Article(id=1241035812670853378, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241035810628235909, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202407072, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1720195200000, receivedDateStr=2024-07-06, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773815595071, onlineDateStr=2026-03-18, pubDate=1733760000000, pubDateStr=2024-12-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773815595071, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773815595071, creator=13701087609, updateTime=1773815595071, updator=13701087609, issue=Issue{id=1241035810628235909, tenantId=1146029695717560320, journalId=1227665162245664772, year='2024', volume='51', issue='23', pageStart='4225', pageEnd='4416', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773815594584, creator=13701087609, updateTime=1773815743629, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241036435843764756, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241035810628235909, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241036435843764757, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241035810628235909, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=4327, endPage=4332, ext={EN=ArticleExt(id=1241035815179047183, articleId=1241035812670853378, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=A study on the operational efficiency of county-level medical and health sub-centers in Sichuan Province based on data envelopment analysis, columnId=1228016567846367388, journalTitle=Modern Preventive Medicine, columnName=Health Policy and Management, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze the comprehensive efficiency and total factor productivity changes of county-level medical and health sub-centers (referred to as “sub-centers”) in Sichuan Province, providing valuable references for the continuous advancement of sub-center construction and the healthy development of grassroots medical and health systems nationwide.

Methods

A total of 302 sub-centers in Sichuan Province were selected as the research subjects, and the DEA-Malmquist index model was employed to measure and evaluate their static and dynamic efficiencies.

Results

Using 21 cities and prefectures as decision-making units, the comprehensive efficiency of the sub-centers was 0.884, with 12 cities and prefectures experiencing increasing returns to scale and 9 achieving optimal operational efficiency. Analyzing the time series of the 302 sub-centers as decision-making units, the total factor productivity of the sub-centers increased by 1.4%; regionally, total factor productivity rose in 16 cities and prefectures.

Conclusion

The construction of sub-centers in Sichuan Province has been a successful pilot project, with overall operational efficiency being relatively good. However, significant regional development disparities and insufficient technological advancement persist. The government and relevant departments should continue to strengthen policy guidance, develop scientific and reasonable planning, focus on solidifying the grassroots talent base, and enhance information technology infrastructure to empower the vitality of sub-center healthcare.

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目的

分析四川省县域医疗卫生次中心(简称“次中心”)综合效率和全要素生产率变动情况,为全国各地持续推进次中心建设,促进基层医疗卫生体系健康发展提供有益借鉴。

方法

以四川省302家次中心为研究对象,运用DEA-Malmquist指数模型测算并评价其静态效率和动态效率。

结果

以21个市州为决策单元,次中心的综合效率为0.884,12个市州处于规模报酬递增状态,9个市州运行效率达到最优状态。以302家次中心为决策单元,按时间序列分析,次中心全要素生产率提高1.4%;按地区分别统计,有16个市州全要素生产率上升。

结论

四川省次中心建设是成功的试点,运行效率总体情况较好。但存在地区发展差异明显、技术进步不足的问题,政府及有关部门应持续加强政策引领,制定科学合理的规划,着力夯实基层人才基础,同时加强信息化建设,赋能次中心医疗活力。

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李家伟,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=Z0d9jywSU8HGGBSIVbsC+g==, magXml=7StL6L2/jsiXwYsminYgPQ==, pdfUrl=null, pdf=BdI+Aa/PsUZZyRuf+E6rBA==, pdfFileSize=1001292, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=4gP1glbvbBoA9EUkUrUCMA==, mapNumber=null, authorCompany=null, fund=null, authors=

陈丽(2000—),女,硕士在读,研究方向:卫生管理与政策研究

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陈丽(2000—),女,硕士在读,研究方向:卫生管理与政策研究

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陈丽(2000—),女,硕士在读,研究方向:卫生管理与政策研究

