Article(id=1241522926093135891, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241522919977841545, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202310335, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1697817600000, receivedDateStr=2023-10-21, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773931731961, onlineDateStr=2026-03-19, pubDate=1710000000000, pubDateStr=2024-03-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773931731961, onlineIssueDateStr=2026-03-19, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773931731961, creator=13701087609, updateTime=1773931731961, updator=13701087609, issue=Issue{id=1241522919977841545, tenantId=1146029695717560320, journalId=1227665162245664772, year='2024', volume='51', issue='5', pageStart='769', pageEnd='960', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773931730503, creator=13701087609, updateTime=1773931880386, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241523548695622547, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241522919977841545, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241523548695622548, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241522919977841545, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=871, endPage=876, ext={EN=ArticleExt(id=1241522926902636596, articleId=1241522926093135891, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Spatial distribution characteristics and efficiency evaluation of resources of pension institutions in Dongguan city based on GIS and three-stage DEA model, columnId=1228016567846367388, journalTitle=Modern Preventive Medicine, columnName=Health Policy and Management, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze the spatial distribution characteristics, efficiency, and influencing factors of pension institutions in Dongguan, so as to provide reference for optimizing the resource allocation of pension institutions in Dongguan.

Methods

The resource allocation data of pension institutions in Dongguan were obtained by questionnaire survey, and the spatial distribution characteristics and efficiency of pension institutions were analyzed and evaluated based on GIS and three-stage DEA model.

Results

There was a good spatial coupling between the resources of pension institutions in Dongguan and the elderly population over 60 years old; the lowest occupancy rate was 12.50%, the highest was 100.005%, and the phenomenon of “difficulty in finding a bed” and “half of the beds were vacant” coexisted. In the third stage, the average comprehensive efficiency decreased from 0.679 to 0.635, and environmental factors had a great influence on the efficiency of resource allocation in Dongguan. There were great differences in the efficiency of pension institutions in different areas. The comprehensive efficiency of urban areas was 0.784, which exceeded the average level of the whole city (0.635). The comprehensive efficiency of the eastern industrial park was only 0.439, which did not reach the average level of the whole city. The per capita regional GDP and the level of aging had a negative impact on efficiency.

Conclusion

It is suggested to rationally allocate the resources of pension institutions, optimize regional development planning, promote the upgrading of institutional pension services, improve the efficiency of resource allocation, and provide improved reference scheme for improving the service level of pension institutions in Dongguan.

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目的

分析东莞市养老机构资源空间分布特征、效率及其影响因素,为优化东莞市养老机构资源配置提供参考。

方法

通过问卷调查获取东莞市养老机构资源配置数据,基于GIS和三阶段DEA模型对养老机构资源进行空间分布特征分析和效率评价。

结果

东莞市养老机构资源与60岁以上老年人口空间耦合性较好;入住率最低为12.50%,最高达100.00%,“一床难求”与“一半空置”现象并存;第三阶段综合效率均值由0.679降至0.635,环境因素对东莞市资源配置效率影响较大;各片区养老机构效率差异大,城区片区综合效率为0.784,超过全市平均水平(0.635),东部工业园片区综合效率仅为0.439,未达全市平均水平;人均地区生产总值和老龄化水平对效率具有负向影响。

结论

合理配置养老机构资源,优化区域发展规划,推动机构养老服务智慧升级,提高资源配置效率,为提升东莞市养老机构服务水平提供更完善的参考方案。

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彭浩晟,E-mail:
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郭珊珊(1997—),女,硕士在读,研究方向:卫生事业管理

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郭珊珊(1997—),女,硕士在读,研究方向:卫生事业管理

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郭珊珊(1997—),女,硕士在读,研究方向:卫生事业管理

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figureFileBig=vD2QtKAV2I38I3QchTYU/Q==, tableContent=null), ArticleFig(id=1241678327015068188, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241522926093135891, language=CN, label=图3, caption=东莞市老年人口和养老机构入住率空间分布, figureFileSmall=Powp+Z9Pw+MsC9sf12AhHg==, figureFileBig=vD2QtKAV2I38I3QchTYU/Q==, tableContent=null), ArticleFig(id=1241678327711322662, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241522926093135891, language=EN, label=Table 1, caption=

