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Article(id=1240950907416932401, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240950898113966774, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202311040, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1699027200000, receivedDateStr=2023-11-04, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773795352080, onlineDateStr=2026-03-18, pubDate=1712678400000, pubDateStr=2024-04-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773795352080, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773795352080, creator=13701087609, updateTime=1773795352080, updator=13701087609, issue=Issue{id=1240950898113966774, tenantId=1146029695717560320, journalId=1227665162245664772, year='2024', volume='51', issue='7', pageStart='1153', pageEnd='1344', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773795349862, creator=13701087609, updateTime=1773795519367, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1240951609136567133, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240950898113966774, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1240951609136567134, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240950898113966774, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1249, endPage=1254, ext={EN=ArticleExt(id=1240950907823779917, articleId=1240950907416932401, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Resource allocation efficiency and spatial autocorrelation analysis of China’s elderly care institutions in 2021, columnId=1228016572892119056, journalTitle=Modern Preventive Medicine, columnName=Primary Health Services, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze the resource allocation efficiency and spatial aggregation of elderly care institutions in China, so as to provide reference for optimizing the elderly care service system.

Methods

Three-stage DEA model was used to analyze the resource allocation efficiency of elderly care institutions in 31 provinces (autonomous regions and cities) in 2021. Global Moran’s I index and Getis-Ord Gi* index was used to analyze the spatial autocorrelation of resource allocation efficiency of elderly care institutions in China.

Results

In 2021, the overall scale efficiency of resource allocation of elderly care institutions in China was not high, and there was spatial aggregation effect. Scale efficiency was the main factor restricting the improvement of the allocation efficiency of elderly care institutions in China. The resource allocation efficiency of elderly care institutions was greatly affected by the external environment.

Conclusion

According to the demand of local elderly care service, the government should adjust its scale efficiency reasonably, improve the management level, allocate the resources of elderly care institutions reasonably and promote its efficiency.

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目的

分析我国养老机构资源配置效率和空间聚集状况，为优化养老服务体系提供参考。

方法

使用三阶段DEA模型分析2021年我国31个省（区、市）养老机构资源配置效率，使用全局Moran I指数和Getis-Ord Gi*指数热点分析我国养老机构资源配置效率的空间自相关性。

结果

2021年我国养老机构资源配置整体规模效率不高，且存在空间聚集效应；规模效率是制约我国养老机构配置效率提升的主要因素；养老机构资源配置效率受外部环境影响较大。

结论

政府应根据当地养老服务需求，合理调整其规模效率，提升管理水平，合理配置养老机构资源，促进其效率的提升。

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黄冬梅，E-mail:
, copyrightStatement=本刊刊出的所有文章不代表中华预防医学会和本刊编委会的观点，除非特别声明。, copyrightOwner=中华预防医学会和四川大学华西公共卫生学院, extLink=null, articleAbsUrl=null, sourceXml=KGPZA5IKGZ2BQVPjl+WPSQ==, magXml=YqWRR65L+7u5gz98EjziyQ==, pdfUrl=null, pdf=h5rlrq7NZdBqlqiT74K8zQ==, pdfFileSize=681690, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=hzbhu47K3WU6ZapUaK4Nng==, mapNumber=null, authorCompany=null, fund=null, authors=

付凯云（1996—），女，硕士在读，研究方向：卫生管理与政策研究

, authorsList=付凯云, 尹文强, 宋雅蕾, 杜悦, 亓霏, 杨春晓, 李秋莎, 黄冬梅)}, authors=[Author(id=1240972159733002416, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950907416932401, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1240972159951106232, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950907416932401, authorId=1240972159733002416, language=EN, stringName=Kai-yun FU, firstName=Kai-yun, middleName=null, lastName=FU, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 3, 4, address=School of Public Health, Shandong Second Medical University, Weifang, Shandong 261053, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1240972160034992318, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950907416932401, authorId=1240972159733002416, language=CN, stringName=付凯云, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 3, 4, address=1.山东第二医科大学管理学院，山东 潍坊 261053
3.“健康山东”重大社会风险预测与治理协同创新中心，山东 潍坊 261053
4.健康相关重大社会风险预警协同创新中心，上海 200032, bio={"content":"

