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Article(id=1228016569087886174, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1228016566646801206, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202504404, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1745251200000, receivedDateStr=2025-04-22, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1770711565515, onlineDateStr=2026-02-10, pubDate=1758729600000, pubDateStr=2025-09-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1770711565515, onlineIssueDateStr=2026-02-10, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1770711565515, creator=13701087609, updateTime=1770711565515, updator=13701087609, issue=Issue{id=1228016566646801206, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='18', pageStart='3265', pageEnd='3456', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1770711564932, creator=13701087609, updateTime=1770711815039, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1228017615784833769, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1228016566646801206, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1228017615784833770, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1228016566646801206, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=3366, endPage=3372, ext={EN=ArticleExt(id=1228016570627195772, articleId=1228016569087886174, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Study on the current situation of medical resource allocation based on spatial accessibility — taking the municipal district of a prefectural city in Yangtze River Delta as an example, columnId=1228016567846367388, journalTitle=Modern Preventive Medicine, columnName=Health Policy and Management, runingTitle=null, highlight=null, articleAbstract=
Objective

To evaluate the spatial accessibility of various types of healthcare institutions in an urban district of a prefecture-level city in the Yangtze River Delta, in order to provide a basis for optimizing healthcare service allocation.

Methods

This study obtained 2024 healthcare facility data and population data for each subdistrict (town) through secondary data collection, and gathered population spatial distribution data and road traffic data from public service platforms. The Two-Step Floating Catchment Area (2SFCA) method based on a Gaussian decay function was used to assess the accessibility levels of different healthcare institutions within the district.

Results

Within a 15-minute drive, 42.5% of demand points cannot access primary healthcare institutions and are classified as inaccessible areas. Comprehensive specialty healthcare institutions exhibit a clustered distribution in the southeastern region, indicating significant regional disparities in development. Dental service institutions demonstrate overall good accessibility; however, resource levels remain notably insufficient in the northwestern region. Accessibility to rehabilitation service institutions is relatively balanced overall, though areas requiring improvement still exist in the northwest.

Conclusion

The distribution pattern of medical institutions in city districts is “dense in urban areas and sparse in suburbs”, and the results of the accessibility of various types of medical institutions are different, so the results of this study can provide a reference for other cities to evaluate the spatial allocation of medical resources.

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目的

本研究旨在评估长三角某地级市市辖区各类医疗机构的空间可达性水平，为优化医疗资源配置提供依据。

方法

本研究通过二手收集得到2024年医疗机构数据和各街道（镇）人口数据，通过公开服务平台收集得到人口空间分布数据和道路交通数据。使用基于高斯衰减函数的两步移动搜索法评估市辖区内各类医疗资源的空间可达性水平。

结果

在15分钟车程内，42.5%的需求点无法到达基层医疗服务机构，属于不可达区域；综合性专科服务机构整体呈东南区域聚集分布，区域发展不均衡问题显著；口腔服务机构整体可达性表现良好，但西北部资源水平仍存在明显不足；康复服务机构可达性整体较为均衡，但西北部存在可达性待提升区域。

结论

市辖区医疗机构呈现“城区密集、郊区稀疏”的分布格局，且各类医疗机构空间可达性结果不同，本研究结果可为其他城市评估医疗资源空间配置提供参考。

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胡敏，E-mail:
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廖博玮（1999—），女，硕士在读，研究方向：卫生事业管理

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廖博玮（1999—），女，硕士在读，研究方向：卫生事业管理

