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论著·调查与研究 | 更新时间:2025-08-27
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我国卫生资源配置公平与效率研究
Research on fairness and efficiency of health resource allocation in China

广西医学 页码:1186-1195

作者机构:徐兵,硕士,六级职员,研究方向为现代医院管理、卫生健康政策分析等。

基金信息:重庆市科卫联合医学科研项目(2021MSXM011)

DOI:10.11675/j.issn.0253⁃4304.2025.08.16

  • 中文简介
  • 英文简介
  • 参考文献

目的 分析我国卫生资源配置公平和效率及其区域差异,为推动卫生资源优质高效整合提供参考。方法 收集我国31个省(自治区、直辖市)2010—2021年卫生资源投入、产出等相关资料,采用集聚度对我国卫生资源配置公平性进行分析;运用三阶段数据包络分析(DEA)模型对我国卫生资源配置效率进行静态分析,运用Malmquist指数对2010—2021年相关数据进行动态分析。结果 (1)按地理面积配置时,2021年我国各省(自治区、直辖市)卫生物力资源的集聚度取值范围为0.02~25.71,卫生人力资源的集聚度取值范围为0.02~30.89。四大经济区域的卫生资源集聚度(HRAD)表现为东部>中部>1>东北>西部。按人口配置时,医疗卫生机构方面,西藏自治区的HRAD/人口集聚度(PAD)值最大,上海市的HRAD/PAD值最小;实有床位方面,黑龙江省的HRAD/PAD值最大,广东省的HRAD/PAD值最小;在卫生技术人员方面,北京市的HRAD/PAD值最大,江西省的HRAD/PAD值最小。四大经济区域的卫生物力资源的HRAD/PAD值整体表现为东北>西部>中部>1>东部,卫生人力资源的HRAD/PAD表现为东北>西部>东部>1>中部。(2)三阶段DEA调整前,我国卫生资源配置的综合效率、规模效率和纯技术效率平均值分别为0.837、0.935和0.897。重庆市等5个省(自治区、直辖市)为DEA有效状态,辽宁省等26个省(自治区、直辖市)为DEA无效状态。规模报酬方面,31个省(自治区、直辖市)中,规模报酬递增的有15个,规模报酬递减的有11个。调整后我国卫生资源配置综合效率、规模效率和纯技术效率平均值分别为0.798、0.883和0.897,天津市等13个省(自治区、直辖市)综合效率下降,黑龙江省等13个省(自治区、直辖市)综合效率上升。调整后江苏省等8个省(自治区、直辖市)达到了DEA有效状态,新增四川省、江苏省、广东省3个省处于技术前沿面。(3)2010—2021年我国卫生资源配置的全要素生产率指数均值为0.990,年均下降1.00%,各省(自治区、直辖市)间卫生资源配置效率差异较大。上海市等14个省(自治区、直辖市)处于高集聚度高效率地区,北京市等9个省(自治区、直辖市)处于高集聚度低效率地区,西藏自治区等7个省(自治区、直辖市)处于低集聚度低效率地区,云南省处于低集聚度高效率地区。按四大经济区域划分,东部地区和中部地区处于高集聚度高效率地区,而东北地区和西部地区处于低集聚度低效率地区。结论 我国卫生资源配置公平和效率存在不均衡、不协调等问题。同时,卫生资源配置效率不高且呈下降态势,技术进步的提升是卫生资源配置效率提升的关键。建议兼顾多方因素,制订具有地区特色的区域卫生规划,推动区域优质医疗资源均衡分布及合理利用。

Objective To analyze the fairness and efficiency of health resource allocation and their regional differences in China, providing references for promoting high⁃quality and efficient integration of health resources. Methods Data on the input and output of health resources from 31 provinces (autonomous regions, municipalities directly under the central government) from 2010 to 2021 were collected, and the fairness of health resources allocation was analyzed by the degree of agglomeration. The three⁃stage data envelopment analysis (DEA) model was used to conduct a static analysis of the efficiency of health resource allocation in China, and the Malmquist index was used to conduct a dynamic analysis of the relevant data from 2010 to 2021. Results (1) When allocated by geographical area, the agglomeration degree of physical health resources in China's provinces (autonomous regions, municipalities directly under the central government) in 2021 ranged from 0.02 to 25.71, while that of human health resources ranged from 0.02 to 30.89. The health resource agglomeration degree (HRAD) across the four major economic regions showed the pattern of Eastern>Central>1>Northeastern>Western. When allocated by population, in terms of medical institutions, Xizang Autonomous Region had the highest HRAD/population agglomeration degree (PAD) value, while Shanghai had the lowest. For actual hospital beds, Heilongjiang Province had the highest HRAD/PAD value, while Guangdong Province had the lowest. Regarding health technical personnel, Beijing had the highest HRAD/PAD value, while Jiangxi Province had the lowest. For physical health resources, the HRAD/PAD values across the four major economic regions generally followed the pattern of Northeastern>Western>Central>1>Eastern, while for human health resources, the pattern was Northeastern>Western>Eastern>1>Central. (2) Before the three⁃stage DEA adjustment, the average values of comprehensive efficiency, scale efficiency, and pure technical efficiency in China's health resource allocation were 0.837, 0.935, and 0.897, respectively. Five provinces (autonomous regions, municipalities directly under the central government), including Chongqing, were in a DEA⁃effective state, while 26 provinces (autonomous regions, municipalities directly under the central government), such as Liaoning Province, were in a DEA⁃ineffective state. In terms of returns to scale, among the 31 provinces (autonomous regions, municipalities directly under the central government), 15 exhibited increasing returns to scale, and 11 exhibited decreasing returns to scale. After adjustment, the average values of comprehensive efficiency, scale efficiency, and pure technical efficiency in China's health resource allocation changed to 0.798, 0.883, and 0.897, respectively. The comprehensive efficiency declined in 13 provinces (autonomous regions, municipalities directly under the central government), including Tianjin, while it improved in 13 others, such as Heilongjiang. Post⁃adjustment, eight provinces (autonomous regions, municipalities directly under the central government), including Jiangsu, achieved DEA effectiveness, with Sichuan, Jiangsu, and Guangdong newly reaching the technological frontier. (3) From 2010 to 2021, the mean total factor productivity of China's health resource allocation was 0.990, with an average annual decline of 1.00%. There were significant disparities in health resource allocation efficiency among provinces (autonomous regions, municipalities directly under the central government). Shanghai and 13 other provinces (autonomous regions, municipalities directly under the central government) were classified as high⁃agglomeration, high⁃efficiency regions. Beijing and 8 other provinces (autonomous regions, municipalities directly under the central government) fell into high⁃agglomeration, low⁃efficiency regions. Xizang Autonomous Region and 6 other provinces (autonomous regions, municipalities directly under the central government) were categorized as low⁃agglomeration, low⁃efficiency regions. Yunnan Province was the only low⁃agglomeration, high⁃efficiency region. When analyzed by the four major economic regions as follows: the Eastern and Central regions were high⁃agglomeration, high⁃efficiency regions, the Northeastern and Western regions were low⁃agglomeration, low⁃efficiency regions. Conclusion The fairness and efficiency of health resource allocation in China are unbalanced and uncoordinated. At the same time, the efficiency of health resource allocation is low and declining, and the improvement of technological progress is the key to improving the efficiency of health resource allocation. It is recommended to take into account multiple factors, formulate regional health planning with regional characteristics, and promote the balanced distribution and rational use of regional high⁃quality medical resources.

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