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Article(id=1240722577291792990, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240722566957027366, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202503202, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1741795200000, receivedDateStr=2025-03-13, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773740913937, onlineDateStr=2026-03-17, pubDate=1760025600000, pubDateStr=2025-10-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773740913937, onlineIssueDateStr=2026-03-17, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773740913937, creator=13701087609, updateTime=1773740913937, updator=13701087609, issue=Issue{id=1240722566957027366, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='19', pageStart='3457', pageEnd='3648', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=0, createTime=1773740911472, creator=13701087609, updateTime=1773740981732, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1240722861736906836, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240722566957027366, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1240722861736906837, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240722566957027366, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=3585, endPage=3589, ext={EN=ArticleExt(id=1240722577627337332, articleId=1240722577291792990, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Mechanisms influencing fairness in public health physician resource allocation in China: An fsQCA configuration perspective, columnId=1228016567846367388, journalTitle=Modern Preventive Medicine, columnName=Health Policy and Management, runingTitle=null, highlight=null, articleAbstract=

Objective To analyze the fairness and impact mechanisms of the allocation of public health physician resources in China. Methods The fairness of public health physician resource allocation in 31 provinces across the country was set as the outcome variable, and 7 indicators were selected from the government, socio-economic and individual levels as conditional variables, and a fuzzy set qualitative comparative analysis (fsQCA) was performed. Results There were large differences in the allocation of public health physician resources in 31 provinces in China. Single factors cannot constitute a necessary condition to affect the fair allocation of public health physician resources. There were 10 paths that affect the fair allocation of public health physician resources, of which 2 paths had high fairness configurations, with an overall consistency of 0.97 and an overall coverage of 0.61. There were 8 paths in low fairness configurations, with an overall consistency of 0.96 and an overall coverage of 0.83. Conclusion Population aggregation is the basic premise for determining the fair allocation of public health physician resources. Financial support and residents’ income are key guarantees to support the fair allocation of public health physician resources. Medical insurance and basic public health service subsidies are complementary support for promoting the fair allocation of public health physician resources. Multi-factor coupling is a systematic mechanism for realizing the fair allocation of public health physician resources.

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目的 分析我国公共卫生医师资源配置公平性及影响机制。方法 将全国31个省级行政区的公共卫生医师资源配置公平性作为结果变量，并从政府、社会经济及个人层面选取7个指标作为条件变量，进行模糊集定性比较分析（fuzzy set qualitative comparative analysis，fsQCA）。结果 我国31个省级行政区公共卫生医师资源配置存在较大差异；单因素均不能构成影响公共卫生医师资源公平配置的的必要条件；影响公共卫生医师资源公平配置的路径共有10条，其中，高公平性组态有2条路径，总体一致性为0.97，总体覆盖度为0.61；低公平性组态共有8条路径，总体一致性为0.96，总体覆盖度为0.83。结论 人口集聚度是决定公共卫生医师资源公平配置基础性前提，财政支持与居民收入是支撑公共卫生医师资源公平配置的关键性保障，医疗保障与基本公共卫生服务补助是促进公共卫生医师资源公平配置的补充性支撑，多因素耦合是实现公共卫生医师资源公平配置的系统性机制。

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张晓云，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=NGKJCRLt7HeSd+Cn4j7mjg==, magXml=ymSecmjR+QGvJKUD05NVRw==, pdfUrl=null, pdf=dRzMzoG7JYS4VZNrM98Eyw==, pdfFileSize=542957, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=luFskAyjygQeK2ZtUduvCw==, mapNumber=null, authorCompany=null, fund=null, authors=

张晓云（1994—），女，硕士，助理研究员，研究方向：卫生管理与政策研究

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张晓云（1994—），女，硕士，助理研究员，研究方向：卫生管理与政策研究

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张晓云（1994—），女，硕士，助理研究员，研究方向：卫生管理与政策研究