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Progress in Geography, 2016, 35(5): 589-599.(In Chinese), articleTitle=Research progress of the two-step floating catchment area method and extensions, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1228016577497465237, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016569087886174, xref=null, ext=[AuthorCompanyExt(id=1228016577501659542, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016569087886174, companyId=1228016577497465237, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=School of Public Health, Fudan University, Shanghai 200032, China), AuthorCompanyExt(id=1228016577510048151, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016569087886174, companyId=1228016577497465237, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=复旦大学公共卫生学院，上海　200032)])], figs=[ArticleFig(id=1228016579707863589, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016569087886174, language=EN, label=Fig.1, caption=Map of administrative boundaries of the municipal district (Base map provided by Tianditu, approved by GS(2025)1508; original map content remains unaltered), figureFileSmall=cQjI+P6hl/uPY6taVlJ3Yg==, figureFileBig=kS35FZ1fdbS5u7P+tRnjKw==, tableContent=null), ArticleFig(id=1228016579800138282, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016569087886174, language=CN, label=图1, caption=市辖区行政边界图（天地图，审图号GS(2025)1508号，底图内容未经改动）, figureFileSmall=cQjI+P6hl/uPY6taVlJ3Yg==, figureFileBig=kS35FZ1fdbS5u7P+tRnjKw==, tableContent=null), ArticleFig(id=1228016580093739574, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016569087886174, language=EN, label=Fig.2, caption=Population grid map (500 m × 500 m) (Approved by GS(2025)1508), figureFileSmall=UC/2yUIHoP/TWSJ1pz8pLA==, figureFileBig=9UXtoXJW4E33zwBYzdtXcQ==, tableContent=null), ArticleFig(id=1228016580223763004, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016569087886174, language=CN, label=图2, caption=人口渔网图（500 m×500 m）（审图号GS(2025)1508号）, figureFileSmall=UC/2yUIHoP/TWSJ1pz8pLA==, figureFileBig=9UXtoXJW4E33zwBYzdtXcQ==, tableContent=null), ArticleFig(id=1228016580366369348, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016569087886174, language=EN, label=Fig.3, caption=Map of spacial accessibility scores to primary healthcare institutions for each demand point (approved by GS(2025)1508), figureFileSmall=/svmOSMOfHAPltVMuM//fw==, figureFileBig=aaZByvfI9eqlexmkFtJvsQ==, tableContent=null), ArticleFig(id=1228016580492198472, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016569087886174, language=CN, label=图3, caption=各需求点获取基层医疗服务机构的空间可达性得分图（审图号 GS(2025)1508号）, figureFileSmall=/svmOSMOfHAPltVMuM//fw==, figureFileBig=aaZByvfI9eqlexmkFtJvsQ==, tableContent=null), ArticleFig(id=1228016580609638991, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016569087886174, language=EN, label=Fig.4, caption=Map of spacial accessibility scores to comprehensive specialty healthcare institutions for each demand point (approved by GS(2025)1508), figureFileSmall=ET/WL/3iBj38Ttnh8EDobw==, figureFileBig=cTlizHrveb0NCudT1H3Riw==, tableContent=null), ArticleFig(id=1228016580739662425, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016569087886174, language=CN, label=图4, caption=各需求点获取综合性专科服务机构的空间可达性得分图（审图号 GS(2025)1508号）, figureFileSmall=ET/WL/3iBj38Ttnh8EDobw==, figureFileBig=cTlizHrveb0NCudT1H3Riw==, tableContent=null), ArticleFig(id=1228016580857102945, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016569087886174, language=EN, label=Fig.5, caption=Map of spacial accessibility scores to dental service institutions for each demand point (approved by GS(2025)1508), figureFileSmall=lbPNLvLHXOPVz+qSF51LPg==, figureFileBig=W9gJz+b3hrjJ23iYOyOYNg==, tableContent=null), ArticleFig(id=1228016580982932071, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016569087886174, language=CN, label=图5, caption=各需求点获取口腔服务机构的空间可达性得分图（审图号 GS(2025)1508号）, figureFileSmall=lbPNLvLHXOPVz+qSF51LPg==, figureFileBig=W9gJz+b3hrjJ23iYOyOYNg==, tableContent=null), ArticleFig(id=1228016581104566893, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016569087886174, language=EN, label=Fig.6, caption=Map of spacial accessibility scores to rehabilitation service institutions for each demand point (approved by GS(2025)1508), figureFileSmall=U5U5S2gjOEr3x7hhzYcZwA==, figureFileBig=lJTTKvRDfQ0CuXqvCg5b/w==, tableContent=null), ArticleFig(id=1228016581234590319, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016569087886174, language=CN, label=图6, caption=各需求点获取康复服务机构的空间可达性得分图（审图号 GS(2025)1508号）, figureFileSmall=U5U5S2gjOEr3x7hhzYcZwA==, figureFileBig=lJTTKvRDfQ0CuXqvCg5b/w==, tableContent=null), ArticleFig(id=1228016581356225143, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016569087886174, language=EN, label=Table 1, caption=

