Article(id=1241676529541895134, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241676522256388920, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202405451, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1716480000000, receivedDateStr=2024-05-24, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773968353877, onlineDateStr=2026-03-20, pubDate=1731168000000, pubDateStr=2024-11-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773968353877, onlineIssueDateStr=2026-03-20, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773968353877, creator=13701087609, updateTime=1773968353877, updator=13701087609, issue=Issue{id=1241676522256388920, tenantId=1146029695717560320, journalId=1227665162245664772, year='2024', volume='51', issue='21', pageStart='3841', pageEnd='4032', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773968352140, creator=13701087609, updateTime=1773968629818, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241677686985249701, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241676522256388920, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241677686985249702, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241676522256388920, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=3941, endPage=3947, ext={EN=ArticleExt(id=1241676530598859771, articleId=1241676529541895134, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=The spatiotemporal distribution of quality medical resources and its effects on maternal and child health in the context of healthy China, columnId=1228016567846367388, journalTitle=Modern Preventive Medicine, columnName=Health Policy and Management, runingTitle=null, highlight=null, articleAbstract=
Objective

To provide a reference for the expansion and balanced distribution of quality medical resources, thereby promoting maternal and child health.

Methods

This study utilized panel data from 31 provinces, cities, and autonomous regions from 2012 to 2021. The Moran I index and Getas-Ord G* index were employed to analyze the spatiotemporal characteristics and hotspot distributions of quality medical resources. The Grossman health production function was used to explore the effects of quality medical resources on maternal and child health.

Results

From 2012 to 2021, the overall quality of medical resources in China showed an upward trend, with the number of tertiary hospitals increasing from 1 624 to 3 275, increasing by 101.66%.The Moran I indices for the years 2012, 2017, and 2021 were 0.292, 0.286, and 0.264, respectively, indicating a declining trend in the spatial autocorrelation of quality medical resources. For every additional tertiary hospital per 10 000 square kilometers, the infant mortality rate decreased by approximately 2.73‰, and the maternal mortality rate decreased by about 0.25 per 100 000.

Conclusion

The overall trend of quality medical resources in China is upward, with the eastern region experiencing the highest increase in quality medical resources, while the western region shows the greatest percentage increase. A significant“East-Central-West” hierarchical differentiation pattern exists, characterized by a spatial clustering distribution, where the eastern region is high, the central region is relatively high, and the western region is low. The effects of quality medical resources on maternal and child health are significant, negatively impacting both infant and maternal mortality rates.

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目的

为推进优质医疗资源扩容和均衡布局,促进妇幼健康提供参考。

方法

本研究采用2012—2021年31个省市自治区面板数据,使用Moran I指数以及Getis-Ord G*指数分析优质医疗资源时间空间特征及冷热点分布,以Grossman健康生产函数为基础探究优质医疗资源的妇幼健康效应。

结果

2012—2021年,我国优质医疗资源总体呈上升趋势,三级医院数由1 624家增加至3 275家,增幅为101.66%;2012、2017和2021年的Moran I指数分别为0.292、0.286、0.264,优质医疗资源的空间自相关性呈下降趋势;每万平方公里三级医院数增加1家,婴儿死亡率约降低2.73‰,孕产妇死亡率约降低0.25/10万。

结论

我国优质医疗资源总体呈上升趋势,东部优质医疗资源增量最多,西部优质医疗资源增幅最大;优质医疗资源“东-中-西”阶梯式分异格局显著且在空间上呈聚集性分布,整体呈现“东部高、中部较高、西部低”的特征;优质医疗资源的妇幼健康效应显著且负向影响婴儿死亡率、孕产妇死亡率。

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郭红霞,E-mail:
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甘明玉(1999—),女,硕士,初级统计师,研究方向:卫生政策管理与研究、医院管理

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甘明玉(1999—),女,硕士,初级统计师,研究方向:卫生政策管理与研究、医院管理

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注:基于自然资源部标准地图服务系统审图号GS(2023)2756号的标准底图制作,底图边界无修改。

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注:基于自然资源部标准地图服务系统审图号GS(2023)2756号的标准底图制作,底图边界无修改。

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注:基于自然资源部标准地图服务系统审图号GS(2023)2756号的标准底图制作,底图边界无修改。

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注:基于自然资源部标准地图服务系统审图号GS(2023)2756号的标准底图制作,底图边界无修改。

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Variable definition and statistical description

