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Article(id=1323941325317480579, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1323941237702668764, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202504337, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1745337600000, receivedDateStr=2025-04-23, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793581809596, onlineDateStr=2026-11-02, pubDate=1765296000000, pubDateStr=2025-12-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793581809596, onlineIssueDateStr=2026-11-02, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793581809596, creator=13701087609, updateTime=1793581809596, updator=13701087609, issue=Issue{id=1323941237702668764, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='23', pageStart='4225', pageEnd='4416', issueExtLink='null', onlineDate='null', pubDate='1765296000000', pubDateStr='2025-12-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1793581788707, creator='13701087609', updateTime=1793581887795, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1323941653374959780, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1323941237702668764, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1323941653374959781, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1323941237702668764, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=4339, endPage=4345, ext={EN=ArticleExt(id=1323941327100059780, articleId=1323941325317480579, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Efficiency and improvement paths of community home care services based on three-stage DEA and FsQCA, columnId=1228016567846367388, journalTitle=Modern Preventive Medicine, columnName=Health Policy and Management, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze the specific paths of the resource allocation efficiency of community home care in China and provide strong support for the balanced development of the resource allocation of such services.

Methods

Based on the relevant data from China Civil Affairs Statistical Yearbook, China Statistical Yearbook, China Health Statistics Yearbook, and China Social Statistics Yearbook (2020—2023), this study used the Data Envelopment Analysis (DEA) method to measure the allocation efficiency of community-based home care resources in China. On this basis, the Fuzzy-set qualitative comparative analysis (fsQCA) was employed to explore the configurational paths for the efficient allocation of community-based home care resources.

Results

The average values of the comprehensive efficiency, pure technical efficiency, and scale efficiency of community home care services in China were 0.533, 0.640, and 0.810, respectively. There were significant differences among different regions and provinces. There were three paths to improve the efficiency of community home care services, with an overall consistency of 0.925, indicating a strong explanatory power of the model.

Conclusion

The overall efficiency level of community home care services needs to be enhanced. It is recommended to optimize management processes and technological innovation, strengthen the radiation and driving force of advantageous regions, precisely expand the scale of the elderly care industry, effectively improve the resource allocation efficiency, adhere to the principle of development based on local conditions, and explore new differentiated elderly care paths.

, authors=Shuang HAN1, Xiu-ming HUANG2, Xiao-wei TIAN1, Xin-yu ZHANG1, Yang KONG1, authorsList=Shuang HAN, Xiu-ming HUANG, Xiao-wei TIAN, Xin-yu ZHANG, Yang KONG, authorCompany=null, correspAuthors=Yang KONG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1323941327896977543, articleId=1323941325317480579, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=基于三阶段DEA-FsQCA的社区居家养老资源配置效率及组态路径研究, columnId=1228016568014139551, journalTitle=现代预防医学, columnName=卫生政策与管理, runingTitle=null, highlight=null, articleAbstract=
目的

分析我国社区居家养老资源配置效率的具体路径，为实现社区居家养老服务资源配置均衡发展提供有力支撑。

方法

基于2020—2023年《中国民政统计年鉴》《中国统计年鉴》《中国卫生健康统计年鉴》《中国社会统计年鉴》中相关数据，采用数据包络分析法对我国社区居家养老资源配置效率进行测算，在此基础上借助模糊集定性比较分析法探究社区居家养老资源高效配置组态路径。

结果

我国社区居家养老服务综合效率、纯技术效率、规模效率的均值分别为0.533、0.640、0.810，各地区和省份之间存在显著差异；提升社区居家养老资源配置效率的路径有三条，总体一致性为0.925，模型解释力较强。

结论

社区居家养老资源配置效率整体水平有待提升，建议优化管理流程和技术创新，增强优势区域辐射带动力；精准拓宽养老产业规模，有效提升资源配置效率；秉持因地制宜发展原则，探寻差异化养老新路径。

, authors=韩霜1, 黄修明2, 田晓伟1, 张新宇1, 孔杨1, authorsList=韩霜, 黄修明, 田晓伟, 张新宇, 孔杨, authorCompany=null, correspAuthors=孔杨, authorNote=

韩霜（2001—），女，硕士在读，研究方向：养老服务与管理、卫生事业管理

, correspAuthorsNote=
孔杨，E-mail：
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韩霜（2001—），女，硕士在读，研究方向：养老服务与管理、卫生事业管理