付凯云（1996—），女，硕士在读，研究方向：卫生管理与政策研究

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付凯云（1996—），女，硕士在读，研究方向：卫生管理与政策研究

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3.“健康山东”重大社会风险预测与治理协同创新中心，山东 潍坊 261053
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3.“健康山东”重大社会风险预测与治理协同创新中心，山东 潍坊 261053
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Research on the operational efficiency of urban and rural elderly care institutions in China against the background of population aging——Analysis based on the three-stage SBM-DEA model[J]. 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Efficiency evaluation of elderly care institutions in Shandong Province based on three-stage DEA[J]. 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Resource allocation efficiency of elderly care institutions in 31 provinces (autonomous regions and municipalities) in China in 2021

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省份第一阶段第三阶段
综合效率纯技术效率规模效率规模报酬综合效率纯技术效率规模效率规模报酬
北京0.9290.9330.996irs0.7790.8830.882irs
天津0.7310.7340.996irs0.4830.6320.763irs
河北0.8620.8621.000-0.8670.8750.991irs
山西0.8160.8240.991irs0.7410.8890.833irs
内蒙古1.0001.0001.000-0.8520.9530.895irs
辽宁1.0001.0001.000-1.0001.0001.000-
吉林1.0001.0001.000-0.8970.9650.929irs
黑龙江0.9820.9900.992irs0.8250.8680.951irs
上海1.0001.0001.000-0.9430.9580.985irs
江苏0.7931.0000.793drs0.8311.0000.831drs
浙江0.9930.9960.997drs0.9830.9910.991irs
安徽0.7600.7610.998irs0.8100.8340.972irs
福建0.6720.6740.997irs0.7020.9620.730irs
江西1.0001.0001.000-1.0001.0001.000-
山东0.7890.8910.885drs0.8280.9010.918drs
河南0.8700.9550.911drs0.9320.9800.951drs
湖北0.8040.8050.999irs0.8260.8660.954irs
湖南0.8370.8370.999drs0.8540.8590.994irs
广东0.7450.7461.000-0.7360.7680.959irs
广西0.5950.5980.996irs0.6130.7370.831irs
海南0.7550.9190.822irs0.2771.0000.277irs
重庆0.9730.9760.997irs0.8800.9580.918irs
四川1.0001.0001.000-1.0001.0001.000-
贵州0.7400.7710.960irs0.6880.8860.776irs
云南0.6370.6400.994irs0.6760.8480.797irs
西藏0.9741.0000.974irs0.1650.5040.327irs
陕西1.0001.0001.000-0.9771.0000.977irs
甘肃0.7850.7940.988irs0.5160.8130.634irs
青海0.8841.0000.884irs0.1480.6000.247irs
宁夏0.5810.5910.984irs0.3240.8760.370irs
新疆0.9280.9350.993irs0.8081.0000.808irs
平均值0.8530.8780.9720.7410.8840.822
), ArticleFig(id=1240972166741684709, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950907416932401, language=CN, label=表1, caption=

2021年我国31个省（区、市）养老机构资源配置效率

, figureFileSmall=null, figureFileBig=null, tableContent=
省份第一阶段第三阶段
综合效率纯技术效率规模效率规模报酬综合效率纯技术效率规模效率规模报酬
北京0.9290.9330.996irs0.7790.8830.882irs
天津0.7310.7340.996irs0.4830.6320.763irs
河北0.8620.8621.000-0.8670.8750.991irs
山西0.8160.8240.991irs0.7410.8890.833irs
内蒙古1.0001.0001.000-0.8520.9530.895irs
辽宁1.0001.0001.000-1.0001.0001.000-
吉林1.0001.0001.000-0.8970.9650.929irs
黑龙江0.9820.9900.992irs0.8250.8680.951irs
上海1.0001.0001.000-0.9430.9580.985irs
江苏0.7931.0000.793drs0.8311.0000.831drs
浙江0.9930.9960.997drs0.9830.9910.991irs
安徽0.7600.7610.998irs0.8100.8340.972irs
福建0.6720.6740.997irs0.7020.9620.730irs
江西1.0001.0001.000-1.0001.0001.000-
山东0.7890.8910.885drs0.8280.9010.918drs
河南0.8700.9550.911drs0.9320.9800.951drs
湖北0.8040.8050.999irs0.8260.8660.954irs
湖南0.8370.8370.999drs0.8540.8590.994irs
广东0.7450.7461.000-0.7360.7680.959irs
广西0.5950.5980.996irs0.6130.7370.831irs
海南0.7550.9190.822irs0.2771.0000.277irs
重庆0.9730.9760.997irs0.8800.9580.918irs
四川1.0001.0001.000-1.0001.0001.000-
贵州0.7400.7710.960irs0.6880.8860.776irs
云南0.6370.6400.994irs0.6760.8480.797irs
西藏0.9741.0000.974irs0.1650.5040.327irs
陕西1.0001.0001.000-0.9771.0000.977irs
甘肃0.7850.7940.988irs0.5160.8130.634irs
青海0.8841.0000.884irs0.1480.6000.247irs
宁夏0.5810.5910.984irs0.3240.8760.370irs
新疆0.9280.9350.993irs0.8081.0000.808irs
平均值0.8530.8780.9720.7410.8840.822
), ArticleFig(id=1240972166850736623, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950907416932401, language=EN, label=Table 2, caption=