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Analysis on personnel remuneration in the township hospitals in China[J]. Chinese Health Economics, 2021, 40(1):71-74.(In Chinese), articleTitle=Analysis on personnel remuneration in the township hospitals in China, refAbstract=null)], funds=[Fund(id=1241069124768551252, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035812670853378, awardId=0701-234011130073, language=CN, fundingSource=2023年四川省县域医疗卫生次中心建设项目监测与验收(0701-234011130073), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241069117474657254, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035812670853378, xref=1., ext=[AuthorCompanyExt(id=1241069117487240167, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035812670853378, companyId=1241069117474657254, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Chengdu University of Traditional Chinese Medicine, School of Management / Health Sichuan Research Institute, Chengdu, Sichuan 611137, China), AuthorCompanyExt(id=1241069117495628777, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035812670853378, companyId=1241069117474657254, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.成都中医药大学管理学院/健康四川研究院,四川 成都 611137)]), AuthorCompany(id=1241069117608874997, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035812670853378, xref=2., ext=[AuthorCompanyExt(id=1241069117617263605, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035812670853378, companyId=1241069117608874997, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.自贡市第四人民医院)]), AuthorCompany(id=1241069117734704126, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035812670853378, xref=3., ext=[AuthorCompanyExt(id=1241069117738898431, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035812670853378, companyId=1241069117734704126, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3.成都医学院第二附属医院·核工业416医院)]), AuthorCompany(id=1241069118795862023, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035812670853378, xref=4., ext=[AuthorCompanyExt(id=1241069118804250631, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035812670853378, companyId=1241069118795862023, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=4.西南民族大学)])], figs=[ArticleFig(id=1241069124009382182, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035812670853378, language=EN, label=Table 1, caption=

DEA analysis of operation efficiency of county medical and health sub-centers in Sichuan Province

, figureFileSmall=null, figureFileBig=null, tableContent=
地区综合效率纯技术效率规模效率规模报酬相对有效性S1门急诊人 次(人次)S2入院人次 (人次)S3医疗业务 收入 (万元)S4开放床位 (张)S5卫技 人员S6投入经费 (万元)
成都平原经济区
成都市1.0001.0001.000不变有效000000
德阳市1.0001.0001.000不变有效000000
绵阳市1.0001.0001.000不变有效000000
遂宁市0.8250.8360.987递增非有效2 259.37007.5300
乐山市0.8340.9880.844递增非有效27 322.540878.591.8900
眉山市1.0001.0001.000不变有效000000
资阳市1.0001.0001.000不变有效000000
雅安市0.7870.7930.992递增非有效00147.88000
川南经济区
自贡市0.8820.9250.954递增非有效7 613.920707.87000
宜宾市0.8590.8680.990递增非有效23 879.780678.1811.4200
泸州市0.8850.8980.985递增非有效25 888.500516.35000
内江市0.8340.8790.949递增非有效26 979.250632.54000
川东北经济区
南充市0.8750.9110.961递增非有效00499.55000
广元市1.0001.0001.000不变有效000000
广安市0.6380.7200.886递增非有效6 685.9765.120000
达州市0.9410.9530.987递增非有效29 681.110974.1713.0400
巴中市1.0001.0001.000不变有效000000
攀西经济区
攀枝花市1.0001.0001.000不变有效000000
凉山州0.6650.8190.812递增非有效00712.05000
川西北生态区
甘孜州0.5321.0000.532递增弱有效000000
阿坝州1.0001.0001.000不变有效000000
全省均值0.8840.9330.947
), ArticleFig(id=1241069124118434094, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035812670853378, language=CN, label=表1, caption=

四川省县域医疗卫生次中心运行效率DEA分析

, figureFileSmall=null, figureFileBig=null, tableContent=
地区综合效率纯技术效率规模效率规模报酬相对有效性S1门急诊人 次(人次)S2入院人次 (人次)S3医疗业务 收入 (万元)S4开放床位 (张)S5卫技 人员S6投入经费 (万元)
成都平原经济区
成都市1.0001.0001.000不变有效000000
德阳市1.0001.0001.000不变有效000000
绵阳市1.0001.0001.000不变有效000000
遂宁市0.8250.8360.987递增非有效2 259.37007.5300
乐山市0.8340.9880.844递增非有效27 322.540878.591.8900
眉山市1.0001.0001.000不变有效000000
资阳市1.0001.0001.000不变有效000000
雅安市0.7870.7930.992递增非有效00147.88000
川南经济区
自贡市0.8820.9250.954递增非有效7 613.920707.87000
宜宾市0.8590.8680.990递增非有效23 879.780678.1811.4200
泸州市0.8850.8980.985递增非有效25 888.500516.35000
内江市0.8340.8790.949递增非有效26 979.250632.54000
川东北经济区
南充市0.8750.9110.961递增非有效00499.55000
广元市1.0001.0001.000不变有效000000
广安市0.6380.7200.886递增非有效6 685.9765.120000
达州市0.9410.9530.987递增非有效29 681.110974.1713.0400
巴中市1.0001.0001.000不变有效000000
攀西经济区
攀枝花市1.0001.0001.000不变有效000000
凉山州0.6650.8190.812递增非有效00712.05000
川西北生态区
甘孜州0.5321.0000.532递增弱有效000000
阿坝州1.0001.0001.000不变有效000000
全省均值0.8840.9330.947
), ArticleFig(id=1241069124219097397, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035812670853378, language=EN, label=Table 2, caption=