, figureFileSmall=null, figureFileBig=null, tableContent=
变量类型变量变量定义均值标准差
因变量婴儿死亡率婴儿出生后不满周岁人数同出生人数的比率(‰)5.683.59
核心解释变量孕产妇死亡率每十万例活产中孕产妇的死亡数(/10万)15.6017.97
优质医疗资源各省市自治区每万平方公里三级医院数量(个/万平方公里)9.2815.98
控制变量政府医疗卫生支出政府医疗卫生支出的对数15.060.72
人均地区生产总值人均地区生产总值的对数10.860.44
城乡居民人均可支配收入城乡居民人均可支配收入的对数10.050.41
建成区绿化覆盖率城市建成区的绿化覆盖面积占建成区的百分比(%)35.070.04
养老保险覆盖率年末各省市自治区参加养老保险人数与年末常住人口的比例(%)63.381.00
), ArticleFig(id=1241821867657462572, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676529541895134, language=CN, label=表1, caption=

变量定义及统计描述

, figureFileSmall=null, figureFileBig=null, tableContent=
变量类型变量变量定义均值标准差
因变量婴儿死亡率婴儿出生后不满周岁人数同出生人数的比率(‰)5.683.59
核心解释变量孕产妇死亡率每十万例活产中孕产妇的死亡数(/10万)15.6017.97
优质医疗资源各省市自治区每万平方公里三级医院数量(个/万平方公里)9.2815.98
控制变量政府医疗卫生支出政府医疗卫生支出的对数15.060.72
人均地区生产总值人均地区生产总值的对数10.860.44
城乡居民人均可支配收入城乡居民人均可支配收入的对数10.050.41
建成区绿化覆盖率城市建成区的绿化覆盖面积占建成区的百分比(%)35.070.04
养老保险覆盖率年末各省市自治区参加养老保险人数与年末常住人口的比例(%)63.381.00
), ArticleFig(id=1241821867774903095, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676529541895134, language=EN, label=Table 2, caption=

Impact of high-quality medical resources on maternal and child health

, figureFileSmall=null, figureFileBig=null, tableContent=
变量因变量
婴儿死亡率(‰)孕产妇死亡率(/10万)
(1)(2)(3)(4)
优质医疗资源(个/万平方公里)-6.14***(1.24)-2.73**(1.39)-0.43**(0.13)-0.25*(0.12)
政府医疗卫生支出120.50(37.51)-0.52(3.53)
人均地区生产总值-25.25(81.48)-4.89(7.67)
城乡居民人均可支配收入-239.89***(94.65)-10.64*(8.91)
建成区绿化覆盖率(%)-0.62**(0.32)0.04(0.03)
养老保险覆盖率(%)0.13(0.11)-0.008(0.01)
省份固定效应控制控制控制控制
样本量310310310310
R240.4950.0185.5689.72
), ArticleFig(id=1241821867896537916, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676529541895134, language=CN, label=表2, caption=

优质医疗资源对妇幼健康的影响

, figureFileSmall=null, figureFileBig=null, tableContent=
变量因变量
婴儿死亡率(‰)孕产妇死亡率(/10万)
(1)(2)(3)(4)
优质医疗资源(个/万平方公里)-6.14***(1.24)-2.73**(1.39)-0.43**(0.13)-0.25*(0.12)
政府医疗卫生支出120.50(37.51)-0.52(3.53)
人均地区生产总值-25.25(81.48)-4.89(7.67)
城乡居民人均可支配收入-239.89***(94.65)-10.64*(8.91)
建成区绿化覆盖率(%)-0.62**(0.32)0.04(0.03)
养老保险覆盖率(%)0.13(0.11)-0.008(0.01)
省份固定效应控制控制控制控制
样本量310310310310
R240.4950.0185.5689.72
), ArticleFig(id=1241821868030755652, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676529541895134, language=EN, label=Table 3, caption=

Impact of high-quality medical resources on maternal and child health: robustness test

, figureFileSmall=null, figureFileBig=null, tableContent=
变量因变量:婴儿死亡率(‰)
(1)(2)(3)(4)
优质医疗资源(个/万平方公里)-5.94***(1.27)-2.23**(1.42)-5.53***(0.284)-2.50**(0.47)
政府医疗卫生支出85.40(37.64)-0.18(0.87)
人均地区生产总值-61.22(80.36)5.48(1.77)
城乡居民人均可支配收入-119.39(92.80)-8.58***(2.09)
建成区绿化覆盖率(%)-0.64**(0.32)-0.12(0.06)
养老保险覆盖率(%)0.17(0.10)-0.04(0.02)
省份固定效应控制控制控制控制
观测值310310279279
R249.3550.0170.0890.11
), ArticleFig(id=1241821868181750602, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676529541895134, language=CN, label=表3, caption=