Results of DEA analysis in the second stage

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变量机构床位数年末职工人数机构建筑面积
常数项97 581.95***14 749.17***3 810 612.70***
城镇人口比重-1 173.30***-118.25***-33 691.63***
一般公共预算支出占GDP比重-956.13*-166.12***-48 211.07***
老年人口抚养比-614.53*-339.81***-68 394.22***
人均GDP特化系数7 892.06***2 492.77***585 673.10***
γ值1.00***1.00***1.00***
对数似然函数-347.73-289.03-468.32
似然比单边检验19.488.6915.74
), ArticleFig(id=1240972166959788538, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950907416932401, language=CN, label=表2, caption=

第二阶段DEA分析结果

, figureFileSmall=null, figureFileBig=null, tableContent=
变量机构床位数年末职工人数机构建筑面积
常数项97 581.95***14 749.17***3 810 612.70***
城镇人口比重-1 173.30***-118.25***-33 691.63***
一般公共预算支出占GDP比重-956.13*-166.12***-48 211.07***
老年人口抚养比-614.53*-339.81***-68 394.22***
人均GDP特化系数7 892.06***2 492.77***585 673.10***
γ值1.00***1.00***1.00***
对数似然函数-347.73-289.03-468.32
似然比单边检验19.488.6915.74
), ArticleFig(id=1240972167047868933, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950907416932401, language=EN, label=Table 3, caption=

Getis-Ord Gi* hot spot analysis of resource allocation efficiency of elderly care institutions in 31 provinces (autonomous regions and municipalities) in China in 2021

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冷点地区热点地区
90%CI95%CI99%CI90%CI95%CI99%CI
广西西藏新疆陕西、内蒙古、黑龙江山西、山东、辽宁、吉林河北、北京、天津
), ArticleFig(id=1240972167156920849, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950907416932401, language=CN, label=表3, caption=

2021年我国31个省（区、市）养老机构资源配置效率的Getis-Ord Gi*热点分析

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冷点地区热点地区
90%CI95%CI99%CI90%CI95%CI99%CI
广西西藏新疆陕西、内蒙古、黑龙江山西、山东、辽宁、吉林河北、北京、天津
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2021年我国养老机构资源配置效率及空间自相关分析
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付凯云 1, 3, 4 , 尹文强 1, 3, 4 , 宋雅蕾 1, 3, 4 , 杜悦 1, 3, 4 , 亓霏 1, 3, 4 , 杨春晓 2, 3, 4 , 李秋莎 2, 3, 4 , 黄冬梅 1, 3, 4
现代预防医学 | 基层卫生服务 2024,51(7): 1249-1254
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现代预防医学 | 基层卫生服务 2024, 51(7): 1249-1254
2021年我国养老机构资源配置效率及空间自相关分析
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付凯云1, 3, 4, 尹文强1, 3, 4, 宋雅蕾1, 3, 4, 杜悦1, 3, 4, 亓霏1, 3, 4, 杨春晓2, 3, 4, 李秋莎2, 3, 4, 黄冬梅1, 3, 4
作者信息
  • 1.山东第二医科大学管理学院，山东 潍坊 261053
  • 2.山东第二医科大学公共卫生学院
  • 3.“健康山东”重大社会风险预测与治理协同创新中心，山东 潍坊 261053
  • 4.健康相关重大社会风险预警协同创新中心，上海 200032