Changes and decomposition of total factor productivity from 2021 to 2023

, figureFileSmall=null, figureFileBig=null, tableContent=
年份(年)技术效率技术进步纯技术效率规模效率全要素生产率
2021—20221.1160.8561.1101.0050.955
2022—20230.9411.1440.9311.0111.077
均值1.0250.9891.0171.0081.014
), ArticleFig(id=1241069124302983482, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035812670853378, language=CN, label=表2, caption=

2021—2023年全要素生产效率变化及分解

, figureFileSmall=null, figureFileBig=null, tableContent=
年份(年)技术效率技术进步纯技术效率规模效率全要素生产率
2021—20221.1160.8561.1101.0050.955
2022—20230.9411.1440.9311.0111.077
均值1.0250.9891.0171.0081.014
), ArticleFig(id=1241069124391063872, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035812670853378, language=EN, label=Table 3, caption=

Statistical changes and decomposition of total factor production efficiency by city (state)

, figureFileSmall=null, figureFileBig=null, tableContent=
地区技术效率技术进步纯技术效率规模效率全要素生产率全要素生产率提高的次中心占比(%)
成都市1.0851.0051.0801.0051.08980.56
自贡市0.9951.0210.9681.0501.01841.67
攀枝花市1.1540.9611.1321.0381.10560.00
泸州市1.0431.0231.0351.0111.06668.75
德阳市1.0230.9971.0271.0011.01647.06
绵阳市0.9930.9811.0010.9970.97235.71
广元市1.0741.0271.0840.9891.10185.71
遂宁市1.0421.0401.0790.9811.08360.00
内江市0.9571.0280.9581.0170.98435.71
乐山市1.0660.9641.0281.0331.02860.00
南充市0.9370.9980.9410.9950.93239.13
眉山市1.1191.0081.1081.0121.12981.82
宜宾市1.0501.0151.1030.9661.06666.67
广安市0.9711.0050.9681.0030.96525.00
达州市0.9891.0121.0250.9691.00160.87
雅安市1.2010.8841.0241.1951.06162.50
巴中市1.0820.9841.1050.9801.06846.15
资阳市0.9671.0501.0210.9611.01353.85
甘孜藏族自治州1.1160.8720.9631.1430.95328.57
阿坝藏族羌族自治州1.4150.7311.2601.1791.00866.67
凉山彝族自治州1.2470.9311.0771.1451.14145.45
), ArticleFig(id=1241069124500115782, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035812670853378, language=CN, label=表3, caption=