Descriptive analysis of indexes and variables of three-stage DEA

, figureFileSmall=null, figureFileBig=null, tableContent=
分类变量最小值最大值
投入指标床位数(张)180.355±149.83440581
职工数56.387±64.08910304
产出指标入住老人总数91.548±92.95011417
失能半失能老人数84.710±89.6763400
环境变量人均地区生产总值(万元)9.797±2.5905.8617.60
60岁及以上老年人口占比(%)6.261±2.7142.6813.42
), ArticleFig(id=1241678328294330926, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241522926093135891, language=CN, label=表1, caption=

三阶段DEA各指标、变量描述性分析

, figureFileSmall=null, figureFileBig=null, tableContent=
分类变量最小值最大值
投入指标床位数(张)180.355±149.83440581
职工数56.387±64.08910304
产出指标入住老人总数91.548±92.95011417
失能半失能老人数84.710±89.6763400
环境变量人均地区生产总值(万元)9.797±2.5905.8617.60
60岁及以上老年人口占比(%)6.261±2.7142.6813.42
), ArticleFig(id=1241678328617292340, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241522926093135891, language=EN, label=Table 2, caption=

Spearman correlation test results of input and output indicators

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指标床位数职工数
入住老人总数0.878a0.872a
失能半失能老人数0.898a0.883a
), ArticleFig(id=1241678329493901891, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241522926093135891, language=CN, label=表2, caption=

投入与产出指标的Spearman相关性检验结果

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指标床位数职工数
入住老人总数0.878a0.872a
失能半失能老人数0.898a0.883a
), ArticleFig(id=1241678329934303819, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241522926093135891, language=EN, label=Table 3, caption=

Comparison of resource allocation efficiency between the first stage and the third stage of elderly care institutions in Dongguan

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地区第一阶段第三阶段
综合效率纯技术效率规模效率综合效率纯技术效率规模效率
城区片区东城街道0.8731.0000.8731.0001.0001.000
南城街道0.6380.8360.7640.7880.9120.864
万江街道1.0001.0001.0001.0001.0001.000
莞城街道0.7140.8490.8410.8870.9100.974
石碣镇0.6350.7700.8240.4220.8280.510
高埗镇0.6001.0000.6000.4621.0000.462
石龙镇0.6380.8360.7640.9280.9940.934
均值0.7540.9090.8290.7840.9490.821
松山湖片区茶山镇0.9300.9400.9900.7881.0000.788
大朗镇1.0001.0001.0000.8910.9750.914
大岭山镇0.3750.5580.6720.3890.6900.564
东坑镇0.7720.7880.9790.8140.8290.982
寮步镇0.5251.0000.5250.2550.9170.278
黄江镇0.7071.0000.7070.9951.0000.995
均值0.7180.8810.8120.6890.9020.754
东部工业园片区常平镇0.6540.6580.9950.6530.7020.930
谢岗镇0.5180.6710.7720.4820.9150.527
桥头镇0.8301.0000.8300.5011.0000.501
横沥镇0.6390.7540.8480.4260.8160.522
石排镇0.6200.7970.7780.3760.8200.459
企石镇0.2810.5970.4710.1980.8150.242
均值0.5900.7460.7820.4390.8450.530
水乡新城片区望牛墩镇0.7560.8770.8630.8940.9410.950
道滘镇0.5430.5580.9730.5150.8770.587
洪梅镇0.8860.8880.9970.9441.0000.944
中堂镇0.5640.8040.7010.4601.0000.460
均值0.6870.7820.8840.7030.9550.735
滨海片区沙田镇0.4590.5710.8030.4560.8470.538
长安镇0.3700.8700.4250.2310.8450.273
厚街镇0.8680.9130.9510.6940.8820.786
虎门镇0.5380.5500.9790.5010.6800.736
均值0.5590.7260.7900.4710.8140.583
东南临深片区樟木头镇1.0001.0001.0001.0001.0001.000
凤岗镇0.5950.7630.7800.5580.8340.669
塘厦镇1.0001.0001.0000.8681.0000.868
清溪镇0.3470.6020.5760.3180.7690.413
均值0.7360.8410.8390.6860.9010.738
全市均值0.6790.8230.8200.6350.8970.699
), ArticleFig(id=1241678330395677267, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241522926093135891, language=CN, label=表3, caption=

