关键词: 社区卫生服务, 熵权法, 模型, 统计学, 数据分析

Abstract: Objective To measure the inter-provincial community health service （CHS） level in China and diagnose the obstacles restricting the CHS level. Methods Average scores of the inter-provincial CHS level across the country was estimated according to the “Evaluation Index System of Community Health Service Quality”. Entropy weight method, exploratory spatial data analysis method and obstacle degree model were used to analyze and evaluate the average scores in 2016. Results The average score of CHS in China was 0.277 3. The highest score of CHS was 0.863 8 in Guangdong, and the lowest was 0.013 6 in Tibet, and the difference between the highest score and the lowest was 0.850 2. The provinces with high levels of inter-provincial CHS were Guangdong, Jiangsu, Shanghai, Zhejiang, and Shandong; the middle and high-level provinces were Hubei, Sichuan, Beijing, Hunan, Henan, Chongqing, and Anhui; the middle and low-level provinces were Fujian and Liaoning, Tianjin, Hebei, and Heilongjiang; the low-level provinces are Yunnan, Inner Mongolia, Guangxi, Xinjiang, Shaanxi, Shanxi, Guizhou, Jiangxi, Gansu, Jilin, Hainan, Ningxia, Qinghai, and Tibet. From the national perspective, the I₆ （bed occupancy rate） and I₇ （mean hospitalization day） were the two major obstacles that hindered the improvement of CHS levels in the central and western provinces. The I₄ （number of admissions） was the primary obstacle to the improvement of CHS in the eastern provinces. Conclusion The levels of CHS in the eastern, central and western regions of China were quite different. The overall CHS level in the eastern provinces was higher than that in the central and western ones. It is suggested that health resources should be allocated reasonably and attention should be paid to the development of low-level areas to narrow the gap of inter-provincial CHS level.

Key words: Community health services, Entropy weight method, Model, statistics, Data analysis