分市(州)统计全要素生产效率变化及分解

, figureFileSmall=null, figureFileBig=null, tableContent=
地区技术效率技术进步纯技术效率规模效率全要素生产率全要素生产率提高的次中心占比(%)
成都市1.0851.0051.0801.0051.08980.56
自贡市0.9951.0210.9681.0501.01841.67
攀枝花市1.1540.9611.1321.0381.10560.00
泸州市1.0431.0231.0351.0111.06668.75
德阳市1.0230.9971.0271.0011.01647.06
绵阳市0.9930.9811.0010.9970.97235.71
广元市1.0741.0271.0840.9891.10185.71
遂宁市1.0421.0401.0790.9811.08360.00
内江市0.9571.0280.9581.0170.98435.71
乐山市1.0660.9641.0281.0331.02860.00
南充市0.9370.9980.9410.9950.93239.13
眉山市1.1191.0081.1081.0121.12981.82
宜宾市1.0501.0151.1030.9661.06666.67
广安市0.9711.0050.9681.0030.96525.00
达州市0.9891.0121.0250.9691.00160.87
雅安市1.2010.8841.0241.1951.06162.50
巴中市1.0820.9841.1050.9801.06846.15
资阳市0.9671.0501.0210.9611.01353.85
甘孜藏族自治州1.1160.8720.9631.1430.95328.57
阿坝藏族羌族自治州1.4150.7311.2601.1791.00866.67
凉山彝族自治州1.2470.9311.0771.1451.14145.45
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基于数据包络分析的四川省县域医疗卫生次中心运行效率研究
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陈丽 1 , 朱立燕 2 , 倪小荣 1 , 李丹 1 , 姚魏紫 3 , 熊颖 4 , 李家伟 1
现代预防医学 | 卫生政策与管理 2024,51(23): 4327-4332
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现代预防医学 | 卫生政策与管理 2024, 51(23): 4327-4332
基于数据包络分析的四川省县域医疗卫生次中心运行效率研究
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陈丽1, 朱立燕2, 倪小荣1, 李丹1, 姚魏紫3, 熊颖4, 李家伟1
作者信息
  • 1.成都中医药大学管理学院/健康四川研究院,四川 成都 611137
  • 2.自贡市第四人民医院
  • 3.成都医学院第二附属医院·核工业416医院
  • 4.西南民族大学
  • 陈丽(2000—),女,硕士在读,研究方向:卫生管理与政策研究

通讯作者:

李家伟,E-mail:
A study on the operational efficiency of county-level medical and health sub-centers in Sichuan Province based on data envelopment analysis
Li CHEN1, Li-yan ZHU2, Xiao-rong NI1, Dan LI1, Wei-zi YAO3, Ying XIONG4, Jia-wei LI1
Affiliations
  • Chengdu University of Traditional Chinese Medicine, School of Management / Health Sichuan Research Institute, Chengdu, Sichuan 611137, China
出版时间: 2024-12-10 doi: 10.20043/j.cnki.MPM.202407072
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目的

分析四川省县域医疗卫生次中心(简称“次中心”)综合效率和全要素生产率变动情况,为全国各地持续推进次中心建设,促进基层医疗卫生体系健康发展提供有益借鉴。

方法

以四川省302家次中心为研究对象,运用DEA-Malmquist指数模型测算并评价其静态效率和动态效率。

结果

以21个市州为决策单元,次中心的综合效率为0.884,12个市州处于规模报酬递增状态,9个市州运行效率达到最优状态。以302家次中心为决策单元,按时间序列分析,次中心全要素生产率提高1.4%;按地区分别统计,有16个市州全要素生产率上升。

结论

四川省次中心建设是成功的试点,运行效率总体情况较好。但存在地区发展差异明显、技术进步不足的问题,政府及有关部门应持续加强政策引领,制定科学合理的规划,着力夯实基层人才基础,同时加强信息化建设,赋能次中心医疗活力。

县域医疗卫生次中心  /  运行效率  /  资源配置  /  数据包络分析  /  Malmquist指数
Objective

To analyze the comprehensive efficiency and total factor productivity changes of county-level medical and health sub-centers (referred to as “sub-centers”) in Sichuan Province, providing valuable references for the continuous advancement of sub-center construction and the healthy development of grassroots medical and health systems nationwide.

Methods

A total of 302 sub-centers in Sichuan Province were selected as the research subjects, and the DEA-Malmquist index model was employed to measure and evaluate their static and dynamic efficiencies.

Results

Using 21 cities and prefectures as decision-making units, the comprehensive efficiency of the sub-centers was 0.884, with 12 cities and prefectures experiencing increasing returns to scale and 9 achieving optimal operational efficiency. Analyzing the time series of the 302 sub-centers as decision-making units, the total factor productivity of the sub-centers increased by 1.4%; regionally, total factor productivity rose in 16 cities and prefectures.

Conclusion

The construction of sub-centers in Sichuan Province has been a successful pilot project, with overall operational efficiency being relatively good. However, significant regional development disparities and insufficient technological advancement persist. The government and relevant departments should continue to strengthen policy guidance, develop scientific and reasonable planning, focus on solidifying the grassroots talent base, and enhance information technology infrastructure to empower the vitality of sub-center healthcare.