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departmentName=null, remark=苏州市吴中区疾病预防控制中心，江苏 苏州 215127)])])], keywords=[Keyword(id=1240933502003237602, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722577291792990, language=EN, orderNo=1, keyword=Public health physician), Keyword(id=1240933502124872423, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722577291792990, language=EN, orderNo=2, keyword=Fairness of resource allocation), Keyword(id=1240933502233924334, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722577291792990, language=EN, orderNo=3, keyword=Influencing mechanisms), Keyword(id=1240933502351364855, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722577291792990, language=EN, orderNo=4, keyword=FsQCA configuration perspective), Keyword(id=1240933502439445247, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722577291792990, language=CN, orderNo=1, keyword=公共卫生医师), 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Chinese Journal of Health Statistics, 2016, 33(3): 463-465.(In Chinese), articleTitle=Analysis of equalization of allocation of basic public health service resources based on concentration index and Thiel Index, refAbstract=null)], funds=[Fund(id=1240933503727096669, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722577291792990, awardId=WZYW2024018, language=CN, fundingSource=2024年度苏州市吴中区科技计划项目（医疗卫生领域）(WZYW2024018), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1240933501025964704, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722577291792990, xref=null, ext=[AuthorCompanyExt(id=1240933501034353313, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722577291792990, companyId=1240933501025964704, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Suzhou Wuzhong District Center for Disease Control and Prevention, Suzhou, Jiangsu 215127, China), AuthorCompanyExt(id=1240933501038547619, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722577291792990, companyId=1240933501025964704, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=苏州市吴中区疾病预防控制中心，江苏 苏州 215127)])], figs=[ArticleFig(id=1240933503005676331, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722577291792990, language=EN, label=Table 1, caption=

Calibration of outcome variables and conditional variables

, figureFileSmall=null, figureFileBig=null, tableContent=
变量名称指标描述完全隶属交叉点完全不隶属
Y公共卫生医师资源密度指数23.403.901.11
X1地方政府医疗卫生支出（亿元）1 698.01635.61160.94
X2人均基本医疗保险基金支出（元）6 229.871 593.021 174.18
X3基本公共卫生服务补助资金（元）962 804.40332 304.0045 276.00
X4人口聚集度15.881.900.04
X5人均GDP（元）184 069.4070 923.0048 644.80
X6人均工资收入（元）48 231.5217 111.9013 114.20
X7人均医疗保健支出（元）3 762.502 017.301 114.34
), ArticleFig(id=1240933503106339637, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722577291792990, language=CN, label=表1, caption=

结果变量与条件变量校准

, figureFileSmall=null, figureFileBig=null, tableContent=
变量名称指标描述完全隶属交叉点完全不隶属
Y公共卫生医师资源密度指数23.403.901.11
X1地方政府医疗卫生支出（亿元）1 698.01635.61160.94
X2人均基本医疗保险基金支出（元）6 229.871 593.021 174.18
X3基本公共卫生服务补助资金（元）962 804.40332 304.0045 276.00
X4人口聚集度15.881.900.04
X5人均GDP（元）184 069.4070 923.0048 644.80
X6人均工资收入（元）48 231.5217 111.9013 114.20
X7人均医疗保健支出（元）3 762.502 017.301 114.34
), ArticleFig(id=1240933503232168765, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722577291792990, language=EN, label=Table 2, caption=

Results of necessary condition analysis

, figureFileSmall=null, figureFileBig=null, tableContent=
条件变量前因条件高公平性（Y）低公平性（-Y）
一致性覆盖度一致性覆盖度
X1高地方政府医疗卫生支出0.7710.7270.5810.687
～X1低地方政府医疗卫生支出0.6680.5600.7690.808
X2高人均基本医疗保险基金支出0.7500.7970.5360.715
～X2低人均基本医疗保险基金支出0.7320.5570.8480.810
X3高基本公共卫生服务补助资金0.7510.6980.6190.721
～X3低基本公共卫生服务补助资金0.7000.5930.7410.789
X4高人口聚集度0.8770.9440.5000.675
～X4低人口聚集度0.6980.5270.9580.907
X5高人均GDP0.8400.8030.5520.662
～X5低人均GDP0.6470.5350.8360.868
X6高人均工资收入0.8080.8480.4910.646
～X6低人均工资收入0.6630.5090.8850.853
X7高人均医疗保健支出0.8280.7400.6650.745
～X7低人均医疗保健支出0.7150.6300.7680.849
), ArticleFig(id=1240933503353803590, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722577291792990, language=CN, label=表2, caption=