优质医疗资源对妇幼健康的影响——稳健性检验

, figureFileSmall=null, figureFileBig=null, tableContent=
变量因变量:婴儿死亡率(‰)
(1)(2)(3)(4)
优质医疗资源(个/万平方公里)-5.94***(1.27)-2.23**(1.42)-5.53***(0.284)-2.50**(0.47)
政府医疗卫生支出85.40(37.64)-0.18(0.87)
人均地区生产总值-61.22(80.36)5.48(1.77)
城乡居民人均可支配收入-119.39(92.80)-8.58***(2.09)
建成区绿化覆盖率(%)-0.64**(0.32)-0.12(0.06)
养老保险覆盖率(%)0.17(0.10)-0.04(0.02)
省份固定效应控制控制控制控制
观测值310310279279
R249.3550.0170.0890.11
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健康中国背景下我国优质医疗资源的时空分布及妇幼健康效应
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甘明玉 , 郭红霞
现代预防医学 | 卫生政策与管理 2024,51(21): 3941-3947
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现代预防医学 | 卫生政策与管理 2024, 51(21): 3941-3947
健康中国背景下我国优质医疗资源的时空分布及妇幼健康效应
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甘明玉, 郭红霞
作者信息
  • 深圳市宝安区妇幼保健院,广东 深圳 518102
  • 甘明玉(1999—),女,硕士,初级统计师,研究方向:卫生政策管理与研究、医院管理

通讯作者:

郭红霞,E-mail:
The spatiotemporal distribution of quality medical resources and its effects on maternal and child health in the context of healthy China
Ming-yu GAN, Hong-xia GUO
Affiliations
  • Shenzhen Bao’an District Maternal and Child Health Hospital, Shenzhen, Guangdong 518102, China
出版时间: 2024-11-10 doi: 10.20043/j.cnki.MPM.202405451
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目的

为推进优质医疗资源扩容和均衡布局,促进妇幼健康提供参考。

方法

本研究采用2012—2021年31个省市自治区面板数据,使用Moran I指数以及Getis-Ord G*指数分析优质医疗资源时间空间特征及冷热点分布,以Grossman健康生产函数为基础探究优质医疗资源的妇幼健康效应。

结果

2012—2021年,我国优质医疗资源总体呈上升趋势,三级医院数由1 624家增加至3 275家,增幅为101.66%;2012、2017和2021年的Moran I指数分别为0.292、0.286、0.264,优质医疗资源的空间自相关性呈下降趋势;每万平方公里三级医院数增加1家,婴儿死亡率约降低2.73‰,孕产妇死亡率约降低0.25/10万。

结论

我国优质医疗资源总体呈上升趋势,东部优质医疗资源增量最多,西部优质医疗资源增幅最大;优质医疗资源“东-中-西”阶梯式分异格局显著且在空间上呈聚集性分布,整体呈现“东部高、中部较高、西部低”的特征;优质医疗资源的妇幼健康效应显著且负向影响婴儿死亡率、孕产妇死亡率。

优质医疗资源  /  妇幼健康  /  健康中国
Objective

To provide a reference for the expansion and balanced distribution of quality medical resources, thereby promoting maternal and child health.

Methods

This study utilized panel data from 31 provinces, cities, and autonomous regions from 2012 to 2021. The Moran I index and Getas-Ord G* index were employed to analyze the spatiotemporal characteristics and hotspot distributions of quality medical resources. The Grossman health production function was used to explore the effects of quality medical resources on maternal and child health.

Results

From 2012 to 2021, the overall quality of medical resources in China showed an upward trend, with the number of tertiary hospitals increasing from 1 624 to 3 275, increasing by 101.66%.The Moran I indices for the years 2012, 2017, and 2021 were 0.292, 0.286, and 0.264, respectively, indicating a declining trend in the spatial autocorrelation of quality medical resources. For every additional tertiary hospital per 10 000 square kilometers, the infant mortality rate decreased by approximately 2.73‰, and the maternal mortality rate decreased by about 0.25 per 100 000.

Conclusion

The overall trend of quality medical resources in China is upward, with the eastern region experiencing the highest increase in quality medical resources, while the western region shows the greatest percentage increase. A significant“East-Central-West” hierarchical differentiation pattern exists, characterized by a spatial clustering distribution, where the eastern region is high, the central region is relatively high, and the western region is low. The effects of quality medical resources on maternal and child health are significant, negatively impacting both infant and maternal mortality rates.