Population of each subdistrict (town) in 2024

, figureFileSmall=null, figureFileBig=null, tableContent=
街道（镇）名称户籍人口数流动人口数市内区外人口数总人口数
C街道211 832287 681160 784660 297
A街道79 736160 71388 160328 609
F街道139 888109 84163 277313 006
D街道107 055117 80672 134296 995
B街道90 295100 60641 072231 973
E街道79 650100 60650 548230 804
I镇74 07156 90220 451151 424
G街道48 61654 99631 034134 646
H镇44 74928 96113 84587 555
L镇15 8627 1992 57425 635
J镇13 6692 3701 16917 208
K镇11 7062 21144214 359
合计917 1291 029 892545 4902 492 511
), ArticleFig(id=1228016581456888441, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016569087886174, language=CN, label=表1, caption=

2024年各街道（镇）人口数量

, figureFileSmall=null, figureFileBig=null, tableContent=
街道（镇）名称户籍人口数流动人口数市内区外人口数总人口数
C街道211 832287 681160 784660 297
A街道79 736160 71388 160328 609
F街道139 888109 84163 277313 006
D街道107 055117 80672 134296 995
B街道90 295100 60641 072231 973
E街道79 650100 60650 548230 804
I镇74 07156 90220 451151 424
G街道48 61654 99631 034134 646
H镇44 74928 96113 84587 555
L镇15 8627 1992 57425 635
J镇13 6692 3701 16917 208
K镇11 7062 21144214 359
合计917 1291 029 892545 4902 492 511
), ArticleFig(id=1228016581607883391, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016569087886174, language=EN, label=Table 2, caption=

Distribution and indicator results of primary healthcare institutions in each subdistrict (town)

, figureFileSmall=null, figureFileBig=null, tableContent=
街道（镇）名称机构数量医师数量每万人基层医疗服务机构数每万人基层医师数
C街道602000.913.03
E街道251041.084.51
D街道231270.774.28
A街道231130.703.44
B街道221250.955.39
F街道221390.704.44
I镇201351.328.92
H镇13531.486.05
G街道10420.743.12
K镇563.484.18
L镇5331.9512.87
J镇4182.3210.46
合计232
), ArticleFig(id=1228016581712740996, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1228016569087886174, language=CN, label=表2, caption=

各街道（镇）基层医疗服务机构分布情况及相关指标结果

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C街道602000.913.03
E街道251041.084.51
D街道231270.774.28
A街道231130.703.44
B街道221250.955.39
F街道221390.704.44
I镇201351.328.92
H镇13531.486.05
G街道10420.743.12
K镇563.484.18
L镇5331.9512.87
J镇4182.3210.46
合计232
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Distribution and indicator results of comprehensive specialty healthcare institutions by subdistrict (town)

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F街道56043.48420.64
I镇22771.16160.97
E街道2930.7836.28
A街道28410.2396.05
C街道13210.0721.20
D街道11040.044.51
G街道160.040.26
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G街道160.040.26
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Distribution and indicator results of dental service institutions by subdistrict (town)

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所在街道
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D街道19600.642.02
A街道18990.553.01
F街道15570.481.82
E街道8540.352.34
I镇7310.462.05
B街道4110.170.47
G街道3110.220.82
H镇340.340.46
L镇240.781.56
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所在街道
（镇）名称		机构数量医师数量每万人口腔服务机构数每万人口腔医师数
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D街道19600.642.02
A街道18990.553.01
F街道15570.481.82
E街道8540.352.34
I镇7310.462.05
B街道4110.170.47
G街道3110.220.82
H镇340.340.46
L镇240.781.56
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Distribution and indicator results of rehabilitation service institutions by subdistrict (town)

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所在街道
（镇）名称		机构数量医师数量每万人康复机构数每万人康复医师数
E街道2500.092.17
C街道2240.030.36
G街道130.070.22
I镇120.070.13
B街道1290.041.25
F街道140.030.13
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C街道2240.030.36
G街道130.070.22
I镇120.070.13
B街道1290.041.25
F街道140.030.13
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基于空间可达性的医疗资源配置现状研究——以长三角某地级市市辖区为例
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廖博玮 , 胡敏 , 陈文
现代预防医学 | 卫生政策与管理 2025,52(18): 3366-3372
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现代预防医学 | 卫生政策与管理 2025, 52(18): 3366-3372
基于空间可达性的医疗资源配置现状研究——以长三角某地级市市辖区为例
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廖博玮, 胡敏 , 陈文
作者信息
  • 复旦大学公共卫生学院，上海　200032