必要条件分析结果

, figureFileSmall=null, figureFileBig=null, tableContent=
条件变量前因条件高公平性（Y）低公平性（-Y）
一致性覆盖度一致性覆盖度
X1高地方政府医疗卫生支出0.7710.7270.5810.687
～X1低地方政府医疗卫生支出0.6680.5600.7690.808
X2高人均基本医疗保险基金支出0.7500.7970.5360.715
～X2低人均基本医疗保险基金支出0.7320.5570.8480.810
X3高基本公共卫生服务补助资金0.7510.6980.6190.721
～X3低基本公共卫生服务补助资金0.7000.5930.7410.789
X4高人口聚集度0.8770.9440.5000.675
～X4低人口聚集度0.6980.5270.9580.907
X5高人均GDP0.8400.8030.5520.662
～X5低人均GDP0.6470.5350.8360.868
X6高人均工资收入0.8080.8480.4910.646
～X6低人均工资收入0.6630.5090.8850.853
X7高人均医疗保健支出0.8280.7400.6650.745
～X7低人均医疗保健支出0.7150.6300.7680.849
), ArticleFig(id=1240933503450272588, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722577291792990, language=EN, label=Table 3, caption=

High/low fairness configuration of public health physician resource allocation

, figureFileSmall=null, figureFileBig=null, tableContent=
条件组态高公平性组态（Y）低公平性组态（-Y）
H1H2L1L2L3L4L5L6L7L8
X1:地方政府医疗卫生支出●○○○▲▲▲△○
X2:人均基本医疗保险基金支出▲●△△△△△▲▲
X3:基本公共卫生服务补助△▲△△△▲▲▲▲△
X4:人口聚集度●▲○○○○○○
X5:人均GDP●▲△△△○○▲
X6:人均工资收入●●○○○○▲▲▲
X7:人均医疗保健支出●△△▲●●▲
符合条件省级行政区上海、天津、北京、北京、重庆上海、天津、北京、北京、重庆西藏、吉林、青海、甘肃、黑龙江、 新疆、贵州西藏、甘肃、山西、贵州吉林、宁夏云南、四川、广西四川、陕西内蒙古河北辽宁
一致性0.970.980.980.991.00.980.990.990.980.98
原始覆盖度0.450.440.650.590.460.470.440.320.240.30
总体一致性0.970.96
总体覆盖度0.610.83
), ArticleFig(id=1240933503567713110, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722577291792990, language=CN, label=表3, caption=

公共卫生医师资源配置高/低公平性组态

, figureFileSmall=null, figureFileBig=null, tableContent=
条件组态高公平性组态（Y）低公平性组态（-Y）
H1H2L1L2L3L4L5L6L7L8
X1:地方政府医疗卫生支出●○○○▲▲▲△○
X2:人均基本医疗保险基金支出▲●△△△△△▲▲
X3:基本公共卫生服务补助△▲△△△▲▲▲▲△
X4:人口聚集度●▲○○○○○○
X5:人均GDP●▲△△△○○▲
X6:人均工资收入●●○○○○▲▲▲
X7:人均医疗保健支出●△△▲●●▲
符合条件省级行政区上海、天津、北京、北京、重庆上海、天津、北京、北京、重庆西藏、吉林、青海、甘肃、黑龙江、 新疆、贵州西藏、甘肃、山西、贵州吉林、宁夏云南、四川、广西四川、陕西内蒙古河北辽宁
一致性0.970.980.980.991.00.980.990.990.980.98
原始覆盖度0.450.440.650.590.460.470.440.320.240.30
总体一致性0.970.96
总体覆盖度0.610.83
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我国公共卫生医师资源配置公平性的影响机制研究——基于fsQCA组态视角
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张晓云 , 孙亚婧
现代预防医学 | 卫生政策与管理 2025,52(19): 3585-3589
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现代预防医学 | 卫生政策与管理 2025, 52(19): 3585-3589
我国公共卫生医师资源配置公平性的影响机制研究——基于fsQCA组态视角
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张晓云 , 孙亚婧
作者信息
  • 苏州市吴中区疾病预防控制中心，江苏 苏州 215127

