| 引用本文：董恩宏, 严越, 解亚丽, 王益嘉, 王韬, 陈诚, 董四平.我国卫生资源配置区域差异化程度及空间分布趋势研究(2009—2020年)[J].中国卫生政策研究,2022,15(6):73-79 |
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| 我国卫生资源配置区域差异化程度及空间分布趋势研究(2009—2020年) |
| 投稿时间：2022-05-06 修订日期：2022-06-09 PDF全文浏览 HTML全文浏览 |
| 董恩宏1,2, 严越3, 解亚丽4, 王益嘉1, 王韬5, 陈诚6,7, 董四平7,8,9 |
1. 上海健康医学院护理与健康管理学院 上海 201318;
2. 上海交通大学健康长三角研究院 上海 200130;
3. 清华大学医学院 北京 100084;
4. 山东大学齐鲁医院德州医院 山东德州 253014;
5. 同济大学附属东方医院 上海 200127;
6. 武汉科技大学公共卫生学院 湖北武汉 430065;
7. 国家卫生健康委医院管理研究所 北京 100044;
8. 武汉大学政治与公共管理学院 湖北武汉 430072;
9. 福建医科大学卫生健康研究院 福建福州 350004 |
| 摘要:目的：探索我国卫生资源配置集聚性的现状以及空间自相关特征等空间分布特征。方法：使用2009—2020年卫生资源数据，运用全局和局部空间自相关Moran'I指数分析我国31个省(自治区、直辖市)卫生机构数、床位数、医生数、医技数和护士数的集聚指数和空间差异化程度。结果：2009—2020年，我国卫生资源集聚指数中绝大部分指标呈下降趋势，集聚指数平均值每年大部分均在1.0以上；除了机构、床位数呈上升趋势外，卫生人力集聚性的全局空间自相关指数大都呈下降状态；局部Moran's I指数显示我国机构、床位与卫生人力资源集聚性冷热点分布呈东、西差异化不均态势，且机构和床位的需重点关注区域集中在东部省份，卫生人力的需重点关注区域集中在东南、西南省份。结论：2009—2020年我国卫生资源总体集聚呈现空间区域差异化分布趋势，尤其东部和南部省份集聚性相对较低，因此建议总体优化东部资源配置结构、优化调整机构和床位资源存量；做大增量、优化存量、提升西部卫生人力资源质量。 |
| 关键词:集聚指数 区域差异化 卫生资源 空间自相关 |
| 基金项目:国家社科基金重大项目(18ZDA088)；国家社科基金一般项目(19BGL246)；国家社科基金一般项目(18BGL242)；上海市2020年度“科技创新行动计划”软科学重点项目(21692104900) |
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| A study on the degree of regional difference and trend of spatial distribution of health resource allocation in mainland of China from 2009 to 2020 |
| DONG En-hong1,2, YAN Yue3, XIE Ya-li4, WANG Yi-jia1, WANG Tao5, CHEN Cheng6,7, DONG Si-ping7,8,9 |
1. School of Nursing and Health Management, Shanghai University of Medicine and Health Sciences, Shanghai 201318, China;
2. Institute of Healthy Yangtze River Delta, Shanghai Jiaotong University, Shanghai 200130, China;
3. School of Medicine, Tsinghua University, Beijing 100084, China;
4. Qilu Hospital of Shandong University Dezhou Hospital, Dezhou Shandong 253014, China;
5. Shanghai East Hospital, Tongji University, Shanghai 200127, China;
6. School of Public Health, Wuhan University of Science and Technology, Wuhan Hubei 430065, China;
7. National Institute of Hospital Administration, National Health Commission, Beijing 100044, China;
8. School of Political Science and Public Administration, Wuhan University, Wuhan Hubei 430072, China;
9. Health Research Institute, Fujian Medical University, Fuzhou Fujian 350004, China |
| Abstract:Objective: To explore the current status of the agglomeration of health resourcein mainland of China and its spatial distribution characteristics. Methods: Based on the health resource data from 2009 to 2020, global and local spatial autocorrelation Moran'I index was used to analyze the extent of agglomeration and spatial differentiation of the numbers of health institutions, beds, doctors, medical technicians and nurses in 31 provinces of mainland of China. Results: Most of the indicators of nationwide health resource agglomerationshowed a decreasing trend from 2009 to 2020, with the average valuesmostly above 1.0 in each year. Except for the numbers of institutions and beds which showed an increasing trend, most of the global spatial autocorrelation indexes of theagglomeration of health human resource showed a decreasing trend. Moreover, local Moran's I index showed that the hotspotdistribution in the agglomeration of institutions, beds and health human resources in China is unevenly differentiated between the eastern and western regions., and the areas that need strong attentionregarding institutions and beds are mostly in the eastern provinces, whereas areas that need strong attentionregardinghealth human resources are mostly in the southeastern and southwestern provinces.Conclusions: From 2009 to 2020, the distribution of health resource in mainland of Chinagenerally manifesteda trend of spatial and regional differentiation.Especially, the eastern and southern provinces manifested a lowerlevel of agglomeration. Therefore, it is suggested that the resource allocation structure in eastern China should be optimized by optimizing and adjusting institutional and bed resource inventory; on the other hand, the stock of healthcare human resources in western China should be increased and the quality should be improved. |
| Key words:Agglomeration index Regional differentiation Health resources Spatial autocorrelation |
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