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韩霜（2001—），女，硕士在读，研究方向：养老服务与管理、卫生事业管理

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注：A高效率； B低效率。

, figureFileSmall=GQ3odRnC2laY53ZWGDmyZg==, figureFileBig=A8j6mvXIrmwSonsw/vpfEw==, tableContent=null), ArticleFig(id=1323941332640735409, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1323941325317480579, language=EN, label=Table 1, caption=

Index system of input, output and environmental variables

, figureFileSmall=null, figureFileBig=null, tableContent=
一级指标二级指标单位
投入指标社区日间照料床位数张
社区居家养老服务站和设施数个
社区居家养老服务人员数人
社区卫生服务站卫生技术人员数人
老年福利支出万元
产出指标社区日间照料养老服务人次人次
社区卫生服务中心家庭卫生服务人次人次
环境变量老年抚养比%
人均公园和绿地面积人/平方米
老年人均养老机构和设施建筑面积人/平方米
), ArticleFig(id=1323941332724621490, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1323941325317480579, language=CN, label=表1, caption=

投入、产出及环境变量指标体系

, figureFileSmall=null, figureFileBig=null, tableContent=
一级指标二级指标单位
投入指标社区日间照料床位数张
社区居家养老服务站和设施数个
社区居家养老服务人员数人
社区卫生服务站卫生技术人员数人
老年福利支出万元
产出指标社区日间照料养老服务人次人次
社区卫生服务中心家庭卫生服务人次人次
环境变量老年抚养比%
人均公园和绿地面积人/平方米
老年人均养老机构和设施建筑面积人/平方米
), ArticleFig(id=1323941332816896179, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1323941325317480579, language=EN, label=Table 2, caption=

Operation results of traditional DEA model

, figureFileSmall=null, figureFileBig=null, tableContent=
地区省份传统DEA模型结果
综合效率纯技术效率规模效率规模报酬
东部北京1.0001.0001.000—
天津0.6270.7510.835irs
河北0.4280.4290.998irs
上海0.6110.6790.899irs
江苏0.7050.8110.869drs
浙江1.0001.0001.000—
福建1.0001.0001.000—
山东0.7940.7970.997irs
广东0.9601.0000.960drs
海南0.7391.0000.739irs
东北辽宁0.8390.8730.960irs
吉林1.0001.0001.000—
黑龙江0.7530.8080.932irs
中部山西1.0001.0001.000—
安徽1.0001.0001.000—
江西0.5410.5460.990drs
河南0.6510.6530.997irs
湖北1.0001.0001.000—
湖南0.5010.5080.986drs
西部四川0.9150.9190.996drs
内蒙古1.0001.0001.000—
重庆0.7510.7770.966irs
广西0.3570.4160.858irs
贵州0.2310.2580.894irs
云南0.1930.2370.814irs
西藏1.0001.0001.000—
陕西0.5060.6760.749irs
甘肃0.6870.8530.806irs
青海0.5010.8120.616irs
宁夏0.8711.0000.871irs
新疆0.5100.5740.889irs
东部均值0.7860.8470.930
东北均值0.8640.8940.964
中部均值0.7820.7850.996
西部均值0.6270.7100.872
全国均值0.7310.7860.923
), ArticleFig(id=1323941332959502516, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1323941325317480579, language=CN, label=表2, caption=

传统DEA模型运行结果

, figureFileSmall=null, figureFileBig=null, tableContent=
地区省份传统DEA模型结果
综合效率纯技术效率规模效率规模报酬
东部北京1.0001.0001.000—
天津0.6270.7510.835irs
河北0.4280.4290.998irs
上海0.6110.6790.899irs
江苏0.7050.8110.869drs
浙江1.0001.0001.000—
福建1.0001.0001.000—
山东0.7940.7970.997irs
广东0.9601.0000.960drs
海南0.7391.0000.739irs
东北辽宁0.8390.8730.960irs
吉林1.0001.0001.000—
黑龙江0.7530.8080.932irs
中部山西1.0001.0001.000—
安徽1.0001.0001.000—
江西0.5410.5460.990drs
河南0.6510.6530.997irs
湖北1.0001.0001.000—
湖南0.5010.5080.986drs
西部四川0.9150.9190.996drs
内蒙古1.0001.0001.000—
重庆0.7510.7770.966irs
广西0.3570.4160.858irs
贵州0.2310.2580.894irs
云南0.1930.2370.814irs
西藏1.0001.0001.000—
陕西0.5060.6760.749irs
甘肃0.6870.8530.806irs
青海0.5010.8120.616irs
宁夏0.8711.0000.871irs
新疆0.5100.5740.889irs
东部均值0.7860.8470.930
东北均值0.8640.8940.964
中部均值0.7820.7850.996
西部均值0.6270.7100.872
全国均值0.7310.7860.923
), ArticleFig(id=1323941333110497461, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1323941325317480579, language=EN, label=Table 3, caption=