    • 付凯云（1996—），女，硕士在读，研究方向：卫生管理与政策研究

通讯作者:

黄冬梅，E-mail:
Resource allocation efficiency and spatial autocorrelation analysis of China’s elderly care institutions in 2021
Kai-yun FU1, 3, 4, Wen-qiang YIN1, 3, 4, Ya-lei SONG1, 3, 4, Yue DU1, 3, 4, Fei QI1, 3, 4, Chun-xiao YANG2, 3, 4, Qiu-sha LI2, 3, 4, Dong-mei HUANG1, 3, 4
Affiliations
  • School of Public Health, Shandong Second Medical University, Weifang, Shandong 261053, China
出版时间: 2024-04-10 doi: 10.20043/j.cnki.MPM.202311040
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摘要
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目的

分析我国养老机构资源配置效率和空间聚集状况，为优化养老服务体系提供参考。

方法

使用三阶段DEA模型分析2021年我国31个省（区、市）养老机构资源配置效率，使用全局Moran I指数和Getis-Ord Gi*指数热点分析我国养老机构资源配置效率的空间自相关性。

结果

2021年我国养老机构资源配置整体规模效率不高，且存在空间聚集效应；规模效率是制约我国养老机构配置效率提升的主要因素；养老机构资源配置效率受外部环境影响较大。

结论

政府应根据当地养老服务需求，合理调整其规模效率，提升管理水平，合理配置养老机构资源，促进其效率的提升。

养老机构  /  配置效率  /  三阶段DEA  /  空间自相关性
Objective

To analyze the resource allocation efficiency and spatial aggregation of elderly care institutions in China, so as to provide reference for optimizing the elderly care service system.

Methods

Three-stage DEA model was used to analyze the resource allocation efficiency of elderly care institutions in 31 provinces (autonomous regions and cities) in 2021. Global Moran’s I index and Getis-Ord Gi* index was used to analyze the spatial autocorrelation of resource allocation efficiency of elderly care institutions in China.

Results

In 2021, the overall scale efficiency of resource allocation of elderly care institutions in China was not high, and there was spatial aggregation effect. Scale efficiency was the main factor restricting the improvement of the allocation efficiency of elderly care institutions in China. The resource allocation efficiency of elderly care institutions was greatly affected by the external environment.

Conclusion

According to the demand of local elderly care service, the government should adjust its scale efficiency reasonably, improve the management level, allocate the resources of elderly care institutions reasonably and promote its efficiency.