    • 廖博玮（1999—），女，硕士在读，研究方向：卫生事业管理

通讯作者:

胡敏，E-mail:
Study on the current situation of medical resource allocation based on spatial accessibility — taking the municipal district of a prefectural city in Yangtze River Delta as an example
Bo-wei LIAO, Min HU , Wen CHEN
Affiliations
  • School of Public Health, Fudan University, Shanghai 200032, China
出版时间: 2025-09-25 doi: 10.20043/j.cnki.MPM.202504404
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摘要
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目的

本研究旨在评估长三角某地级市市辖区各类医疗机构的空间可达性水平，为优化医疗资源配置提供依据。

方法

本研究通过二手收集得到2024年医疗机构数据和各街道（镇）人口数据，通过公开服务平台收集得到人口空间分布数据和道路交通数据。使用基于高斯衰减函数的两步移动搜索法评估市辖区内各类医疗资源的空间可达性水平。

结果

在15分钟车程内，42.5%的需求点无法到达基层医疗服务机构，属于不可达区域；综合性专科服务机构整体呈东南区域聚集分布，区域发展不均衡问题显著；口腔服务机构整体可达性表现良好，但西北部资源水平仍存在明显不足；康复服务机构可达性整体较为均衡，但西北部存在可达性待提升区域。

结论

市辖区医疗机构呈现“城区密集、郊区稀疏”的分布格局，且各类医疗机构空间可达性结果不同，本研究结果可为其他城市评估医疗资源空间配置提供参考。

医疗资源配置  /  空间可达性  /  两步移动搜索法
Objective

To evaluate the spatial accessibility of various types of healthcare institutions in an urban district of a prefecture-level city in the Yangtze River Delta, in order to provide a basis for optimizing healthcare service allocation.

Methods

This study obtained 2024 healthcare facility data and population data for each subdistrict (town) through secondary data collection, and gathered population spatial distribution data and road traffic data from public service platforms. The Two-Step Floating Catchment Area (2SFCA) method based on a Gaussian decay function was used to assess the accessibility levels of different healthcare institutions within the district.

Results

Within a 15-minute drive, 42.5% of demand points cannot access primary healthcare institutions and are classified as inaccessible areas. Comprehensive specialty healthcare institutions exhibit a clustered distribution in the southeastern region, indicating significant regional disparities in development. Dental service institutions demonstrate overall good accessibility; however, resource levels remain notably insufficient in the northwestern region. Accessibility to rehabilitation service institutions is relatively balanced overall, though areas requiring improvement still exist in the northwest.

Conclusion

The distribution pattern of medical institutions in city districts is “dense in urban areas and sparse in suburbs”, and the results of the accessibility of various types of medical institutions are different, so the results of this study can provide a reference for other cities to evaluate the spatial allocation of medical resources.