Regression results of SFA model

, figureFileSmall=null, figureFileBig=null, tableContent=
类别社区日间照料床位数社区居家养老服务站
和设施数		社区居家养老
服务人员数		社区卫生服务站
卫生技术人员数		老年福利支出
标准化系数t值标准化系数t值标准化系数t值标准化系数t值标准化系数t值
常数项-1.91×105-1.91×105-7.29×104-7.28×104-5.39×105-8.28×103-7.98×103-5.39×1034.63×1052.26×104
老年抚养比1.21×1031.21×1035.43×1021.41×1031.72×1032.235.16×1027.476.01×1039.19
人均绿地和公园面积6.81×1026.81×1021.30×10240.701.71×1031.67-6.82×102-1.14-2.04×10487.20
老年人均养老机构和设施建筑面积-5.92×103-5.92×1031.77×1031.74×1031.58×10435.20-2.94×102-1.58×102-1.49×104-2.69×102
σ22.97×10102.97×10103.30×1093.30×1095.66×10105.66×10101.16×1091.16×1095.27×10115.36×1011
γ1.0020.301.001.12×1071.0065.001.001.07×1061.003.75×104
对数似然函数-396.284 1-361.111 0-406.810 4-348.572 2-440.881 7
LR单边检验14.196 716.436 913.125 19.142 414.164 5
), ArticleFig(id=1323941333223743670, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1323941325317480579, language=CN, label=表3, caption=

SFA模型回归结果

, figureFileSmall=null, figureFileBig=null, tableContent=
类别社区日间照料床位数社区居家养老服务站
和设施数		社区居家养老
服务人员数		社区卫生服务站
卫生技术人员数		老年福利支出
标准化系数t值标准化系数t值标准化系数t值标准化系数t值标准化系数t值
常数项-1.91×105-1.91×105-7.29×104-7.28×104-5.39×105-8.28×103-7.98×103-5.39×1034.63×1052.26×104
老年抚养比1.21×1031.21×1035.43×1021.41×1031.72×1032.235.16×1027.476.01×1039.19
人均绿地和公园面积6.81×1026.81×1021.30×10240.701.71×1031.67-6.82×102-1.14-2.04×10487.20
老年人均养老机构和设施建筑面积-5.92×103-5.92×1031.77×1031.74×1031.58×10435.20-2.94×102-1.58×102-1.49×104-2.69×102
σ22.97×10102.97×10103.30×1093.30×1095.66×10105.66×10101.16×1091.16×1095.27×10115.36×1011
γ1.0020.301.001.12×1071.0065.001.001.07×1061.003.75×104
对数似然函数-396.284 1-361.111 0-406.810 4-348.572 2-440.881 7
LR单边检验14.196 716.436 913.125 19.142 414.164 5
), ArticleFig(id=1323941333332795575, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1323941325317480579, language=EN, label=Table 4, caption=

Operation results of adjusted DEA model

, figureFileSmall=null, figureFileBig=null, tableContent=
地区省份传统DEA模型结果
综合效率纯技术效率规模效率规模报酬
东部北京1.0001.0001.000—
天津0.4080.6770.602irs
河北0.3850.4070.946irs
上海0.3270.4780.683irs
江苏0.7070.7460.947drs
浙江0.8800.8820.998irs
福建0.6600.6770.974irs
山东1.0001.0001.000—
广东0.9591.0000.959drs
海南0.1000.4600.217irs
东北辽宁0.5110.5610.911irs
吉林0.5310.6080.872irs
黑龙江0.4000.4660.858irs
中部山西0.8360.8990.930irs
安徽1.0001.0001.000—
江西0.3820.3970.963irs
河南0.5720.5750.996irs
湖北0.8280.8360.990irs
湖南0.4370.4400.993irs
西部四川0.5020.5660.888irs
内蒙古0.7440.8020.928irs
重庆0.5550.6030.920irs
广西0.2620.3420.767irs
贵州0.1950.2560.761irs
云南0.1280.2740.467irs
西藏0.1241.0000.124irs
陕西0.2110.3600.585irs
甘肃0.4370.5760.759irs
青海0.1880.5840.321irs
宁夏0.9601.0000.960irs
新疆0.2860.3620.791irs
东部均值0.6430.7330.833
东北均值0.4810.5450.880
中部均值0.6760.6910.979
西部均值0.3830.5600.689
全国均值0.5330.6400.810
), ArticleFig(id=1323941333433458872, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1323941325317480579, language=CN, label=表4, caption=