东莞市养老机构资源配置效率第一阶段和第三阶段对比

, figureFileSmall=null, figureFileBig=null, tableContent=
地区第一阶段第三阶段
综合效率纯技术效率规模效率综合效率纯技术效率规模效率
城区片区东城街道0.8731.0000.8731.0001.0001.000
南城街道0.6380.8360.7640.7880.9120.864
万江街道1.0001.0001.0001.0001.0001.000
莞城街道0.7140.8490.8410.8870.9100.974
石碣镇0.6350.7700.8240.4220.8280.510
高埗镇0.6001.0000.6000.4621.0000.462
石龙镇0.6380.8360.7640.9280.9940.934
均值0.7540.9090.8290.7840.9490.821
松山湖片区茶山镇0.9300.9400.9900.7881.0000.788
大朗镇1.0001.0001.0000.8910.9750.914
大岭山镇0.3750.5580.6720.3890.6900.564
东坑镇0.7720.7880.9790.8140.8290.982
寮步镇0.5251.0000.5250.2550.9170.278
黄江镇0.7071.0000.7070.9951.0000.995
均值0.7180.8810.8120.6890.9020.754
东部工业园片区常平镇0.6540.6580.9950.6530.7020.930
谢岗镇0.5180.6710.7720.4820.9150.527
桥头镇0.8301.0000.8300.5011.0000.501
横沥镇0.6390.7540.8480.4260.8160.522
石排镇0.6200.7970.7780.3760.8200.459
企石镇0.2810.5970.4710.1980.8150.242
均值0.5900.7460.7820.4390.8450.530
水乡新城片区望牛墩镇0.7560.8770.8630.8940.9410.950
道滘镇0.5430.5580.9730.5150.8770.587
洪梅镇0.8860.8880.9970.9441.0000.944
中堂镇0.5640.8040.7010.4601.0000.460
均值0.6870.7820.8840.7030.9550.735
滨海片区沙田镇0.4590.5710.8030.4560.8470.538
长安镇0.3700.8700.4250.2310.8450.273
厚街镇0.8680.9130.9510.6940.8820.786
虎门镇0.5380.5500.9790.5010.6800.736
均值0.5590.7260.7900.4710.8140.583
东南临深片区樟木头镇1.0001.0001.0001.0001.0001.000
凤岗镇0.5950.7630.7800.5580.8340.669
塘厦镇1.0001.0001.0000.8681.0000.868
清溪镇0.3470.6020.5760.3180.7690.413
均值0.7360.8410.8390.6860.9010.738
全市均值0.6790.8230.8200.6350.8970.699
), ArticleFig(id=1241678330806719067, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241522926093135891, language=EN, label=Table 4, caption=

SFA regression results of relaxation variables of investment index of elderly care institutions in Dongguan

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环境变量床位数职工数
常数项-93.559a-12.614a
人均地区生产总值3.382a1.316b
60岁以上老年人口占比7.472a-0.300
Sigma-squared3 958.719a387.875a
Gamma0.999a0.999a
LR12.338a23.241a
), ArticleFig(id=1241678331066765918, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241522926093135891, language=CN, label=表4, caption=

东莞市养老机构投入指标松弛变量SFA回归结果

, figureFileSmall=null, figureFileBig=null, tableContent=
环境变量床位数职工数
常数项-93.559a-12.614a
人均地区生产总值3.382a1.316b
60岁以上老年人口占比7.472a-0.300
Sigma-squared3 958.719a387.875a
Gamma0.999a0.999a
LR12.338a23.241a
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东莞市养老机构资源空间分布特征及效率评价——基于GIS和三阶段DEA模型
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郭珊珊 1 , 杜进林 1 , 柯小瑜 2 , 卢小焕 3 , 莫晓宇 4 , 彭浩晟 5
现代预防医学 | 卫生政策与管理 2024,51(5): 871-876
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现代预防医学 | 卫生政策与管理 2024, 51(5): 871-876
东莞市养老机构资源空间分布特征及效率评价——基于GIS和三阶段DEA模型
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郭珊珊1, 杜进林1, 柯小瑜2, 卢小焕3, 莫晓宇4, 彭浩晟5
作者信息
  • 1.广东医科大学公共卫生学院,广东 东莞 523808
  • 2.东莞城市学院语言文化学院
  • 3.东莞市社会福利中心
  • 4.东莞市民政局养老服务和儿童福利科
  • 5.广东医科大学研究生院,广东 东莞 523808
  • 郭珊珊(1997—),女,硕士在读,研究方向:卫生事业管理