Quality medical resources  /  Maternal and child health  /  Healthy China
甘明玉, 郭红霞. 健康中国背景下我国优质医疗资源的时空分布及妇幼健康效应. 现代预防医学, 2024 , 51 (21) : 3941 -3947 . DOI: 10.20043/j.cnki.MPM.202405451
Ming-yu GAN, Hong-xia GUO. The spatiotemporal distribution of quality medical resources and its effects on maternal and child health in the context of healthy China[J]. Modern Preventive Medicine, 2024 , 51 (21) : 3941 -3947 . DOI: 10.20043/j.cnki.MPM.202405451
党的二十大报告提出促进优质医疗资源扩容和区域均衡布局,这一切的出发点和落脚点是人民健康。优质医疗资源配置公平是居民享有优质医疗服务,推进健康中国建设的重要保障。当前,我国面临老龄化、少子化,妇女和儿童是医疗服务重点关注人群,妇幼健康是健康中国重要组成部分并被列入“健康中国2030”战略目标。因此,当前亟需把握优质医疗资源的时空分布和动态演进,探究优质医疗资源的妇幼健康效应。
国内外学者对于优质医疗资源时空分布特征研究较少。在探究医疗卫生资源配置时,常从以下三个角度出发:一是不同地区卫生资源配置现状[1-3];二是不同类型卫生资源配置现状,包括公共卫生人力资源、精神卫生资源等[4-6];三是不同类型医疗机构卫生资源配置现状,包括中医医疗机构、公共卫生机构等[7-9]。对于妇幼健康影响因素的研究,多数停留于总体医疗卫生支出与卫生资源配置的作用[10],缺乏以优质医疗资源为核心解释变量探究其妇幼健康效应。总体而言,目前对于我国优质医疗资源的时空特征及妇幼健康效应研究较少,本研究采用2012—2021年31个省市自治区面板数据,使用Moran I指数、Getis-Ord G*指数等分析优质医疗资源时间空间变化特征及冷热点分布,以Grossman健康生产函数为基础探究优质医疗资源的妇幼健康效应,旨在为推进优质医疗资源扩容和均衡布局、促进妇幼健康提供参考。
优质医疗资源是医疗卫生服务体系中高水平资源,包括高质量的医疗技术、精英医疗人才、先进医疗设备和系统等[11]。根据《医院分级管理办法》,三级医院是向多区域提供高水平医疗服务,执行高等教育和科研任务的医院。因此,三级医院数量可以在一定程度上代表优质医疗资源。另一方面,妇幼健康核心指标包括孕产妇死亡率、婴儿死亡率等[12],本研究采用上述两个重点核心指标综合反映妇幼健康水平。
数据来源于2013—2022年《中国统计年鉴》、2013—2017年《中国卫生和计划生育统计年鉴》、2018—2022年《中国卫生健康统计年鉴》;各省市自治区统计年鉴、卫生健康事业发展统计公报、国民经济和社会发展公报、妇女(儿童)发展状况统计监测报告等。
采用全局莫兰指数(Moran I)来度量中国优质医疗资源的分布格局,该指数能判断中国优质医疗资源在空间上的分布模式是否存在集聚、分散现象。Moran I计算公式为:
其中,n是观察值总数,Wi,j是要素ij之间空间权重矩阵,Zi是要素i的属性与其平均值()的偏差。S0是所有空间聚合权重的集合。
同时,对MoranI进行Z检验,以Z值和P值判断空间自相关的显著性和正负性。当Z值显著且为正时,代表存在正的空间自相关;当Z值显著且为负时,代表存在负的空间自相关。
其中E(I)为数学期望,Var(I)为方差。
利用探索性空间分析方法(exploratory spatial data analysis,ESDA)中的Moran I分析优质医疗资源在空间上的相似聚集或随机分散,采用热点分析(Getis-Ord G*)测度优质医疗资源分布的冷点和热点区。
其中Wi,j是空间权重矩阵,XiXj是要素ij的属性值。Getis-Ord G*值为正时,则为热点地区,否则为冷点地区。
Grossman认为健康是一种特殊的人力资本,可以消耗和投资。本研究从宏观角度出发,以Grossman健康生产函数为基础,探究我国优质医疗资源与妇幼健康的关系。