County-level medical and health sub-centers  /  Operational efficiency  /  Resource allocation  /  Data envelopment analysis  /  Malmquist index
陈丽, 朱立燕, 倪小荣, 李丹, 姚魏紫, 熊颖, 李家伟. 基于数据包络分析的四川省县域医疗卫生次中心运行效率研究. 现代预防医学, 2024 , 51 (23) : 4327 -4332 . DOI: 10.20043/j.cnki.MPM.202407072
Li CHEN, Li-yan ZHU, Xiao-rong NI, Dan LI, Wei-zi YAO, Ying XIONG, Jia-wei LI. A study on the operational efficiency of county-level medical and health sub-centers in Sichuan Province based on data envelopment analysis[J]. Modern Preventive Medicine, 2024 , 51 (23) : 4327 -4332 . DOI: 10.20043/j.cnki.MPM.202407072
《“健康中国2030”规划纲要》明确将“坚持以基层为重点”作为卫生健康工作方针之一,由此,我国基层医疗卫生事业得到了长足发展,但基层医疗卫生机构服务能力弱、运行效率偏低的问题仍较普遍存在,特别是在西部地区这些问题更为突出[1-2]。四川省作为西部地区人口大省,全省基层医疗卫生机构也存在数量多、布局散、能力不强等问题,无法满足人民群众就近就医需求。为打造与乡村振兴相匹配的基层医疗卫生服务能力,避免政府的有限投入被稀释,四川省在全国率先依托中心镇和特色镇卫生院建设县域医疗卫生次中心,聚集资源重点打造,将次中心建设成为具有二级综合医院水平的基层医疗卫生机构,分担县医院部分职能任务,指导帮扶周边一般乡镇卫生院,以点带面,促进基层医疗卫生服务能力提升。目前贵州[3]、湖南[4]、福建[5]等多个省正逐步推进次中心建设,国家层面也印发了《重点中心乡镇卫生院建设参考标准》,因此,开展次中心运行效率方面的研究具有重要现实意义。本研究在深入调研的基础上,通过数据包络分析方法(data envelopment analysis,DEA)分析四川省次中心的运行效率,总结四川省次中心建设的经验,为全国各地推动次中心建设发展提供借鉴和参考。
以2023年底四川省建成的302家次中心为研究对象,在文献研究及专家咨询的基础上,考虑数据可获得性及投入产出指标间的逻辑关系,将投入指标确定为卫生技术人员数、投入经费和实际开放床位数,产出指标选定为门急诊人次数、入院人数和医疗业务收入[6-7]
数据包络分析是研究多输入、多输出决策单元有效性的一种效率评价方法。常用的DEA模型有CCR模型和BCC模型,其中BCC模型用于规模报酬可变的情况[8]。次中心运行效率受卫生人员、技术水平、管理制度等因素的影响,规模报酬可变,故采用BCC对次中心进行静态分析,通过计算每个决策单元(简称“DMU”)的综合效率、技术效率和规模效率来判断DMU是否有效。如果效率值为1,为DMU有效;如果效率值<1,则为DMU无效。本文以四川省21个市州为决策单元,基于BCC模型评价2023年次中心的运行效率。
Malmquist指数通常用于测量不同时期决策单元全要素生产率及其分解情况[9]。全要素生产率(TFP)可分解为技术效率(EC)和技术进步(TC),分别反映决策单元组织管理水平和科学技术水平;技术效率可分解为纯技术效率(PEC)与规模效率(SEC),分别反映决策单元技术有效利用程度及经济要素配置水平。各指数大于1,表示效率提升;若小于或等于1,则表示效率降低或无变化。本文采用Malmquist指数模型分析2021—2023年302家次中心生产效率全方面变化情况。
本文采用Excel2016录入数据,运用DEAP2.1对302家次中心进行DEA运行效率测算及Malmquist指数分析。