调整后DEA模型运行结果

, figureFileSmall=null, figureFileBig=null, tableContent=
地区省份传统DEA模型结果
综合效率纯技术效率规模效率规模报酬
东部北京1.0001.0001.000—
天津0.4080.6770.602irs
河北0.3850.4070.946irs
上海0.3270.4780.683irs
江苏0.7070.7460.947drs
浙江0.8800.8820.998irs
福建0.6600.6770.974irs
山东1.0001.0001.000—
广东0.9591.0000.959drs
海南0.1000.4600.217irs
东北辽宁0.5110.5610.911irs
吉林0.5310.6080.872irs
黑龙江0.4000.4660.858irs
中部山西0.8360.8990.930irs
安徽1.0001.0001.000—
江西0.3820.3970.963irs
河南0.5720.5750.996irs
湖北0.8280.8360.990irs
湖南0.4370.4400.993irs
西部四川0.5020.5660.888irs
内蒙古0.7440.8020.928irs
重庆0.5550.6030.920irs
广西0.2620.3420.767irs
贵州0.1950.2560.761irs
云南0.1280.2740.467irs
西藏0.1241.0000.124irs
陕西0.2110.3600.585irs
甘肃0.4370.5760.759irs
青海0.1880.5840.321irs
宁夏0.9601.0000.960irs
新疆0.2860.3620.791irs
东部均值0.6430.7330.833
东北均值0.4810.5450.880
中部均值0.6760.6910.979
西部均值0.3830.5600.689
全国均值0.5330.6400.810
), ArticleFig(id=1323941333508956345, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1323941325317480579, language=EN, label=Table 5, caption=

Calibration results of various variables

, figureFileSmall=null, figureFileBig=null, tableContent=
变量类型变量名称权重目标集合定位锚点
完全隶属交叉点完全不隶属
结果变量综合效率1综合效率0.8590.5470.335
条件变量老龄补贴投入0.036 7政府补贴2.7892.0220.646
高学历社区居家养老服务人员数0.123 7专业化水平4 975.6102 856.8101 443.350
社会工作师数0.127 2
人均社会养老保险支出0.031 0社会保障212.368152.068134.917
最低生活保障平均标准0.006 2
人均可支配收入0.006 1生活水平840.262707.582632.853
生活垃圾无害化处理能力0.122 4居住环境1 590 000839 333437 192
互联网接入端口数0.117 6
城镇环境基础设施投资0.120 2
有线广播电视实际用户数0.117 2文化休闲372.942287.688168.522
人均水资源0.175 9资源环境2 329.4201 300.430287.776
森林覆盖率0.015 7
), ArticleFig(id=1323941333592842426, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1323941325317480579, language=CN, label=表5, caption=

各类变量校准结果

, figureFileSmall=null, figureFileBig=null, tableContent=
变量类型变量名称权重目标集合定位锚点
完全隶属交叉点完全不隶属
结果变量综合效率1综合效率0.8590.5470.335
条件变量老龄补贴投入0.036 7政府补贴2.7892.0220.646
高学历社区居家养老服务人员数0.123 7专业化水平4 975.6102 856.8101 443.350
社会工作师数0.127 2
人均社会养老保险支出0.031 0社会保障212.368152.068134.917
最低生活保障平均标准0.006 2
人均可支配收入0.006 1生活水平840.262707.582632.853
生活垃圾无害化处理能力0.122 4居住环境1 590 000839 333437 192
互联网接入端口数0.117 6
城镇环境基础设施投资0.120 2
有线广播电视实际用户数0.117 2文化休闲372.942287.688168.522
人均水资源0.175 9资源环境2 329.4201 300.430287.776
森林覆盖率0.015 7
), ArticleFig(id=1323941333689311419, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1323941325317480579, language=EN, label=Table 6, caption=

