基于主成分分析和TOPSIS模型的我国各省份医疗水平评价研究  

Evaluation of Medical Level in China by Provinces Based on Principal Component Analysis and TOPSIS Model

作　　者：周洁 胡凌娟[1] 怀晴雨 ZHOU Jie;HU Lingjuan;HUAI Qingyu(School of Management,Beijing University of Traditional Chinese Medicine,Beijing 100029,China)

机构地区：[1]北京中医药大学管理学院,北京市100029

出　　处：《中国全科医学》2023年第34期4254-4260,4268,共8页Chinese General Practice

摘　　要：背景 在新型冠状病毒感染(COVID-19)疫情全国流行期间,我国医疗资源的空间集聚效应凸显,各省份医疗水平存在明显差异,目前,国内学者多运用定量方法对当前全国各省份医疗水平进行评价,应用综合方法评价全国各省份医疗水平者较少。目的 了解我国各省份在医疗卫生事业发展水平上的差异,以期为医疗卫生事业决策者提供参考。方法 于2022年11月,计算机检索中国知网、万方数据知识服务平台和Web of Science数据库,检索有关医疗水平评价的文献。在借鉴现有研究成果的基础上,选取相对指标和平均指标来构建评价指标体系。以《2022中国卫生健康统计年鉴》为数据源,提取/计算各评价指标数据。运用主成分分析法和TOPSIS模型,对我国31个省份(未将中国香港特别行政区、中国澳门特别行政区、中国台湾地区纳入统计范畴)的医疗水平进行综合评价。结果 共检索出合格文献6篇,从医疗资源、医疗服务、医疗保障3个方面选取13个相对指标和平均指标构建评价体系。KMO值为0.733,Bartlett's球形检验结果显示,χ^(2)=346.908、P<0.001,提示数据适用于主成分分析;按照特征根>1.000的标准可提取4个主成分,分别为医疗资源规模和医疗服务质量(F1)、医疗机构工作效率(F2)、传染病控制能力(F3)、其他因素(F4),4个主成分的累积方差贡献率为84.012%。根据主成分得分系数矩阵建立各主成分线性模型后,基于4个主成分的方差贡献率得到可用于评价医疗水平的综合评价模型:Y=0.439 85×Y1+0.158 54×Y2+0.154 40×Y3+0.087 34×Y4。医疗水平综合得分位列前3位的省份分别为北京市(151.908分)、上海市(124.379分)、天津市(78.673分)。TOPSIS贴近度排名结果显示,北京市和上海市处于靠前水平(贴近度分别为0.767、0.646),以贴近度0.400和0.201为节点,可以将31个省份分为3个梯队,第1梯队有北京市、上海市和天津市3个�Background During the nationwide epidemic of COVID-19 infection,the spatial agglomeration of medical resources in China has been highlighted,and there are obvious differences in medical level among provinces.Currently,the evaluation of medical level in China by provinces was mainly conducted by domestic scholars using quantitative methods,while comprehensive method was less applied to evaluate the medical level by provinces.Objective To understand the differences in the level of healthcare development in China by provinces,so as to provide a reference for healthcare decision makers.Methods In November 2022,CNKI,Wanfang Data Knowledge Service Platform,and Web of Science were searched by computer for the researches in the field of medical level.Based on the existing research results,relative and average indicators were selected to construct the evaluation index system.The data of each evaluation index was extracted or calculated by using China Health and Health Statistical Yearbook 2022 as the data source.Using the principal component analysis and TOPSIS model,the medical levels of 31 provinces in China(Hong Kong Special Administrative Region,Macao Special Administrative Region and Taiwan Province were not included in the statistics)were comprehensively evaluated.Results A total of 6 qualified papers were retrieved and 13 relative and average indicators were selected from three aspects of medical resources,medical services,and medical security to construct the evaluation system.The KMO value was 0.733,and Bartlett's spherical test showed thatχ2=346.908,P<0.001,suggesting that the data were suitable for principal component analysis;four principal components were extracted according to the criterion of characteristic root above 1.000,including the scale of medical resources and quality of medical services(F1),the efficiency of medical institutions(F2),infectious disease control ability(F3),and other factors(F4),and the cumulative percent variance of the four principal components was 84.012%.After establishing the li

关 键 词：医疗水平评价 主成分分析法 TOPSIS模型 卫生保健质量 获取和评价 质量改进 

分 类 号：R197[医药卫生—卫生事业管理]