通讯作者:

彭浩晟,E-mail:
Spatial distribution characteristics and efficiency evaluation of resources of pension institutions in Dongguan city based on GIS and three-stage DEA model
Shan-shan GUO1, Jin-lin DU1, Xiao-yu KE2, Xiao-huan LU3, Xiao-yu MO4, Hao-sheng PENG5
Affiliations
  • School of Public Health, Guangdong Medical University, Dongguan, Guangdong 523808, China
出版时间: 2024-03-10 doi: 10.20043/j.cnki.MPM.202310335
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目的

分析东莞市养老机构资源空间分布特征、效率及其影响因素,为优化东莞市养老机构资源配置提供参考。

方法

通过问卷调查获取东莞市养老机构资源配置数据,基于GIS和三阶段DEA模型对养老机构资源进行空间分布特征分析和效率评价。

结果

东莞市养老机构资源与60岁以上老年人口空间耦合性较好;入住率最低为12.50%,最高达100.00%,“一床难求”与“一半空置”现象并存;第三阶段综合效率均值由0.679降至0.635,环境因素对东莞市资源配置效率影响较大;各片区养老机构效率差异大,城区片区综合效率为0.784,超过全市平均水平(0.635),东部工业园片区综合效率仅为0.439,未达全市平均水平;人均地区生产总值和老龄化水平对效率具有负向影响。

结论

合理配置养老机构资源,优化区域发展规划,推动机构养老服务智慧升级,提高资源配置效率,为提升东莞市养老机构服务水平提供更完善的参考方案。

养老机构资源  /  空间分布  /  效率  /  GIS  /  三阶段DEA
Objective

To analyze the spatial distribution characteristics, efficiency, and influencing factors of pension institutions in Dongguan, so as to provide reference for optimizing the resource allocation of pension institutions in Dongguan.

Methods

The resource allocation data of pension institutions in Dongguan were obtained by questionnaire survey, and the spatial distribution characteristics and efficiency of pension institutions were analyzed and evaluated based on GIS and three-stage DEA model.

Results

There was a good spatial coupling between the resources of pension institutions in Dongguan and the elderly population over 60 years old; the lowest occupancy rate was 12.50%, the highest was 100.005%, and the phenomenon of “difficulty in finding a bed” and “half of the beds were vacant” coexisted. In the third stage, the average comprehensive efficiency decreased from 0.679 to 0.635, and environmental factors had a great influence on the efficiency of resource allocation in Dongguan. There were great differences in the efficiency of pension institutions in different areas. The comprehensive efficiency of urban areas was 0.784, which exceeded the average level of the whole city (0.635). The comprehensive efficiency of the eastern industrial park was only 0.439, which did not reach the average level of the whole city. The per capita regional GDP and the level of aging had a negative impact on efficiency.

Conclusion

It is suggested to rationally allocate the resources of pension institutions, optimize regional development planning, promote the upgrading of institutional pension services, improve the efficiency of resource allocation, and provide improved reference scheme for improving the service level of pension institutions in Dongguan.