分析显示,2023年四川省县域医疗卫生次中心的综合效率为0.884。21个市州中,9个DEA有效,运行效率达到最优状态,甘孜州DEA弱有效,其余11个DEA非有效。将次中心按照四川省五大经济区划分来看[10],成都平原经济区的成都、德阳、绵阳、眉山、资阳DEA有效,表明这五个市充分利用了医疗卫生资源,投入产出已经达到最优;川南经济区的4个市州DEA均无效,说明投入的资源没有得到充分利用;川东北经济区中广元和巴中DEA有效,南充、广安和达州DEA无效;攀西经济区中攀枝花DEA有效,凉山州的三个效率值均小于1,DEA无效;川西北生态区中的甘孜州DEA弱有效,阿坝州DEA有效。分解来看,21个市州中,纯技术效率等于1的有10个,为技术有效,表明医疗服务产出达到最大化;广安的纯技术效率最低,仅0.720,说明其医疗卫生资源未得到充分利用,技术水平有待提高。规模效率等于1的有9个市州,其医疗资源投入的规模报酬处于最佳状态,另外12个规模效率不等于1的市州皆为规模报酬递增。见表1
进一步对2023年四川省21个市州次中心效率的松弛变量进行分析,S1、S2、S3作为产出指标的松弛变量,用以衡量产出不足情况;而S4、S5、S6作为投入指标的松弛变量,则反映了投入冗余情况。当这两类松弛变量的数值均为0时,表明要素投入与产出均达到合理状态,即实现了DEA有效[11]。在产出方面,在门急诊人次方面存在产出不足现象的遂宁、乐山、自贡、宜宾、泸州、内江、广安、达州这8个市中,入院人数指标产出不足的仅广安市;乐山、雅安、自贡等9个市州在医疗业务收入方面存在产出不足。在投入方面,卫技人员数和投入经费无冗余情况;遂宁、乐山、宜宾、达州这4个市在床位数的配置上出现了投入冗余的情况。
全要素生产率指数是动态效率,反映了四川省次中心投入对产出增长的贡献。对四川省次中心的投入和产出数据进行分析,得到Malmquist生产率及其分解变化情况,2021—2023年次中心平均全要素生产率为1.014,表明四川省次中心全要素生产率年均提升1.4%。另外,全要素生产率大于1的次中心共有167家,占总数的55.3%。
分解来看,技术效率和纯技术效率在2022—2023有所下降,但下降幅度较小,平均值仍然大于1,说明次中心管理水平有所下降,如果不加以重视,可能会引发后续运行效率低下的问题。技术进步指数虽在2022—2023上升14.4%,但均值仍然小于1,可见,次中心技术水平仍有待提升。另外,技术进步指数与全要素生产率变动趋势最为接近,说明四川省次中心全要素生产效率主要受技术进步变动的影响。规模效率表现出上升趋势,说明四川省各次中心规模效益较好,资金使用效率较高。见表2
以次中心为决策单元,分市州统计结果显示:2021—2023年四川省县域医疗卫生次中心全要素生产率整体提升。21个市州中有16个全要素生产率提高,5个全要素生产率下降,其中成都市全要素生产率最高,为1.089,南充市最低,为0.932。见表3
分解来看,技术效率≥1的有14个,技术进步≥1的有11个,纯技术效率≥1的有16个,规模效率≥1的有13个。其中,攀枝花市、德阳市、乐山市、雅安市、阿坝州和凉山州的技术效率、纯技术效率和规模效率均为>1,而技术进步小于1,说明其全要素生产效率的进一步提高主要受技术进步影响。见表3
从各市州全要素生产率提升的次中心占比看,广元市、眉山市和成都市全要素生产率提升的次中心占比较高,分别为85.71%、81.82%和80.56%;广安市和甘孜州全要素生产率提升的次中心提升占比较低,分别为25.00%和28.57%。见表3
本文采取两种决策单元从动静两个角度分析次中心运行效率。以市州为决策单元观察次中心2023年整体效率,具有全局观。分析显示,四川省21个市州次中心综合效率为0.884,与张怡青等[12]学者研究得出我国基层医疗卫生机构综合效率均值0.774相比较高,这可能与次中心推进落实“县招乡用”或“县聘乡用”、与上级医院签署支持次中心专科(科室)建设协议等“强基层”政策有关。另外,次中心在投入经费和卫技人员上皆无冗余现象,遂宁、乐山、宜宾和达州这4个市在床位资源利用上尚有一定的优化空间。
以次中心为决策单元主要观察每个次中心运行效率变动,分别以时间和市州来统计Malmquist指数,样本量大,结果稳定可信。Malmquist模型结果显示,次中心全要素生产效率提高了1.4%,而许心蕊等人[13]的研究指出基层医疗卫生资源配置全要素生产率总体呈下降趋势,说明四川省次中心在疫情防控期间,虽然承担了大量防控任务,但其管理效能达到了整体进步水平。此外,广元市、眉山市和成都市等12个市州全要素生产率提升的次中心占比超过50%。表明这些地区通过次中心建设,让更多偏远农村地区的居民就近能看上病,享受到县级医院的医疗服务,更快促进基层医疗卫生体系的完善。