    • 张晓云（1994—），女，硕士，助理研究员，研究方向：卫生管理与政策研究

通讯作者:

张晓云，E-mail:
Mechanisms influencing fairness in public health physician resource allocation in China: An fsQCA configuration perspective
Xiao-yun ZHANG , Ya-jing SUN
Affiliations
  • Suzhou Wuzhong District Center for Disease Control and Prevention, Suzhou, Jiangsu 215127, China
出版时间: 2025-10-10 doi: 10.20043/j.cnki.MPM.202503202
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摘要
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目的 分析我国公共卫生医师资源配置公平性及影响机制。方法 将全国31个省级行政区的公共卫生医师资源配置公平性作为结果变量，并从政府、社会经济及个人层面选取7个指标作为条件变量，进行模糊集定性比较分析（fuzzy set qualitative comparative analysis，fsQCA）。结果 我国31个省级行政区公共卫生医师资源配置存在较大差异；单因素均不能构成影响公共卫生医师资源公平配置的的必要条件；影响公共卫生医师资源公平配置的路径共有10条，其中，高公平性组态有2条路径，总体一致性为0.97，总体覆盖度为0.61；低公平性组态共有8条路径，总体一致性为0.96，总体覆盖度为0.83。结论 人口集聚度是决定公共卫生医师资源公平配置基础性前提，财政支持与居民收入是支撑公共卫生医师资源公平配置的关键性保障，医疗保障与基本公共卫生服务补助是促进公共卫生医师资源公平配置的补充性支撑，多因素耦合是实现公共卫生医师资源公平配置的系统性机制。

公共卫生医师  /  资源配置公平性  /  影响机制  /  fsQCA组态视角

Objective To analyze the fairness and impact mechanisms of the allocation of public health physician resources in China. Methods The fairness of public health physician resource allocation in 31 provinces across the country was set as the outcome variable, and 7 indicators were selected from the government, socio-economic and individual levels as conditional variables, and a fuzzy set qualitative comparative analysis (fsQCA) was performed. Results There were large differences in the allocation of public health physician resources in 31 provinces in China. Single factors cannot constitute a necessary condition to affect the fair allocation of public health physician resources. There were 10 paths that affect the fair allocation of public health physician resources, of which 2 paths had high fairness configurations, with an overall consistency of 0.97 and an overall coverage of 0.61. There were 8 paths in low fairness configurations, with an overall consistency of 0.96 and an overall coverage of 0.83. Conclusion Population aggregation is the basic premise for determining the fair allocation of public health physician resources. Financial support and residents’ income are key guarantees to support the fair allocation of public health physician resources. Medical insurance and basic public health service subsidies are complementary support for promoting the fair allocation of public health physician resources. Multi-factor coupling is a systematic mechanism for realizing the fair allocation of public health physician resources.