Pension institution resources  /  Spatial distribution  /  Efficiency  /  GIS  /  Three-stage DEA
郭珊珊, 杜进林, 柯小瑜, 卢小焕, 莫晓宇, 彭浩晟. 东莞市养老机构资源空间分布特征及效率评价——基于GIS和三阶段DEA模型. 现代预防医学, 2024 , 51 (5) : 871 -876 . DOI: 10.20043/j.cnki.MPM.202310335
Shan-shan GUO, Jin-lin DU, Xiao-yu KE, Xiao-huan LU, Xiao-yu MO, Hao-sheng PENG. Spatial distribution characteristics and efficiency evaluation of resources of pension institutions in Dongguan city based on GIS and three-stage DEA model[J]. Modern Preventive Medicine, 2024 , 51 (5) : 871 -876 . DOI: 10.20043/j.cnki.MPM.202310335
“十四五”时期,我国60岁及以上老年人口占比将超过20%,进入中度老龄化阶段。2035年左右,60岁及以上老年人口占比将超过30%,进入重度老龄化阶段[1]。人口老龄化加剧很大程度伴随着社会对养老服务需求的增加以及我国养老服务产业规模的扩张。2022年第一季度,作为我国养老服务体系重要支撑的各类养老机构和设施总数已达36万个、床位812.6万张,且养老床位总数比2012年底的416.5万张翻了近1番[2]。尽管养老机构资源总量不断提升、规模不断扩大,其资源配置效率从国家、省到市级层面均存在不同程度的改善空间[3-5]
截至2022年6月,作为我国特大城市之一的东莞,共51家在运营养老机构,床位共计5 675张[6]。然而,从目前的研究成果来看,东莞市养老机构资源配置现状及利用效率还不得而知。因此,本研究对东莞市养老机构开展资源配置调查,采用三阶段数据包络分析(data envelopment analysis,DEA)模型评价各镇街养老机构效率,并探究环境因素对效率的影响程度。另外,以往相关研究对养老机构资源配置基本情况的分析多采用以文字陈述为主的描述性分析[4,7],缺少基于空间角度的探索。本研究借助ArcGIS对东莞市不同类型、不同规模养老机构空间分布及入住率等进行可视化分析,直观呈现各区、镇街养老机构资源配置差异,进而为东莞市养老机构开办主体提升运营水平、为政府优化养老机构发展模式及空间布局提供参考。
本研究投入和产出指标通过问卷调查获得。2023年4—5月,本课题组对东莞市截至2023年5月登记在册且正常运营的46家养老机构开展问卷调查,调查内容包含养老机构性质、入住老人数、床位数、人员配备等。为保证调查数据真实可靠,本课题组已对不符合要求的问卷予以电话访问补缺修正。人均地区生产总值、60岁及以上老年人口占比两个环境变量源于《2022东莞市统计年鉴》及《东莞市第七次全国人口普查公报》。养老机构信息点(point of information,POI)通过百度地图服务的应用接口获取,经过换算将POI坐标转换成国际通用的WGS-84坐标。
在ArcGIS 10.8中导入审图号为GS(2022)1873号的标准地图,将东莞市60岁及以上老年人口占比、养老机构数等数据与各镇街相连接,分析老年人口和养老机构床位、入住率的空间分布特征。
传统DEA是一种基于多投入、多产出指标的以评价决策单元(decision-making units,DMU)效率相对有效性的非参数方法[8]。DEA模型包括规模报酬不变的CCR模型和规模报酬可变的BCC模型,本研究养老机构规模报酬可变,因而选用BCC模型[9]。三阶段DEA模型则是在传统DEA模型基础之上,引入随机前沿分析(stochastic frontier analysis,SFA)回归模型,剔除管理无效率、环境因素的干扰,以便在第三阶段获得更为真实的效率值[10]。本研究选取东莞市养老机构床位数、职工数作为投入指标,入住老人总数、失能半失能老人数作为产出指标,人均地区生产总值、60岁及以上老年人口占比作为环境变量。
运用DEAP 2.1计算各DMU的综合效率、纯技术效率、规模效率及投入指标的松弛值;采用FRONT 4.1分析环境变量影响程度,检验水准α=0.05。