Configuration analysis results of high efficiency conditions

, figureFileSmall=null, figureFileBig=null, tableContent=
条件组合H1aH1bH1cH2H3
政府补贴○▼○☆☆
专业化水平●●●●●
社会保障○○☆○☆
生活水平●●●●●
居住环境○○○☆☆
文化休闲▼○○☆○
资源环境☆☆▼☆○
一致性0.9670.92309470.8981
原始覆盖度0.3250.3930.3460.1240.079
唯一覆盖度0.0350.0870.0530.0690.031
解的一致性0.925
解的覆盖度0.595
), ArticleFig(id=1323941333789974716, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1323941325317480579, language=CN, label=表6, caption=

高效率条件组态分析结果

, figureFileSmall=null, figureFileBig=null, tableContent=
条件组合H1aH1bH1cH2H3
政府补贴○▼○☆☆
专业化水平●●●●●
社会保障○○☆○☆
生活水平●●●●●
居住环境○○○☆☆
文化休闲▼○○☆○
资源环境☆☆▼☆○
一致性0.9670.92309470.8981
原始覆盖度0.3250.3930.3460.1240.079
唯一覆盖度0.0350.0870.0530.0690.031
解的一致性0.925
解的覆盖度0.595
), ArticleFig(id=1323941333953552573, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1323941325317480579, language=EN, label=Table 7, caption=

Configuration analysis results of low efficiency conditions

, figureFileSmall=null, figureFileBig=null, tableContent=
条件组合NH1aNH1bNH1cNH2aNH2b
政府补贴☆◇○○○
专业化水平☆◇▼◇◇
社会保障☆▼☆○●
生活水平◇◇◇○●
居住环境☆◇◇◇●
文化休闲◇◇◇○◇
资源环境▼○○◇●
一致性0.8500.9720.9890.8820.961
原始覆盖度0.1800.1670.2100.0760.074
唯一覆盖度0.0710.0570.1730.0450.032
解的一致性0.924
解的覆盖度0.508
), ArticleFig(id=1323941334062604478, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1323941325317480579, language=CN, label=表7, caption=

低效率条件组态分析结果

, figureFileSmall=null, figureFileBig=null, tableContent=
条件组合NH1aNH1bNH1cNH2aNH2b
政府补贴☆◇○○○
专业化水平☆◇▼◇◇
社会保障☆▼☆○●
生活水平◇◇◇○●
居住环境☆◇◇◇●
文化休闲◇◇◇○◇
资源环境▼○○◇●
一致性0.8500.9720.9890.8820.961
原始覆盖度0.1800.1670.2100.0760.074
唯一覆盖度0.0710.0570.1730.0450.032
解的一致性0.924
解的覆盖度0.508
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基于三阶段DEA-FsQCA的社区居家养老资源配置效率及组态路径研究
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韩霜 1 , 黄修明 2 , 田晓伟 1 , 张新宇 1 , 孔杨 1
现代预防医学 | 卫生政策与管理 2025,52(23): 4339-4345
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现代预防医学 |卫生政策与管理 2025 , 52 (23) : 4339 -4345
基于三阶段DEA-FsQCA的社区居家养老资源配置效率及组态路径研究
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韩霜1, 黄修明2, 田晓伟1, 张新宇1, 孔杨1
作者信息
  • 1.滨州医学院卫生管理学院，山东　烟台　264003
  • 2.曲阜师范大学体育科学学院
通讯作者:
孔杨，E-mail：
作者简介:

韩霜（2001—），女，硕士在读，研究方向：养老服务与管理、卫生事业管理

Efficiency and improvement paths of community home care services based on three-stage DEA and FsQCA
Shuang HAN1, Xiu-ming HUANG2, Xiao-wei TIAN1, Xin-yu ZHANG1, Yang KONG1
Affiliations
  • School of Health Management, Binzhou Medical University, Yantai, Shandong 264003, China
出版时间: 2025-12-10 doi: 10.20043/j.cnki.MPM.202504337
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摘要
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目的

分析我国社区居家养老资源配置效率的具体路径，为实现社区居家养老服务资源配置均衡发展提供有力支撑。

方法

基于2020—2023年《中国民政统计年鉴》《中国统计年鉴》《中国卫生健康统计年鉴》《中国社会统计年鉴》中相关数据，采用数据包络分析法对我国社区居家养老资源配置效率进行测算，在此基础上借助模糊集定性比较分析法探究社区居家养老资源高效配置组态路径。

结果

我国社区居家养老服务综合效率、纯技术效率、规模效率的均值分别为0.533、0.640、0.810，各地区和省份之间存在显著差异；提升社区居家养老资源配置效率的路径有三条，总体一致性为0.925，模型解释力较强。

结论

社区居家养老资源配置效率整体水平有待提升，建议优化管理流程和技术创新，增强优势区域辐射带动力；精准拓宽养老产业规模，有效提升资源配置效率；秉持因地制宜发展原则，探寻差异化养老新路径。

社区居家养老服务  /  配置效率  /  数据包络分析  /  模糊集定性比较分析
Objective

To analyze the specific paths of the resource allocation efficiency of community home care in China and provide strong support for the balanced development of the resource allocation of such services.