Elderly care institutions  /  Allocation efficiency  /  Three-stage DEA  /  Spatial autocorrelation
付凯云, 尹文强, 宋雅蕾, 杜悦, 亓霏, 杨春晓, 李秋莎, 黄冬梅. 2021年我国养老机构资源配置效率及空间自相关分析. 现代预防医学, 2024 , 51 (7) : 1249 -1254 . DOI: 10.20043/j.cnki.MPM.202311040
Kai-yun FU, Wen-qiang YIN, Ya-lei SONG, Yue DU, Fei QI, Chun-xiao YANG, Qiu-sha LI, Dong-mei HUANG. Resource allocation efficiency and spatial autocorrelation analysis of China’s elderly care institutions in 2021[J]. Modern Preventive Medicine, 2024 , 51 (7) : 1249 -1254 . DOI: 10.20043/j.cnki.MPM.202311040
正文
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第七次全国人口普查结果显示65岁及以上人口占比为13.5%，相较于2010年第六次全国人口普查相比，65岁及以上的比重上升4.63%，人口老龄化程度逐渐加深[1]。《中华人民共和国国民经济和社会发展第十四五个五年规划和2035年远景目标纲要》中将积极应对人口老龄化上升为国家战略，明确指出要推动养老事业和养老产业协同发展，健全基本养老服务体系，大力发展普惠型养老服务，满足高龄失能失智老年人护理服务需求，加强老年健康服务[2]。
随着我国人均预期寿命的延长，老年人中慢性病患者占比为75%，失能老人达4 000多万人，老年人照护问题亟需解决[3]。养老机构作为高龄、失能以及失智老人的兜底保障[4]，现行医养康养结合服务的重要主体以及促进医疗卫生与养老服务深度结合的主要载体[5]，其资源的科学配置和高效利用是完善养老服务体系的重要基础。曾雁冰[6]对厦门市的13家养老机构的服务效率进行分析，发现整体技术效率较高，但规模效率有待提升。陈雪娇[7]对河南省医养结合养老机构服务效率进行评价，研究发现技术效率总体较低，机构的技术效率与运营模式、所在区域、医务人员和入住率有关。原新研究发现天津市医养结合型养老机构纯技术效率的成分大于规模效率，整体上处于规模报酬递增阶段[8]。当前学者较少从全国层面对养老机构资源配置效率进行分析，因此，本研究利用三阶段DEA模型和空间自相关分析对我国2021年养老机构资源配置情况进行效率测度和空间聚集分析，以期为提高养老机构资源配置效率，完善养老服务体系提供参考。
1　数据与方法
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1.1　数据来源与指标选取
数据包络模型投入、产出指标的选择应遵循可获取性、相关性、以及代表性等原则[9]。通过对已有研究的总结归纳和数据可获得性考虑[10-11]，本研究选取养老机构床位数（张）、年末职工人数、机构建筑面积（m2）作为投入指标；年末在院总人天数（人天）、年末在院人数作为产出指标；环境变量主要基于影响养老机构卫生资源配置的经济、政治、人口、社会等因素的考量[12]，最终选取经济因素的人均GDP特化系数，从全国层面反映地区经济发展水平的指标；政治因素的一般公共预算支出占GDP比重，反映政府对公共服务的投入程度；人口因素的城镇人口比重，反映某地区的城镇化水平，人口的城乡分布情况；社会因素的老年人口抚养比，反映老龄社会劳动人口负担程度的指标。数据来源于《中国统计年鉴2022》和《中国民政统计年鉴2022》。
1.2　研究方法
1.2.1　三阶段DEA模型
本研究运用三阶段DEA模型对2021年我国养老机构的卫生资源配置效率进行测算，该模型在传统DEA基础上剔除环境因素和随机干扰的影响，更能真实反映决策单元的效率。
第一阶段：根据规模报酬是否可变，传统DEA分析分为CCR模型和BCC模型，CCR模型从产出导向角度出发，假设规模报酬不变，得出的效率为综合效率。BCC模型从投入导向角度出发，假设规模报酬可变，得出的效率包括技术效率和规模效率。因养老机构规模具有可变性，采用投入导向的BCC模型，通过DEAP 2.1软件进行第一阶段分析，评价养老机构资源配置效率的综合效率、纯技术效率和规模效率[13]。
第二阶段：采用SFA回归分离环境因素、管理因素和随机干扰对效率的影响，将环境因素和随机干扰剔除，得到管理因素带来的效率影响。使用Frontier 4.1软件，第一阶段计算的投入松弛变量对环境变量进行成本函数回归。
第三阶段：将剔除环境因素和随机干扰后的投入调整值和原始产出值重新进行传统DEA模型运算，得到的效率值更好地说明效率的差异是由管理因素造成，更真实反映效率情况。