Healthcare resource allocation  /  Spatial accessibility  /  Two-step Floating Catchment Area
廖博玮, 胡敏, 陈文. 基于空间可达性的医疗资源配置现状研究——以长三角某地级市市辖区为例. 现代预防医学, 2025 , 52 (18) : 3366 -3372 . DOI: 10.20043/j.cnki.MPM.202504404
Bo-wei LIAO, Min HU, Wen CHEN. Study on the current situation of medical resource allocation based on spatial accessibility — taking the municipal district of a prefectural city in Yangtze River Delta as an example[J]. Modern Preventive Medicine, 2025 , 52 (18) : 3366 -3372 . DOI: 10.20043/j.cnki.MPM.202504404
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2023年3月，国务院办公厅印发《关于进一步完善医疗卫生服务体系的意见》，提出应将保障人民健康放在优先发展的战略位置，促进优质医疗资源扩容和区域均衡布局，建设中国特色优质高效的医疗卫生服务体系。计划到2025年和2035年，将分别实现医疗资源配置更加优化、服务能力和公平性显著提升[1]。
当前，居民需求结构升级对医疗资源提出多元化、差异化的要求，而我国医疗资源配置仍存在结构性问题：首先，供给层级不均衡，“重高端、轻基层”“重综合、轻专科”的现象明显[2–4]；其次，部分专科服务资源配置失衡，如口腔床位利用率低[5]、康复服务供需错配严重[6-7]；最后，空间分布不均，城市中心与郊区存在“核心-边缘”（core-edge）差异，中心行政区资源高度集中，郊区则资源不足[8]。这一模式在新兴城市中尤为明显，面临资源总量不足与布局失衡的双重挑战[9]，尤其是近郊行政区，兼具中心衔接性与郊区属性，因城镇化推进、人口增长迅速，成为医疗资源优化配置的重点区域[10]。因此，以此类市辖区为研究对象优化资源配置，既可缓解中心区压力，也有助于提升地级市整体资源均衡性。
在此背景下，本研究以长三角某地级市市辖区作为研究对象。该区是撤县设区后的快速发展地区，常住人口超140万，城镇化率达74.6%。部分区域属于市中心的核心发展带，但整体面临资源总量不足、空间分布不均[11-12]，且服务结构失衡与供需错配等问题，具有典型性与代表性。本研究聚焦其医疗资源可达性，旨在揭示城市发展过程中的配置短板，为类似城市提供参考。
为精准反映不同类型医疗资源的服务职能，本研究将机构划分为基层医疗服务机构（以下简称为“基层机构”）、综合性专科服务机构（以下简称为“综合性机构”）和特定专科服务机构（如口腔、康复）。基层机构以常见病诊疗和慢性病管理为主[13]，综合性机构具备多学科诊疗能力，特定专科机构提供专业治疗服务。相较以往研究，本研究通过分类测算，有助于更清晰识别不同类型资源的空间可达性特征，为差异化配置与服务均衡提供依据。
1　资料与方法
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1.1　　研究区域
研究区域为长三角某地级市市辖区，按行政区划编码顺序，将该市辖区街道（镇）依次编号为A至L，见图1。
1.2　数据来源
1.2.1　二手数据收集
本研究使用2024年医疗机构数据和各街道（镇）人口数据。医疗机构数据包括机构名称、地址、所在街镇、类型、等级及医师数等；人口数据包括各街道（镇）户籍人口、流动人口和市内区外人口数量。
1.2.2　公开服务平台数据收集
为反映人口空间分布情况，研究使用WorldPop网站提供的2020年100 m分辨率开源人口分布栅格数据。利用 ArcGIS 10.8对数据进行预处理，并按2024年市辖区各街道（镇）总人口修正栅格数据，创建500 m×500 m渔网需求单元，见图2，得到共4 031个需求点，构建市辖区人口空间分布预测数据集。
为准确评估医疗资源可达性，本研究通过Open Street Map（OSM）开源地图平台获取该区域道路交通数据，利用 ArcGIS 10.8进行预处理，通过拓扑检查及人工核实修正人口数据和医疗资源位点错误，构建精准车行路网[14]。按《公路工程技术标准》，设置最大限速值，以评估各需求点至医疗机构的出行时间。在路径计算中，车辆可通行道路采用驾车方式，禁行路段采用步行方式，步行速度设为1.5 m/s（5.4 km/h）。
1.3　分析方法