Methods

Based on the relevant data from China Civil Affairs Statistical Yearbook, China Statistical Yearbook, China Health Statistics Yearbook, and China Social Statistics Yearbook (2020—2023), this study used the Data Envelopment Analysis (DEA) method to measure the allocation efficiency of community-based home care resources in China. On this basis, the Fuzzy-set qualitative comparative analysis (fsQCA) was employed to explore the configurational paths for the efficient allocation of community-based home care resources.

Results

The average values of the comprehensive efficiency, pure technical efficiency, and scale efficiency of community home care services in China were 0.533, 0.640, and 0.810, respectively. There were significant differences among different regions and provinces. There were three paths to improve the efficiency of community home care services, with an overall consistency of 0.925, indicating a strong explanatory power of the model.

Conclusion

The overall efficiency level of community home care services needs to be enhanced. It is recommended to optimize management processes and technological innovation, strengthen the radiation and driving force of advantageous regions, precisely expand the scale of the elderly care industry, effectively improve the resource allocation efficiency, adhere to the principle of development based on local conditions, and explore new differentiated elderly care paths.

Community home care services  /  Allocation efficiency  /  Data envelopment analysis  /  Fuzzy-set qualitative comparative analysis
韩霜, 黄修明, 田晓伟, 张新宇, 孔杨. 基于三阶段DEA-FsQCA的社区居家养老资源配置效率及组态路径研究. 现代预防医学, 2025 , 52 (23) : 4339 -4345 . DOI: 10.20043/j.cnki.MPM.202504337
Shuang HAN, Xiu-ming HUANG, Xiao-wei TIAN, Xin-yu ZHANG, Yang KONG. Efficiency and improvement paths of community home care services based on three-stage DEA and FsQCA[J]. Modern Preventive Medicine, 2025 , 52 (23) : 4339 -4345 . DOI: 10.20043/j.cnki.MPM.202504337
正文
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截至2023年末，中国大陆65岁及以上的老年人口占总人口比重的达15.4%，成为了世界上人口老龄化发展速度最快的国家之一[1]。鉴于此，中国政府在“十三五”和“十四五”国家老龄事业发展和养老体系建设规划中明确提出要大力发展社区居家养老服务机构和强化社区居家养老服务能力的要求[2]。社区居家养老服务整合了传统养老的优势和不足，是传统养老强有力的支撑和补充，已逐步发展成为新型的养老模式[3]。但在实践过程中，社区居家养老资源供给冗余与短缺并存、利用率低、配置差异程度大等问题依然存在[4]，导致当前社区居家养老服务供需脱节的局面仍有待改变[5]。为推动养老事业高质量发展，党和国家发布一系列支持政策，要求推动养老服务扩容提质，提高资源配置效率，满足老年人多层次多样化养老需求。因此，有效提升我国社区居家养老服务资源配置的效率均具有重要性和紧迫性。