1.2.2　空间自相关分析
空间自相关是指同一变量在不同空间位置上的相关性，用于检验空间单位与相邻的空间单位之间的属性值是否相似[14]。为探究养老机构资源配置综合效率的空间分布情况，本研究运用GeoDa软件进行空间自相关分析。在空间自相关分析中，全局Moran I指数检验我国31个省份的养老机构资源配置综合效率的全局空间自相关性，局部Getis Ord Gi*指数热点分析，检验各个省份养老机构资源配置综合效率局部空间自相关性[15]。
全局Moran I指数取值范围为[-1,1]，当Moran I>0时，表示存在空间正相关性；Moran I<0，表示存在空间负相关性；Moran I=0，表示变量在空间上相互独立[16]。公式为：
局部Getis Ord Gi*指数热点分析是在全局Moran I空间自相关基础上，分析研究区域中出现高值（低值），高值（低值）是指研究区域出现高值（低值），邻近地区也出现高值（低值），高值在局部聚集现象称为“热点”，反之称之为“冷点”[17]。
2　结果
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2.1　三阶段DEA分析
2.1.1　第一阶段DEA结果分析
对2021年我国31个省份的养老机构资源配置效率进行第一阶段DEA分析，结果表明各省（区、市）养老机构资源配置综合效率平均值0.853，纯技术效率平均值为0.878，规模效率平均值为0.972。其中内蒙古、辽宁、吉林、上海、江西、四川以及陕西在内的7个省（区、市）DEA综合效率值为1；宁夏综合效率值最低，位于全国末位。大部分地区的规模报酬呈现递增趋势，仅有江苏、浙江、山东、河南和湖南规模报酬呈递减趋势。见表1。
2.1.2　第二阶段回归结果
以第一阶段计算的各投入松弛变量为因变量，城镇人口比重、一般公共预算支出占GDP比重、老年人口抚养比和人均GDP特化系数为自变量，进行SFA回归分析。表2结果显示，三个回归模型的似然比单边检验值均大于广义单边检验中5%水平的临界值7.045，说明环境变量选择合理，SFA回归模型合理。投入变量的γ值均趋近于1，说明管理无效率对养老机构资源配置的影响较大。
环境变量（表2中人均GDP特化系数）系数为正，表明环境变量对投入松弛变量产生正向作用。人均GDP特化系数增加会导致养老机构床位数、年末职工人数以及机构建筑面积的浪费。环境变量（表2中城镇人口比重、一般公共预算支出占GDP比重、老年人口抚养比）系数为负，表明环境变量对投入松弛变量产生负向作用。城镇人口比重、一般公共预算支出占GDP比重以及老年人口抚养比增加均会减少养老机构床位数、年末职工人数以及机构建筑面积的浪费。见表2。
2.1.3　第三阶段调整后结果分析
将第二阶段调整后的投入值和原始产出值重新进行第三阶段DEA分析，测算我国养老机构资源配置效率，结果见表1。从整体来看，我国养老机构资源的综合效率均值和规模效率均值下降，表明未考虑环境变量和随机干预时，养老机构资源的配置效率被高估，且我国养老机构资源配置效率的降低主要由于规模效率的下降所致。从综合效率来看，仅有辽宁、江西和四川综合效率不变且综合效率值为1。北京、天津、山西等18个省（区、市）的综合效率值下降，表明这些省市综合效率低主要受不良外部环境的影响。
从效率分解来看，纯技术效率值为1的省（区、市）从调整前的10个下降到调整后的7个。河北、山西、安徽等16个省（区、市）纯技术效率值上升，辽宁、江苏、江西等5个省（区、市）纯技术效率值不变，表明在考虑外部环境和随机噪声的情况下，多数省份养老机构资源配置水平处于较高水平。规模效率为1的省（区、市）从9个下降到3个，辽宁、江西、四川地区调整后规模效率值为1，天津、福建、海南等10个省份的规模效率值低于平均值。
2.2　空间自相关性分析
2.2.1　全局空间自相关性分析
全局Moran I自相关分析结果显示，2021年我国养老机构资源配置综合效率全局Moran I指数为0.228（Z=2.226 1，P=0.025），通过5%显著性检验，表明我国31个省（区、市）的养老机构资源配置效率存在显著的正相关关系，整体上存在空间聚集效应。
2.2.2　局部空间自相关性分析
采用局部Getis-Ord Gi*指数热点分析对我国养老机构资源配置效率进行局部空间自相关分析，表3结果显示2021年我国养老机构资源配置冷点地区主要集中在新疆、西藏、广西。热点地区较为集中，主要集中在东北、华北以及山东地区。
3　讨论
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3.1　提高养老机构资源配置整体效率，及时关注冷热点区域