本研究使用基于高斯函数的两步移动搜索法（Two-step Floating Catchment Area, 2SFCA）分析市辖区医疗资源空间可达性，具体步骤如下：
第一步，以500 m×500 m的渔网单元创建需求点i；计算各类别医疗机构j的地理坐标与其至各需求点间的出行距离，即OD（Origin-Destination）成本。以每家医疗机构j为搜索中心，设定服务半径d0，查找半径内的所有需求k，使用高斯距离衰减函数按人口加权求和，计算医疗资源供给点j的供需比Rj[15] 。
式中，用机构的医师数Sj表示医疗机构j的供给规模；用搜索范围内的人口数量Dk表示需求点的需求规模；G(dij)为高斯距离衰减函数，其中，dij为需求点与医疗机构间的实际距离，d0为设置的搜索半径。
本研究根据机构类型设置不同的服务半径d0。对于基层医疗机构参照“15分钟卫生服务圈”目标，以15分钟车程为半径。对于综合性和特定专科机构，由于面向全市辖区提供服务，则以OD成本最大值为服务半径。
第二步，以需求点i为中心，查找其半径d0范围内所有医疗机构j，在高斯衰减函数的基础上，对这些医疗资源供需比Rj加权求和，得到需求点i的可达性得分，数值越大，表示该需求点可达性程度越高[16]。
最后，使用自然断点法，根据“组内差异最小，组间差异最大”的原则将所有需求点可达性得分的连续值做离散化处理，得到五个断点，区分可达性水平，并在地图中使用不同颜色进行可视化呈现。红色、橙色、黄色、灰色、蓝色分别为可达性“好”、“较好”、“中等”、“较差”、“差”（即全域内可达性水平最高、次高、居中、次低、最低的需求点），其余若有空白区域，则代表该区域不在出行范围内，不纳入计算，可认为其不具有可达性。需特别指出，上述“好”、“较好”、“中等”、“较差”和“差”的描述仅反映区域内可达性的相对水平，不是区分可达性的绝对标准。
2　结果
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2.1　基本情况
2.1.1　人口情况
该市辖区2024年人口数量，如表1所示。一些毗邻该地级市市中心的街道（镇），如C、A、F、D街道，人口密度相对较高，而位于该市辖区西北的L、J、K镇的人口密度则相对较低。
2.1.2　基层医疗卫生服务机构
该市辖区共有232家基层机构。以各街道（镇）为单位，统计基层医疗服务机构数量、每万人基层医疗服务机构数、基层医师数和每万人基层医师数，如表2。综合来看，C、A、D等街道人口密度较高，而每万人资源量却相对较少，相反，I、H、K、L、J镇的人口密度低，但每万人资源量相对丰富，整体呈现“人口多但资源紧张”与“资源多但需求有限”并存的格局，亟需优化资源配置的供需匹配。
2.1.3　综合性专科服务机构
该市辖区共有14家综合性机构。根据每个街道（镇）分布的机构数量、医师总数以及相应人口数据，计算每万人综合性专科服务机构数和每万人综合性专科医师数，如表3所示。整体上，综合性专科服务资源高度集中在F街道等个别地区，市辖区西北部街道资源供需配比不足，需通过资源下沉以优化配置。
2.1.4　口腔服务机构
该市辖区共有112家口腔服务机构。根据每个街道（镇）分布的机构数量，医师总数以及相应的人口数据，计算得到每万人口腔服务机构数和每万人口腔医师数，见表4。总体来看，部分街道（镇）如F、E、B、G街道及H镇每万人口腔服务机构数不超过0.5家，资源供给不足，需结合人口和实际需求，引导口腔资源在区域间配置更加均衡。
2.1.5　康复服务机构
该市辖区共有8家康复服务机构。结合人口数据和康复机构的医师数，计算出每万人康复机构数和每万人康复医师数，如表5。总体来看，在人口较多的街道，康复资源与需求存在一定错配。在资源薄弱地区，此类服务可作为未来优化重点，需提升其供给能力，优化区域康复资源布局。
2.2　可达性结果
2.2.1　基层医疗服务机构
根据“15分钟医疗卫生服务圈”的要求，将出行半径设定为15分钟车程，由此计算出基层机构的可达性水平（图3）。
根据可达性得分图，从全域来看，在15分钟车程内，无法到达基层机构的需求点数为1 713个，属于不可达区域。这些区域主要集中在机构布点数量较少的街道（镇）交界处、主要地形为丘陵的街道（镇）、交通路网均较为稀疏或存在交通空白区域的街道（镇）。去除这些不可达区域后，全域内按可达性“好”、“较好”、“中等”、“较差”和“差”划分，各级别需求点数分别为4、78、214、581和1 441，占比分别为0.17%、3.36%、9.23%、25.06%和62.17%。
在每个街道（镇）内，发现街道（镇）的中心区域通常可达性水平“较好”，街道（镇）的边缘可达性“较差”，且大部分街道（镇）无可达性“好”的区域。街道（镇）中心区的服务可达性通常较优，而边缘区域明显处于可达性劣势，由此得出，现阶段基础医疗资源在空间分布上仍存在显著不均衡的问题。
2.2.2　综合性专科服务机构
对于综合性机构，本研究将对全部机构做可达性评价。由于此类型机构服务面向全区，故以在全区范围内搜索综合性机构的最大出行半径作为服务半径，得到各需求点获取综合性专科服务机构的可达性水平分布图（图4）。