已有研究主要集中于服务模式[6]、供需资源配置现状[7]及问题和对策[8]三个方面，多侧重于考察单个或少数几个因素对养老资源配置的影响，缺少因素间互动机制与协同作用分析[9]。基于此，本文采用三阶段数据包络分析和模糊集定性比较分析方法，从组态视角探寻我国社区居家养老服务资源配置效率提升路径，以期为各省份识别资源配置短板、优化管理策略提供科学依据，助力地方政府实现管理效能提升与资源优化配置的协同发展。
1　材料与方法
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1.1　材料来源
本文数据收集于2020—2023年《中国民政统计年鉴》《中国统计年鉴》《中国卫生健康统计年鉴》《中国社会统计年鉴》，覆盖2019—2022年31个省份社区居家养老资源配置效率体系的相关指标数据，并依照国家统计局划分标准，将31个省份（不含港澳台）分为东部、东北、中部以及西部地区。
1.2　研究方法
1.2.1　数据包络分析（data envelopment analysis,DEA）
通过线性规划技术衡量多输入、多产出系统中同类型决策单元的相对效率水平。本文采用三阶段DEA模型剖析我国社区居家养老服务的运行效率[10]。
1.2.2　模糊集定性比较分析（fuzzy-set qualitative comparative analysis, FsQCA）
是一种结合定性与定量方法的因果分析工具，旨在揭示多条件组合如何共同导致特定结果[11]。本文采用FsQCA方法探寻社区居家养老资源配置效率组态提升路径。
2　结果
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2.1　社区居家养老资源配置效率研究
2.1.1　指标体系构建
基于文献和数据可获得性[12]，从人力、物力、财力方面选取投入和产出指标；养老资源的分配受到人口老龄化、自然环境和社会养老规模的影响[13]，分别选取老年抚养比、人均公园和绿地面积、老年人均养老机构和设施建筑面积作为环境变量。见表1。
2.1.2　第一阶段：传统DEA模型分析
社区居家养老资源配置效率处于规模报酬不变、递增和递减的省份分别有9、17和5个，说明社区居家养老资源配置整体运行良好，但仍存在一些问题。具体而言，广东、海南以及宁夏三个省份纯技术效率都达到1，规模效率不达标是其未达到技术有效的主要原因。以上结果并未剔除外部环境与随机干扰的影响，不能反映各省份社区居家养老服务运行效率的真实情况，故需进行第二阶段的调整[14]。见表2。
2.1.3　第二阶段：随机前沿分析（stochastic frontier analysis, SFA）回归分析
各松弛量的γ值均趋近于1，说明主要是由管理无效率造成的，随机干扰的影响较小。各松弛变量的单边广义似然比（likelihood ratio，LR）均通过5%的显著性检验，模型选取合理，结合分析结果对社区居家养老资源配置效率进一步调整。见表3。
2.1.4　 第三阶段：调整数据后的DEA分析
与第一阶段相比，纯技术效率和规模效率均有所下降，说明综合效率受技术效率和规模效率两者的共同影响，且第一阶段不剔除环境变量和随机干扰，高估了省域社区居家养老服务运行效率。分地区看，东北和西部地区的综合效率与纯技术效率都低于全国均值，西部地区的规模效率也低于全国均值，这反映出东北和西部地区，尤其是西部应提升社区居家养老服务的技术的创新与管理流程的优化，合理配置资源的投入规模。从省域角度看，第三阶段规模报酬不变、递增和递减的省份分别有26、2和3个。与第一阶段相比，处于规模报酬递增的省份显著增多，整体处于规模报酬递增阶段，部分地区应该适当加大投入规模。见表4。
2.2　社区居家养老资源配置效率的定性比较分析
2.2.1　变量标定与校准
采用直接校准法对条件变量和结果变量进行校准，利用熵权法对具体指标进行赋权处理，以75%、50%和25%分位数值作为完全隶属度、交叉点和完全不隶属度的锚点，并在FsQCA软件中将各变量校准为模糊隶属分数。见表5。
2.2.2　单个条件的必要性分析
利用FsQCA软件对七个前因条件及其非集能否构成高/低效率的必要性条件进行检验，见图1。七个前因条件的一致性均小于0.9，表明不存在导致高/低效率的单一必要条件。
2.2.3　条件组态的充分性分析
将频数阈值设置为1，一致性阈值设置为 0.8，PRI一致性阈值设置为0.7，对真值表进行标准化分析，得到复杂解、简单解和中间解，以中间解为主体并辅以简单解，共同确定最终的条件组态路径，见表6。由表6中高效率的5种条件组态结果可知，总体一致性（0.925）大于0.9，说明条件组态充分性分析的有效性。总体来说，5种组态可以被视为提高效率的充分条件组合，最终归纳为以下三条路径。
路径1：均衡型（H1a、H1b、H1c）。该路径表明：如果区域具备较高的社区居家养老服务专业化水平以及生活水平，同时政府给予充足的老龄补贴及保障，居民享有优良的居住环境以及丰富的文化休闲生活，内外部各要素间的均衡配置能够实现社区居家养老资源配置效率的有效提升。