因此,要积极推动“优质服务基层行”、“基层临床特色科室建设”[14]等“强基层”政策,促进次中心医疗服务内涵式发展,将次中心建设成县域片区医疗救治中心、急诊急救中心、人才培训中心、技术指导中心和公共卫生示范中心等“五大中心”。同时,县域医疗次中心建设是紧密型县域医共体建设的重要突破口[15],要积极参与医联体建设,鼓励大医院的医生在次中心多点执业,支持优秀的全科医生和管理人员进入基层,促进医疗资源纵向流动,通过政策协同联动共同推动次中心运行效率进一步提升,实现县域医疗服务体系的高质量发展。
通过对次中心的静态效率分析,可以发现四川省次中心运行效率存在地区差异。成都平原经济区内的DEA有效市州占比5/8,为全省5个经济区中最高,这可能是由于经济发达地区的居民健康素养水平相对更高,在良好经济实力的支持下,更能主动参与自我健康管理,对卫生服务的利用程度更高。此外,经济条件较好的地区政府对卫生事业关注度更高[16],政策倾斜力度更大,次中心“强基层”措施集中发力效果更明显。因此,卫生行政部门要以各地经济发展水平、人口、疾病谱等情况为导向制定科学的区域卫生规划,协调地区间的差异[17]。对于条件较差、能力相对较弱的次中心,政府要实施优惠政策,引导优质医疗资源向这些地方集聚,还要从发展规划、学科建设等方面给予帮扶,协助次中心打造特色科室,建设区域特色品牌。对于基础条件较好、能力较强的次中心,扩大其业务范围和规模,提高其服务质量,保证一般常见病、慢性病均能在基层医治,盘活存量资源的同时分担上级医疗机构部分职能任务,完善基层医疗卫生网络体系,形成有序就医格局。
按年份和市州统计的动态分析结果皆表明技术进步是影响全要素生产率进一步提高的主要因素,这一发现与既往研究相吻合[18]。究其原因,可以发现尽管近几年次中心在硬件设备设施上有所增强,但仍未能满足居民对高质量医疗服务的需求,致使医疗服务产出不足,进而影响运行效率。此外,乡镇卫生院面临着一系列挑战,如存在执业环境不佳、职业发展路径不明晰和薪酬待遇提升有限等,这些问题无疑削弱了医务人员的工作积极性与职业满意度。再加上三级医院的虹吸效应,卫生技术骨干人才流失现象显著,这直接导致了医疗技术水平的相对低下。
因此,技术进步的实现,首先需要为卫生技术人员设立教育培训专项资金[19],鼓励基层卫生人员通过对口帮扶、到三甲医院进修等方式参加培训和继续教育,着重提升其知识更新速度和临床技能水平;其次应赋予次中心用人自主权和收支结余自主分配权[20],落实“两个允许”政策;最后要不断完善人才引进和人才激励机制,让人才资源“招得来、融得进、留得住、用得上”,逐步缓解次中心高素质、高水平人才缺乏的状态,以提高技术利用程度及服务水平,推动新技术和新策略的落地实施。另一方面,要加强信息化建设,赋能次中心医疗活力。相关部门应依据次中心功能定位及需求,在升级信息系统等方面予以支持,保证信息系统等硬件条件能辅助疾病监测与筛查,及时发现居民健康异动,并给出健康指导和改善策略,提高次中心的诊疗效率和服务效能。
  • 2023年四川省县域医疗卫生次中心建设项目监测与验收(0701-234011130073)
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2024年第51卷第23期
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doi: 10.20043/j.cnki.MPM.202407072
  • 接收时间:2024-07-06
  • 首发时间:2026-03-18
  • 出版时间:2024-12-10
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  • 收稿日期:2024-07-06
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2023年四川省县域医疗卫生次中心建设项目监测与验收(0701-234011130073)
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    1.成都中医药大学管理学院/健康四川研究院,四川 成都 611137
    2.自贡市第四人民医院
    3.成都医学院第二附属医院·核工业416医院
    4.西南民族大学

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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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