Public health physician  /  Fairness of resource allocation  /  Influencing mechanisms  /  FsQCA configuration perspective
张晓云, 孙亚婧. 我国公共卫生医师资源配置公平性的影响机制研究——基于fsQCA组态视角. 现代预防医学, 2025 , 52 (19) : 3585 -3589 . DOI: 10.20043/j.cnki.MPM.202503202
Xiao-yun ZHANG, Ya-jing SUN. Mechanisms influencing fairness in public health physician resource allocation in China: An fsQCA configuration perspective[J]. Modern Preventive Medicine, 2025 , 52 (19) : 3585 -3589 . DOI: 10.20043/j.cnki.MPM.202503202
正文
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公共卫生医师是公共卫生体系的核心要素和能动资源，其均衡配置是推进健康中国建设的关键环节。“十四五”以来，多项国家政策明确要求加快公共卫生体系建设、推动资源均衡布局和优化人才结构。然而，当前我国公共卫生医师资源配置存在总量不足、队伍不稳、区域（尤其是中西部）和城乡分布不均等问题[1]。现有研究多聚焦于不同层级公共卫生资源配置公平性[2-3]、省级公共卫生医师配置公平性现状分析[4]，缺乏对全国公卫医师资源配置公平性影响机制的探讨。因此，本研究将基于全国31个省级行政区数据，运用模糊集定性比较分析（fuzzy set qualitative comparative analysis，fsQCA）方法，探究影响公共卫生医师资源公平配置的机制，以期为优化资源配置和人才布局提供决策依据。
1　资料与方法
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1.1　资料来源
本研究对象为全国31个省级行政区的公共卫生医师资源，数据来源为2023年《中国卫生健康统计年鉴》、2023年《中国统计年鉴》以及国家统计局官方网站。
1.2　研究方法
本研究运用fsQCA方法，探究影响国内公共卫生医师资源配置公平性的多重并发机制，揭示不同条件组态（因素组合）的作用路径及其导致的公平性差异，进而提出优化资源配置的策略。
1.3　指标选择
1.3.1　结果变量
本研究参考相关研究[5]将公共卫生医师资源密度指数作为结果变量，并将我国31个省级行政区（除港澳台）的公共卫生医师数量作为代理变量。
1.3.2　条件变量
当前有学者基于fsQCA组态视角对我国的全科医师、公共卫生人力资源、基层医疗卫生资源及我国整体卫生人力资源的配置等进行了分析，本研究参考汪晓芳[6]、吴爽[5]、陆瑞钊[7]等既往相关研究中条件变量的设置，从政府、社会经济及个人层面选取地方政府医疗卫生支出、人均基本医疗保险基金支出、基本公共卫生服务补助资金、人口聚集度和人均GDP、人均工资收入和人均医疗保健支出七个指标作为条件变量。
1.4　统计学方法
本研究利用Excel 2010进行数据录入与整理，运用fsQCA 3.0软件进行数据校准、必要条件与组态条件分析。
2　结果
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2.1　数据校准
本研究采用直接校准法将2022年原始案例的条件变量和结果变量校准为模糊集，将95%、50%、5%分别作为变量的完全隶属、交叉点和完全不隶属的3个校准点[8]，校准后的集合隶属度为0～1，同时，为避免校准过程中由于隶属度等于0.50而造成的数据的丢失，将隶属度0.50统一加0.001。见表1。
2.2　必要条件分析
必要条件分析结果显示，根据必要条件一致性判断标准[9]，在高公平组中，各变量条件的一致性均小于0.9，表明这七个条件变量均不能单独成为影响公共卫生医师资源配置高公平性的必要条件，即公共卫生医师资源高公平性配置是多种因素综合作用的结果，需将变量条件全部纳入fsQCA的分析中，探究影响公共卫生医师资源配置公平性的多种组态。在低公平组中，低变量条件人口集聚度一致性>0.9，表明低人口集聚度可能是影响公共卫生医师医师资源配置公平性的必要条件，其他变量均为非必要条件。见表2。