路径2：内外协调型（H2）。该路径表明：即使区域政府给予的老龄补贴并不高，但若拥有较为充足的社区居家养老服务专业化人力资源及优越的养老环境，并辅以社会保障为支撑，通过内生要素的系统性整合与外部政策保障的良性互动，可形成养老服务供给的“正反馈循环”。
路径3：生活水平-专业服务双驱动型（H3）。该路径表明：政府老龄补贴投入、社会保障、老年人的文化休闲活动以及养老环境均没有明显的优势，效率提升主要依靠地区居民较高的生活水平及专业化养老服务，通过提高老年人可支配收入、引进社区居家养老服务高层次人才资源，能够实现社区居家养老服务的高效率配置。
另外，表7呈现了社区居家养老服务低效率的条件组态分析结果。对于低效率结果变量，QCA分析出五种条件组态，总体一致性为0.924，大于阈值 0.9。现将五种条件组态归纳为以下 二条发展路径。
路径1：内外制约型（NH1a、NH1b、NH1c）。该路径表明：生活水平偏低、居住环境欠佳以及文化休闲生活匮乏，造成了区域社区居家养老资源配置效率低下的核心因素。内外部诸多要素的缺失作为前因条件共同制约社区居家养老服务的配置效率。
路径2：养老环境-专业服务双重制约型（NH2a、NH2b）。该路径表明：即使政府保障充足及居民生活水平较高，但若社区居家养老服务专业人才短缺且没有营造出适宜老年人居家养老的环境，社区居家养老资源配置效率也会受到限制。
3　讨论
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3.1　优化管理流程和技术创新，增强优势区域辐射带动力
针对大部分未达到DEA有效的地区，首先构建“全周期、全链条”的社区居家养老服务管理体系。针对服务需求评估、资源配置、服务交付等环节，建立标准化操作流程，明确各部门权责边界。其次，提升社区居家养老服务的智慧化水平。积极引入智能养老设备，利用大数据技术整合分析老年人的健康数据、服务需求数据，为个性化服务提供精准依据，以期有效满足老年人多样化健康养老需求。最后，建立区域间“技术溢出-经验共享”帮扶合作机制，由高效率地区充分发挥空间溢出效应，将先进的管理模式和创新技术向周边地区辐射，带动其他区域共同提升社区居家养老服务水平。
3.2　精准拓宽养老产业规模，有效提升资源配置效率
为有效提升社区居家养老资源配置效率，避免盲目扩张导致资源错配采用“结构性扩张策略”。在硬件投入上，优先填补社区级服务设施空白区域，结合人口密度与老龄化率进行网格化选址分析，避免“建而不用”。人力投入上，依托职业院校定向培养本地养老护理员，同时组建跨市医疗专家巡回支援团队。资金投入上，设立省级养老产业引导基金，吸引社会资本参与智慧养老、适老化改造等领域，通过精准规模扩张与资源高效流转，将规模报酬递增转化为实际服务质量提升。
3.3　 秉持因地制宜发展原则，探寻差异化养老新路径
一方面，需注重统筹协调与因地制宜相结合。低效率资源配置地区需重点突破生活水平、居住环境及文化休闲生活方面的瓶颈，强化政府支持与社会保障的辅助作用，若在短期内难以显著增加政府老龄补贴投入或优化养老环境，可将工作重心置于提升社区居家养老服务专业化水平和改善老年人生活水平上。通过加强专业人才培养、引入先进服务理念和技术，从特定维度推动社区居家养老服务的发展。另一方面，需从“系统性、全面性”的视角统筹规划，将政府补贴、专业化水平、社会保障等条件进行优化组合，充分发挥各前因条件之间的替代效应和互补效应，补齐社区居家养老资源配置低的短板，推动社区居家养老资源配置效率的有效提升。
基金
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  • 国家自然科学基金面上项目(72274023)
  • 2022年度教育部人文社会科学研究一般项目(22YJA890037)
  • 山东省自然科学基金项目(ZR2022MG037)
  • 山东省社会科学规划研究项目(22CGLJ01)
文献
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2025年第52卷第23期
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doi: 10.20043/j.cnki.MPM.202504337
  • 接收时间：2025-04-23
  • 首发时间：2026-11-02
  • 出版时间：2025-12-10
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  • 收稿日期：2025-04-23
基金
国家自然科学基金面上项目(72274023)
2022年度教育部人文社会科学研究一般项目(22YJA890037)
山东省自然科学基金项目(ZR2022MG037)
山东省社会科学规划研究项目(22CGLJ01)
作者信息
    1.滨州医学院卫生管理学院，山东　烟台　264003
    2.曲阜师范大学体育科学学院

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孔杨，E-mail：
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2种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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