东莞市正常运营的46家养老机构中,公办31家(67.39%),民办15家(32.61%);经营年限多在10年以上,占60.87%;房屋来源以自有为主,占60.87%;床位总数达5 591张,且各机构床位多在100张以下,占54.35%;总入住率为50.76%,民办机构入住率为53.29%,高于公办的48.49%。
西部中心城区作为综合服务中心,老年人口占比多,机构分布密集且床位规模多在中等偏上;其余以科技创新、智能制造为主要职能的中部松山湖片区、东部工业园片区、东南临深片区等,老年人口占比总体较低,机构分布分散且多数机构规模较小,但同时设置三家床位数在300张以上的大型养老机构作为补给。可见,东莞市养老机构总体呈现中心城区集聚、规模大,其他片区分散、规模小的空间分布特点。从入住率来看,中心城区养老机构入住率较高,其他片区除个别医养结合机构入住率较高外,普遍处于空置状态。见图123
本研究投入和产出指标情况见表1,各指标观察值无缺失值、无负值。以东莞市设置了养老机构的31个镇街为DMU,样本量符合“≥3(投入指标数+产出指标数)”的标准[11]
对投入与产出指标进行Spearman相关性检验,结果显示,投入与产出指标呈现正相关(P<0.01),选取的指标适用于DEA模型。见表2
结果显示,东莞市养老机构资源配置综合效率、纯技术效率、规模效率均值分别为0.679、0.823、0.820,纯技术效率、规模效率均值相当。其中,万江街道、大朗镇、樟木头镇、塘厦镇的综合效率为1,属于DEA有效,处于效率前沿面。从片区看,东部工业园片区、滨海片区综合效率均值为0.590、0.559,低于全市均值的0.679,其余片区均高于全市均值。见表3
结果显示,床位数、职工数的LR统计值均大于广义单边1%水平的临界值,说明SFA模型构建合理。各投入指标的gamma值均趋向1,说明环境因素和管理无效率是影响养老机构资源配置的关键因素。其中,人均地区生产总值与床位投入(P<0.01)、职工投入(P<0.05)松弛变量存在正相关,60岁以上老年人口占比对床位投入(P<0.01)松弛变量同样存在正相关,与职工投入松弛变量不相关(P>0.05)。见表4
(1)从整体来看,在排除环境变量的影响后,第三阶段的综合效率和规模效率均值分别下降6.48%、14.76%,说明养老机构资源配置效率在未考虑环境因素时呈虚高之态,且受环境因素影响较大。而在考虑环境因素之后,纯技术效率均值上升8.99%,且纯技术效率均值为0.897,大于规模效率均值的0.699,说明综合效率均值下降主要源于规模效率下降。
(2)从片区来看,无论是否考虑环境变量,城区片区的效率均值保持稳定,均排在前列,说明城区片区养老机构的技术水平较高、管理能力较优,受外部环境因素的影响较小。而东部工业园片区、滨海片区等效率值调整投入变量前后差异大,说明这类片区养老机构的效率受外部环境因素较大。
(3)从镇街来看,未考虑环境变量时,万江街道、大朗镇、樟木头镇、塘厦镇的综合效率值为1,养老机构资源配置效率达到效率前沿面,处于DEA有效状态;考虑环境变量后,处于效率前沿面的镇街减少至万江街道、樟木头镇2个,大朗镇、塘厦镇由DEA有效变为DEA无效,即此前在环境因素影响之下呈现虚假的DEA有效。另外,调整投入变量以后,寮步镇、长安镇等20个镇街综合效率值存在不同程度的下降,黄江镇、莞城街道等9个镇街综合效率存在一定幅度上升,可见各镇街养老机构效率值受环境影响因素较大。见表3
2021年底,东莞市60岁及以上老年人口占常住人口的5.47%,65岁及以上老年人口占3.54%,尚未达到老龄化社会标准,养老机构资源总量能够满足当前老人需求。各片区养老机构资源与60岁及以上老年人口占比基本实现空间耦合。但是,机构整体入住率低,不同类型机构入住率相差悬殊,可谓“一床难求”和“一半空置”现象并存。究其原因,公办养老机构成立时间早,基础设施陈旧,相比近年来新批准建立的部分民办养老机构未能更全面地满足老人个性化、多样化的服务需求。同时,宣传力度不足也可能是入住率一大影响因素。调查中发现,15家民办机构中,将经费用于品牌运营的占比高达93.33%,而这一占比在公办机构中仅为25.81%。此外,通过实地访谈了解到,东莞市养老机构中多为中重度失能老人,照护专业水平要求高,多通过本镇街敬老院转送或直接入住医养结合型养老机构,而该类机构本身收住较多失能老人,导致医养结合养老机构床位通常是供不应求。针对上述情况,一方面,政府可加强养老政策宣传,提高机构养老接受度。另一方面,各镇街要加强养老工作协作联动,若长期入住率不足,可考虑裁减一批不必要床位,或将相邻镇街入住爆满机构的老人引流至空置率高的机构。医疗单位周边机构可借助医疗资源可及性优势,增加失能失智专业化养老护理服务,缓解医养结合养老机构床位紧张压力。