研究结果显示，调整后我国养老机构资源配置的整体规模效率均值为0.822，效率值为1的省份只有3个省（区、市），仅占10%，在未充分考虑控制环境因素和随机干预时，我国养老机构资源配置被高估。大部分养老机构规模报酬呈现递增趋势，产出增长比例大于投入增长比例，因此可以适当增加养老机构资源投入。国家卫生健康委老龄司司长王海东[18]表示，预计“十四五”时期，60岁以上老年人口总量将突破3亿，占比超过20%，进入中度老龄化阶段，养老机构的兜底作用应充分发挥，加大其资源投入。因此，政府应充分考虑当地实际情况，根据养老服务需求控制养老机构规模，完善相应配套设施，优化养老机构服务质量，促进养老机构资源配置效率的提升。2018年取消了养老机构设立许可，在一定程度上激发了养老服务行业活力，引导社会力量根据市场需求参与养老工作，积极探索多样化养老机构经验模式，满足养老服务需求，完善养老服务体系建设。根据全局和局部空间自相关性分析来看，2021年我国养老机构资源配置效率存在空间聚集效应。养老机构资源配置效率热点地区呈现以华北地区向周围扩散趋势，反映出养老机构资源配置效率最高地区与邻近省份存在空间关联性，这与何文举[19]研究结果一致。因此，及时关注养老机构资源配置效率的冷热点地区，在养老机构建设中更加注重当地实际养老服务需求，避免养老机构床位和人员的冗余和盲目扩张，造成资源浪费。
3.2　推动我国养老机构规模发展，同时提高养老机构管理能力
研究结果显示，控制环境变量后，养老机构资源配置效率主要受规模效率的影响，与边妗伟[10]研究结果一致。调整后的规模效率值大部分呈现下降趋势且地区差异较大，其中西部地区规模效率值最低，下降幅度较大，而东部地区规模效率下降幅度小。西部地区经济发展水平较低，多以民族聚居形态为主，家庭养老观念根深蒂固，养老机构资源配置投入低于其他地区，规模效率较低[20]。东部规模效率较低可能受养老机构管理效率的影响，管理人员水平较低和管理人才缺乏，均会降低其管理效率。因此，应注重养老机构的规模发展，各地根据实际情况进行合理配置，并积极探索多种养老服务模式，引导社会力量参与养老服务，满足老年健康服务需求[21] 。其次需要提高养老机构的管理能力，加强养老机构管理人员的管理服务培训，采用专业对口，综合提高管理人员的管理和机构运营能力。
3.3　因地制宜，合理规划各省份养老机构资源配置
研究发现不同环境变量对各个投入松弛值产生不同影响。城镇人口比重、一般公共预算支出占GDP的比重、老年人口抚养比对养老机构床位数、年末职工数以及机构建筑面积这三个投入松弛变量值产生负向影响。城镇人口比重反映当地经济发展水平以及人口聚集程度，直接影响养老机构资源配置[22]。一般公共预算支出占GDP的比重表明财政对养老产业的支持状况，比重增加直接推动养老机构的发展。老年人口抚养比增加，加之家庭养老功能弱化，家庭结构小型化带来的影响，直接影响当地养老机构资源配置效率的提高[23]。人均GDP特化系数对养老机构床位数、职工数以及机构建筑面积产生正向影响。从全国层面反映当地经济发展水平的人均GDP特化系数，间接反映当地居民的服务购买能力。经济发达地区，服务购买能力强，对养老机构环境状况以及人员素质要求较高，但地区经济发展会追求床位、人员以及建筑面积的满目扩张，极易造成养老机构资源配置效率下降[24]。因此，各地区提升养老机构资源配置效率的同时，应因地制宜，根据当地经济发展状况、城镇化水平以及人口老龄化程度，合理调整养老机构资源配置，促进其效率的提升。
基金
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  • 山东省自然科学基金(ZR2022MG043)
文献
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2024年第51卷第7期
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doi: 10.20043/j.cnki.MPM.202311040
  • 接收时间：2023-11-04
  • 首发时间：2026-03-18
  • 出版时间：2024-04-10
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  • 收稿日期：2023-11-04
基金
山东省自然科学基金(ZR2022MG043)
作者信息
    1.山东第二医科大学管理学院，山东 潍坊 261053
    2.山东第二医科大学公共卫生学院
    3.“健康山东”重大社会风险预测与治理协同创新中心，山东 潍坊 261053
    4.健康相关重大社会风险预警协同创新中心，上海 200032

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2种不同金属材料的力学参数
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Number of
species		 占总种数比例
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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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