2.3　前因条件组态分析
2.3.1　高公平性组态分析
高公平性组态中，有二条路径的一致性均大于0.8，符合组态分析中一致性要求标准[10]，其中，总体一致性为0.97，表示所有满足这二个解的条件组态案例中，有97%的案例为高公平性配置；整体覆盖度为0.61，表示这二个条件组态可以解释61%的高公平性配置案例，对于结果变量的产生具有较强的解释力度。
本研究识别出实现高公平性配置的两条核心路径：（1）H1：在人口密集、社会经济实力强、居民收入高且注重医疗消费的地区，即使存在政府对基本公共卫生服务支持不足的短板，只要强化基本医疗保障力度（必要条件），仍可达成公共卫生医师资源的高公平性配置；（2）H2：在财政支持力度大、基本医疗保障充足、居民收入高的地区，若同时满足政府对基本公共卫生服务扶持力度大、人口密集、社会经济实力强三项条件，则无论居民是否注重医疗保健消费支出，均可实现公共卫生医师资源的高公平性配置。见表3。
2.3.2　低公平性组态分析
低公平性组态中，有八条路径的一致性均大于0.8，符合组态分析中一致性要求标准[10]，其中，总体一致性为0.96，表示所有满足这八个解的条件组态案例中，有96%的案例为低公平性配置状态；整体覆盖度为0.83，表示这八个条件组态可以解释83%的低公平性案例，对于结果变量的产生具有较强的解释力度。
本研究将导致公共卫生医师资源低公平性配置的八条核心路径，归纳为四类模式：（1）财政弱+人口稀核心型 (L1/L2/L3)：当财政支持不足和人口稀疏作为核心条件，并伴随居民收入低、政府医疗保障/基本公卫服务补助弱、社会经济差或居民医疗消费意愿不足时，必然导致低公平性；（2）人口稀+收入低抵抗型(L4/L5)：以人口稀疏和居民收入低为核心，即使加强财政支持与基本公卫服务补助 (L4)或提升居民医疗消费意识 (L5)，在政府医疗保障水平低及社会经济不发达的阻力下，公平性仍难以改善；（3）意识强+经济弱失效型 (L6/L7)：核心矛盾在于居民医疗消费意识强但社会经济实力弱，此时即使存在高居民收入、强财政支持/基本公卫服务补助 (L6)或强医疗保障/公卫支持/居民收入 (L7)，也会因政府医疗保障弱 (L6)或财政支持不足 (L7)导致公平性依然低下；（4）国家支持缺位型 (L8)：核心条件是财政支持不足、人口稀疏且缺乏基本公卫服务补助支持，即使医疗保障水平高、社会经济实力雄厚、居民收入高、医疗消费意愿强等其它有利条件，也无法避免低公平性配置状态。见表3。
3　讨论
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3.1　讨论
基于组态分析，2022年我国各省级行政区公共卫生医师资源配置呈现显著区域差异。上海、北京等东部发达省市呈现高公平性状态，西藏、青海等西部及东北地区则处于低公平性配置区间，该分布特征与李明阳[11]、何颖[12]等既有研究结论一致。针对当前公共卫生医师资源配置公平性影响机制研究不足的现状，本研究将依据fsQCA组态分析结果，从多维视角系统分析影响公共卫生医师资源配置公平性的作用机制。
3.1.1　人口集聚度是决定公共卫生医师资源公平配置基础性前提
人口集聚度作为重要的人口地理学特征，构成了公共卫生医师资源公平配置的基础层。组态分析表明，人口集聚度是公共卫生医师资源公平配置的基础性核心因素。高人口密度区域（如北京、上海）因公共卫生服务需求集聚效应，形成公共卫生医师资源高公平配置模式。
3.1.2　财政支持与居民收入是支撑公共卫生医师资源公平配置的关键性保障
财政支持与居民收入作为经济支撑系统，构成了公共卫生医师资源公平配置的保障层。组态分析表明，公共卫生医师资源配置公平性受财政支持与居民收入双重经济因素影响。财政投入作为关键资金来源，直接决定供给能力和分配方向。低投入地区（如组态L3的吉林省）因资金短缺导致岗位不足、设备落后，难以吸引和留存人才；高投入地区（如组态H2的江苏省）则形成资源集聚优势。同时，居民收入通过需求机制影响配置公平。低收入地区（如组态L4、L5的四川省）因健康意识薄弱、支付能力有限，公共卫生服务需求集中于政府基础项目，加剧财政压力并限制资源配置；而高收入地区（如江苏省）通过多元化需求促进资源均衡配置，形成高公平性状态。
3.1.3　医疗保障与基本公共卫生服务供给是促进公共卫生医师资源公平配置的补充性支撑