在排除环境因素影响之后,东莞市养老机构资源配置效率总体下降,仅3个镇街的综合效率为1;从效率分解值来看,多数镇街机构的纯技术效率在调整后得到提升,规模效率则处于较低水平,成为拉低综合效率的主要因素,说明当前东莞市养老机构的技术水平、管理能力有待提升,且在现有的技术水平和管理能力下,要侧重加大养老机构的投入规模。东莞市养老机构平均成立时间为21年,经营年限长,积累了一定的技术和管理能力。但是,随着机构养老服务市场的快速发展、养老需求的不断更新,养老机构的技术、管理手段可能存在滞后,亟待革新。尽管东莞市养老机构资源总量足,但机构规模不大,65.22%的机构床位数未达全市平均值(121张),养老护理员、社会工作者等人力资源也存在大量缺口,因而规模效率表现欠缺。另外,区域间效率差异较大,城区片区、水乡新城片区优于其他各片区,综合效率高于全市均值,这与各片区经济发展水平、养老事业发展底蕴和重视程度密切相关。针对上述情况,一要推动机构养老服务智慧升级,改善资源配置纯技术和管理效率。东莞,作为“制造名城”,科技创新和先进制造是其城市核心特色。相关部门可依托其强大智能制造基础,引入智能养老管理系统,借助养老新思路、新技术实现科学化、精细化管理。二要科学调整资源配置,提高规模效率。对于东部工业园片区、滨海片区等规模效率低的地区,要在基于老人实际服务需求的基础上,合理增加物力、人力资源的投入,减少因规模效率低下而带来的差距。
从SFA回归结果可知,人均地区生产总值对养老机构资源配置效率具有负向影响,即地区经济总量水平高,易引起养老机构床位、人力资源投入的浪费,该结果与焦奥南[12]的研究类似。这可能是由于在地区经济高速发展的背景下,为使机构养老事业发展与经济发展保持同步,政府和养老机构运营方盲目追求养老机构数量、扩张养老机构规模,配套床位数、职工数增加的同时,资源的冗余风险也相应增加。另外,60岁以上老年人口占比对床位资源配置效率也存在负向影响。老年人口总量增加,机构养老服务需求增加,作为养老机构资源配置中最为基本的床位数必将迎来增长。同理,床位数总量上涨,冗余风险也相应上涨。因此,机构养老资源配置应当始终把握服务需求这一核心要素,根据老年人口规模、机构养老服务市场需求设置相应的配置标准。在达到既定床位、人员配置标准时,养老部门应在现有机构养老资源总量基础上,优化存量、提升质量,推动东莞市养老机构资源配置效率的进一步提升。
本文作为当前少数针对东莞市养老机构效率分析的研究,还存在一定局限性,如受数据同向性要求限制,未能纳入更多投入、产出指标;获取各机构财政支持数据受限,未能将其纳入到环境变量中考量。望之后有关研究能够弥补上述缺陷,为提升东莞市养老机构服务水平提供更完善的参考方案。
  • 广东省研究生教育创新计划项目(2020JGXM056)
  • 广东省教育科学“十三五”规划2019年度高校哲学社会科学专项研究项目资助(2019GXJK226)
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2024年第51卷第5期
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doi: 10.20043/j.cnki.MPM.202310335
  • 接收时间:2023-10-21
  • 首发时间:2026-03-19
  • 出版时间:2024-03-10
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  • 收稿日期:2023-10-21
基金
广东省研究生教育创新计划项目(2020JGXM056)
广东省教育科学“十三五”规划2019年度高校哲学社会科学专项研究项目资助(2019GXJK226)
作者信息
    1.广东医科大学公共卫生学院,广东 东莞 523808
    2.东莞城市学院语言文化学院
    3.东莞市社会福利中心
    4.东莞市民政局养老服务和儿童福利科
    5.广东医科大学研究生院,广东 东莞 523808

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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

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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