors Influencing Out-of-county Hospitalizations in the New Cooperative Medical Scheme
Identification of Factors Influencing Out-of-county Hospitalizations in the New Cooperative Medical Scheme
复制标题
新农合县外住院影响因素的识别
DOI：
10.1007/s11596-019-2115-2
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发表时间：
2019-10-01
影响因子：
2.4
通讯作者：
Yin, Ping
中科院分区：
文献类型：
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作者：
Lu, Wan-rong;Wang, Wen-jie;Yin, Ping
在新农合实施期间，人们发现越来越多的农村患者在县外就医，这给新农合基金带来了巨大的负担。本研究旨在了解县外居民异地就医情况及其影响因素，为后续医保政策制定提供科学依据。2008年至2016年，中国中西部共有215个县入选。九年累计县外住院率为16.95%，由2008年的12.37%上升到2016年的19.21%，年均增长5.66%。相关费用和补偿呈逐年增长趋势，中部地区高于西部地区。逐步Logistic回归分析显示，地区(X1)、农村人口(X2)、人均年纯收入(X3)、人均国内生产总值(X4)、新农合人均筹资金额(X5)、县外住院费用补偿比(X6)、人均县内平均住院费用(X7)和县外住院费用(X8)与县外住院率的增加有关。根据贝叶斯网络(BN)，高县外住院率的边际概率高达81.7%。县外住院与X8、X3、X4、X6直接相关。住院费用因素、经济因素、地域特征和新农合政策因素获得较高的县外住院率分别为95.7%、91.1%、93.0%和88.8%。并找出这些因素对县外住院的影响及其相互关系。研究结果提示，应重视这些因素对异地就医的影响机制，并对异地就医的增长进行合理的监督和控制，以指导制定适当的干预政策。
Throughout the duration of the New Cooperative Medical Scheme (NCMS), it was found that an increasing number of rural patients were seeking out-of-county medical treatment, which posed a great burden on the NCMS fund. Our study was conducted to examine the prevalence of out-of-county hospitalizations and its related factors, and to provide a scientific basis for follow-up health insurance policies. A total of 215 counties in central and western China from 2008 to 2016 were selected. The total out-of-county hospitalization rate in nine years was 16.95%, which increased from 12.37% in 2008 to 19.21% in 2016 with an average annual growth rate of 5.66%. Its related expenses and compensations were shown to increase each year, with those in the central region being higher than those in the western region. Stepwise logistic regression reveals that the increase in out-of-county hospitalization rate was associated with region (X1), rural population (X2), per capita per year net income (X3), per capita gross domestic product (GDP) (X4), per capita funding amount of NCMS (X5), compensation ratio of out-of-county hospitalization cost (X6), per time average in-county (X7) and out-of-county hospitalization cost (X8). According to Bayesian network (BN), the marginal probability of high out-of-county hospitalization rate was as high as 81.7%. Out-of-county hospitalizations were directly related to X8, X3, X4 and X6. The probability of high out-of-county hospitalization obtained based on hospitalization expenses factors, economy factors, regional characteristics and NCMS policy factors was 95.7%, 91.1%, 93.0% and 88.8%, respectively. And how these factors affect out-of-county hospitalization and their interrelationships were found out. Our findings suggest that more attention should be paid to the influence mechanism of these factors on out-of-county hospitalizations, and the increase of hospitalizations outside the county should be reasonably supervised and controlled and our results will be used to help guide the formulation of proper intervention policies.