基本医疗保障与公共卫生服务供给作为政策调节层，对公共卫生医师资源公平配置起补充作用。基本医疗保障与基本公共卫生服务补助作为公共卫生服务体系中的两大政策工具，调节公共卫生医师资源公平配置问题[13]。组态分析表明，这两项政策工具通过资金分配机制影响资源配置效率。在医保覆盖与基金分配不均衡地区（如组态L7的河北省），因补助资金总量不足、使用效率偏低，导致公共卫生服务功能受限，资源配置水平低下；反之，健全的医疗保障体系与充足的公卫服务资金投入，能够通过优化服务供给结构促进资源合理配置。该调节机制通过平衡服务需求与供给能力，间接改善公共卫生医师资源配置公平性。
3.1.4　多因素耦合是实现公共卫生医师资源公平配置的系统性机制
多因素耦合作为多种因素的整合机制，构成了公共卫生医师资源公平配置的系统层。组态分析表明，财政投入、医疗保障、公卫服务资金、人口分布、经济水平、居民收入与医疗消费意识等要素通过耦合作用共同决定资源配置状态（如组态L8的辽宁省）。这些因素的交互效应形成复合调节机制，构成资源配置的系统性支撑框架。
3.2　建议
基于上述分析，实现公共医师资源均衡与公平配置作为一项系统性工程，本研究将多措并举，提出以下建议。
3.2.1　强化政策保障水平
首先，将慢性病全程管理、免疫规划等纳入医保目录，建立服务项目动态扩增与阶梯式报销制度。其次，各省级行政区按常住人口、财政能力及公卫水平制定补助标准，向重大公卫问题突出、医师资源薄弱地区（如藏青甘黔）倾斜。最后，依据公卫医师服务半径与密度设定岗位津贴，重点提升资源配置公平性较低省级行政区待遇。
3.2.2　构建经济支撑体系
第一，人均GDP落后省级行政区需提高公卫支出比例，中央以专项转移支付补缺，并设立区域医疗均衡基金（东部地区筹资），支持基层疾控标准化建设及跨区域医师薪酬补助。第二，实施医保个人缴费全额补贴、公卫服务报销比例上浮政策，设定艰苦地区公卫医师最低年薪，建立服务人口密度递减式津贴。第三，构建经济适配性/服务可及性/质量保障性三维考核体系，实行分级预警管理，运用区块链技术全程溯源资金。
3.2.3　优化资源配置路径
首先，依托15个国家级公卫中心（参考长三角/珠三角经验），建立“国家-省-市”三级框架；对藏青甘等资源薄弱地区实施“首席专家+青年骨干+基层人才”引进计划。其次，在边疆及偏远省级行政区试点“省级统筹、区域共享”编制制度，推行“县管乡用、乡聘村用”机制；允许副高以上医师省内多点执业（基层服务时长挂钩继续教育）。最后，开发方言健康教育资源库，开展专家直播与基层视频宣传；在云贵川等地区部署AI公卫终端（含生物识别），100%实现健康档案查阅、疫苗提醒及传染病AI初筛功能。
基金
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  • 2024年度苏州市吴中区科技计划项目（医疗卫生领域）(WZYW2024018)
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2025年第52卷第19期
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doi: 10.20043/j.cnki.MPM.202503202
  • 接收时间：2025-03-13
  • 首发时间：2026-03-17
  • 出版时间：2025-10-10
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  • 收稿日期：2025-03-13
基金
2024年度苏州市吴中区科技计划项目（医疗卫生领域）(WZYW2024018)
作者信息
    苏州市吴中区疾病预防控制中心，江苏 苏州 215127

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张晓云，E-mail:
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2种不同金属材料的力学参数
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多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
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