At present, the problem of regional imbalance and lack of fairness in the allocation of medical resources in China remains prominent. The report of the 20th National Congress of the Communist Party of China clearly stated that it is necessary to promote the expansion of high-quality medical resources and balanced regional layout.

To explore the specific path to improve the efficiency of medical resource allocation in China, and provide scientific reference for realizing the rational and high-efficient allocation of medical resources in China and promoting the equalization of basic public services.

The study was conducted from September 2022 to February 2023, and the data were derived from the 2021 China Statistical Yearbook and 2021 China Health Statistics Yearbook. The data envelopment analysis (DEA) method was used to measure the efficiency of medical resource allocation in 31 provinces of China in 2020, considering the number of healthcare institutions, health technicians, and beds as input indicators, the number of visits and admissions as output indicators. Fuzzy-set Qualitative Comparative Analysis (fsQCA) was used to explore the synergistic influence mechanism of internal and external factors on the efficiency of medical resource allocation from a group perspective, taking resource allocation efficiency as the outcome variable, the ratio of health technicians, number of beds per 1 000 population, average hospitalization days of discharged patients, gross domestic product (GDP) per capita, disposable income of the residents, the fiscal revenue decentralization, and ratio of the budgetary expenditures on healthcare as conditional variables, to analyze the conditional configuration of high or non-high level of healthcare resource allocation efficiency, and clarify the multiple paths of efficient and inefficient allocation of medical resources.

In 2020, the overall level of medical resource allocation efficiency in 31 provinces of China is relatively high, with an average of 0.852, but there were large differences among provinces. The results of configuration analysis showed that the improvement of medical resource allocation efficiency is the result of multiple factors, there are three paths for efficient allocation of medical resources. Path 1: government-led driving path, taking Guangxi Zhuang Autonomous Region as a typical case; Path 2: internal and external coordination driving path, represented by Yunnan Province and Gansu Province; Path 3: balanced driving path, with Guangdong Province, Fujian Province and Hubei Province as representative cases. There are also three paths of non-high medical resource allocation efficiency. Path 1: government-restricted path; Path 2: economic-government dual restriction path, representative cases included Heilongjiang and Jilin Province; Path 3: internal and external constraints path, the typical cases were Shanxi Province and Tibet Autonomous Region.

The internal and external elements and synergies between elements jointly affect the allocation of medical resources in the process of benign interaction, it is necessary to optimize the internal and external environment, and effectively integrate the key resource elements to form a joint force to promote the rational allocation of regional medical resources.

当前我国医疗资源配置区域失衡、公平性缺失问题仍然突出。党的"二十大"报告明确提出要"促进优质医疗资源扩容和区域均衡布局"。

探究提升我国医疗资源配置效率的具体路径，为实现我国医疗资源合理且高效配置、促进基本公共服务均等化提供科学参考。

于2022年9月—2023年2月开展研究，数据源于《2021中国统计年鉴》《2021中国卫生健康统计年鉴》。将医疗卫生机构数、卫生技术人员数、床位数作为投入指标，以诊疗人次和入院人数为产出指标，通过数据包络分析（DEA）方法对我国2020年31个省份医疗资源配置效率进行测度；以医疗资源配置效率为结果变量，以卫生技术人员占比、每千人口床位数、出院者平均住院日、人均国内生产总值（GDP）、居民可支配收入、财政收入分权和医疗卫生财政预算支出占比为条件变量，运用模糊集定性比较分析（fsQCA）方法从组态视角探究内外部要素对医疗资源配置效率的协同影响机制，剖析高或非高水平医疗资源配置效率的条件组态，明确医疗资源高效率和低效率配置的多重路径。

2020年我国31个省份医疗资源配置效率整体水平较高，均值为0.852，但省际存在较大差异。组态分析结果可知，医疗资源配置效率的提升是多因素共同作用的结果，共存在3种医疗资源高效率配置的路径。路径1：政府主导型驱动路径，以广西壮族自治区为典型案例。路径2：内外协调型驱动路径，以云南省和甘肃省为代表案例。路径3：均衡型驱动路径，代表案例主要有广东省、福建省和湖北省。非高医疗资源配置效率的路径也存在3条。路径1：政府制约型路径。路径2：经济-政府双重制约型路径，代表案例有黑龙江省和吉林省。路径3：内外制约型路径，典型案例有山西省和西藏自治区。

内外部各要素及要素间的协同在良性互动过程中共同影响着医疗资源配置效率水平，需优化内外部环境，并对关键资源要素进行有效整合，以形成合力，促进区域医疗资源合理配置。