Zhou Minghua
Department of administration office, Luzhou People's Hospital, Luzhou, Sichuan, China.
PLoS One. 2025 Sep 2;20(9):e0331645. doi: 10.1371/journal.pone.0331645. eCollection 2025.
To analyze the capacity and influencing factors of primary health care services and to provide a scientific basis for promoting the development of primary health care services in China.
The entropy weight technique for order preference by similarity to ideal solution (TOPSIS) and rank‒sum ratio (RSR) methods, which are based on the health resource density index (HRDI), were used to analyze the capacity of primary health care services, and multiple stepwise regression analysis was used to analyze the influencing factors.
Taking the HRDI of primary health care service capacity in 2021 as a reference, the six evaluation indicators of 14 regions, including Hebei, Liaoning, and Shanghai, were higher than the Chinese average. According to the entropy weight TOPSIS method, the average C-values of primary health care service capacity in China from 2017-2021 were 0.303, 0.313, 0.324, 0.331, and 0.326, respectively, with the C-values of regions such as Shanghai, Beijing, and Henan ranking in the top ten, whereas those of regions such as Xinjiang, Qinghai, and Tibet ranked in the bottom five. According to grade divisions by the RSR method, Tianjin, Shandong, Jiangsu, Shanghai, and Beijing were ranked at the good grade level; Xinjiang, Qinghai, Inner Mongolia, and Tibet at the poor grade level; and the remaining 22 regions at the medium grade level. According to the multivariate stepwise regression, population density, health technicians, and the number of beds per 1,000 people were the main factors affecting the capacity of primary health care services in China.
The overall capacity of primary health care services in China is not high, and regional disparities are substantial. The capacity of primary health care services is better in Tianjin, Shandong, Jiangsu, Shanghai and Beijing and worse in Xinjiang, Qinghai, Inner Mongolia and Tibet. The population density and number of health technicians per 1,000 people are the main factors affecting the capacity of primary health care services in China.
分析基层医疗卫生服务能力及其影响因素,为促进我国基层医疗卫生服务发展提供科学依据。
采用基于卫生资源密度指数(HRDI)的熵权逼近理想解排序法(TOPSIS)和秩和比(RSR)法分析基层医疗卫生服务能力,并采用多元逐步回归分析影响因素。
以2021年基层医疗卫生服务能力的HRDI为参照,河北、辽宁、上海等14个地区的6项评价指标高于全国平均水平。根据熵权TOPSIS法,2017—2021年我国基层医疗卫生服务能力的平均C值分别为0.303、0.313、0.324、0.331和0.326,上海、北京、河南等地区的C值排名前十,而新疆、青海、西藏等地区排名后五位。根据RSR法等级划分,天津、山东、江苏、上海和北京处于良好等级水平;新疆、青海、内蒙古和西藏处于较差等级水平;其余22个地区处于中等等级水平。根据多元逐步回归分析,人口密度、卫生技术人员、每千人口床位数是影响我国基层医疗卫生服务能力的主要因素。
我国基层医疗卫生服务整体能力不高,地区差异较大。天津、山东、江苏、上海和北京的基层医疗卫生服务能力较好,新疆、青海、内蒙古和西藏较差。人口密度和每千人口卫生技术人员数是影响我国基层医疗卫生服务能力的主要因素。