在4 031个需求点中，可达性水平划分为“好”、“较好”、“中等”、“较差”、“差”的需求点数分别为1、1 235、1 729、652、414，所占比例分别为0.02%、30.64%、42.89%、16.17%和10.27%，可达性水平为“较好”和“中等”的需求点数占主导，仅在东南角的A街道的一个需求点的可达性得分可以达到可达性“好”水平。据此指出，综合性机构整体呈东南区域聚集分布，区域发展不均衡问题显著。
2.2.3　口腔服务机构
本研究认为口腔服务机构也面向全区提供服务，同理，得到各需求点获取口腔服务资源的可达性评价，见图5。在4 031个需求点中，可达性水平为“好”、“较好”、“中等”、“较差”和“差”的需求点数分别为1 495、1 420、666、369和81个，所占比例分别为37.09%、35.23%、16.52%、9.15%和2.01%，其中可达性水平“好”和“较好”需求点数量较多。综上，口腔服务机构整体可达性表现良好，但西北部资源水平仍存在明显不足。
2.2.4　康复服务机构
对于康复服务机构，本研究将对全部机构做可达性评价。同理可得到各需求点获取康复服务资源的可达性水平情况，见图6，从市辖区角度分析，在4 031个需求点中，可达性水平为“好”、“较好”、“中等”、“较差”和“差”的需求点数分别为516、1 671、1 100、556和188个，占所有需求点的比例分别为12.80%、41.45%、27.29%、13.79%、4.66%，可达性水平为“较好”和“中等”的需求点数量较多。与口腔服务机构类似，康复服务机构可达性整体较为均衡，“较好”与“中等”覆盖面广，但仍存在西北部区域“较差”的服务短板。
3　讨论
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研究发现，（1）市辖区医疗资源呈现“城区密集、郊区稀疏”的分布格局。中心区域居民通常可在较短时间内获得多类型医疗服务，边缘地区则同时面临基层服务不足、专科资源稀缺等多重可达性障碍。（2）不同类型医疗机构之间的可达性差异明显。基层机构在西北边缘区域及部分街道（镇）周边区域的可达性水平较差，存在较多不可达区域。综合性机构分布相对均衡，东南区域可达性较好。特定专科服务机构在西北区域可达性水平偏弱，存在提升空间。
针对研究发现的问题，提出以下优化建议：（1）建立空间导向型的医疗资源动态监测机制。将空间可达性水平作为新机构选址、资源下沉的参考指标，纳入区域卫生资源评估和规划体系，增强政策的科学性和前瞻性。（2）优先弥补基层医疗服务短板。落实“15分钟医疗服务圈”，明确各街道（镇）责任边界，优先保障边缘区域居民的首诊可达性；引入移动医疗、远程问诊等多元供给方式，提升薄弱区域服务能力，加强人员培训、设备升级，确保基本医疗服务质效的双重提升。（3）推动专科资源按类别合理布局。结合人口结构、地理特征与实际需求，在老龄化人口密度较高、交通不便区域优先布局康复机构；鼓励基层机构增设口腔、康复等专科科室，缓解高层级专科机构诊疗压力；通过医联体、推动医生多点执业等方式，扩大服务辐射范围，提升边缘地区的综合服务能力。
本研究亦存在一定局限性：（1）医疗资源供给仅以医师数衡量，未细化至医师结构，难以揭示不同类型医师配置对可达性的影响，未来可引入更精细的人员结构数据。（2）研究范围局限于市辖区内部，未考虑跨行政区就医行为，可能低估实际可达性水平，未来可引入跨区流动数据和空间交互模型，提升分析全面性。
尽管本研究存在一定的局限性，本研究所构建的分析框架具有较强通用性，可为其他快速城市化地区提供医疗资源可达性评估与优化的理论借鉴与实践指导。
文献
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2025年第52卷第18期
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doi: 10.20043/j.cnki.MPM.202504404
  • 接收时间：2025-04-22
  • 首发时间：2026-02-10
  • 出版时间：2025-09-25
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  • 收稿日期：2025-04-22
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    复旦大学公共卫生学院，上海　200032

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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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