healthit=β1qmrit+β2mheit+β3gdpit+β4incomeit+β5greenit+ β6oldit+μi+εit
其中healthit为妇幼健康水平,用婴儿死亡率和孕产妇死亡率表示;qmr为优质医疗资源变量,用每万平方公里三级医院数表示;控制变量包括mhe(政府医疗卫生支出)、gdp(人均地区生产总值)、income(城乡居民人均可支配收入)、old(养老保险覆盖率)、green(建成区绿化覆盖率);εit是随机误差项,μi是个体异质性的截距项,即个体效应。
图1所示,2012—2021年我国优质医疗资源总体呈上升趋势,各省市自治区三级医院数由1 624家增加至3 275家,增幅为101.66%。如图2所示,2012—2021年,东、中、西部三级医院数增量分别为648、406和597家,增长率分别为85.60%、86.75%、149.62%,其中东部优质医疗资源增量最多,西部优质医疗资源增幅最大。2020—2021年,东、中部地区优质医疗资源增长率呈下降趋势,可能是突发公共卫生事件延缓了优质医疗资源扩容和布局。
为了更直观地反映优质医疗资源的空间分布特征,基于2012、2017和2021年各省市自治区三级医院数据,采用自然断点法将31个省市自治区分为低水平区、较低水平区、中等水平区、较高水平区、高水平区等5种类型,见图3。从数量变化看,(1)2012—2017年,35.48%的省份向高等级转移且全为递次转移,其中较高、高等水平区分别增加50.00%、66.67%,低、较低水平区分别减少28.57%、14.28%;(2)2017—2021年,58.06%的省份向高等级转移且全为递次转移,其中较高、高水平区显著增加,增幅分别为100.00%、60.00%,较低水平区大幅减少,降幅为58.33%,该结果显示我国优质医疗资源水平大幅提升。
从空间分布看,(1)2012—2017年,中等水平区趋于集中,形成渝-鄂-豫-皖-赣-闽半环中等水平区;较低、低水平区收缩,形成藏-新-青-甘-内蒙古连片分布区;(2)2017—2021年,中等水平区空间范围大幅扩张,形成川-陕-晋-冀-黔-桂-湘-赣环状连片分区;高水平区显著增加,形成京-津-辽、鲁-苏-浙2个连片区。见图345
2012、2017和2021年的Moran I指数分别为0.292、0.286、0.264,Moran I指数的正态统计量Z值的置信水平均大于0.05,结果显示省级优质医疗资源呈正的空间自相关。但Moran I指数减小,说明优质医疗资源的空间自相关性呈下降趋势。
全局Moran I指数仅能显示居民健康水平在整体上呈现显著的空间相关性,但未能体现局部空间信息。因此,采用冷点区、次冷点区、次热点区、热点区来反映局部空间变化。如图6所示,2021年我国优质医疗资源冷点区呈新-藏-青片状分布,热点区集中于豫-鄂-皖-苏地区。总体而言,中国优质医疗资源“东-中-西”阶梯式分异格局显著。
(1)因变量:妇幼健康水平。妇幼健康指标包括新生儿死亡率、5岁以下儿童死亡率、婴儿死亡率、孕产妇死亡率,上述指标也是我国妇幼健康核心监测指标。基于数据代表性,本研究选取婴儿死亡率和孕产妇死亡率综合反映妇幼健康,见表1
(2)核心解释变量:优质医疗资源。优质医疗资源是医疗卫生服务体系中高水平资源,三级医院数量可以在一定程度上代表优质医疗资源。考虑到优质医疗资源的均衡布局和医疗服务的可及性[13],因此用每万平方公里三级医院数表示优质医疗资源变量,见表1
(3)控制变量:结合研究目标并结合已有研究[14-15],本文从经济、环境、社会等因素选择控制变量,包括政府医疗卫生支出、人均地区生产总值、城乡居民人均可支配收入、建成区绿化覆盖率、养老保险覆盖率,见表1
表2报告了优质医疗资源影响妇幼健康的估计结果,其中列(1)和(3)为不加控制变量的估计结果,列(2)和(4)为加入控制变量的对比分析结果。从整个估计结果看,加入控制变量前后,优质医疗资源对婴儿死亡率影响均在5%的显著水平上显著,且各省市自治区每万平方公里三级医院数增加1家,婴儿死亡率约降低2.73‰。该结果与已有研究基本保持一致,即每100km2儿科医疗机构数与婴儿死亡率负相关[16];加入控制变量前后,优质医疗资源对孕产妇死亡率影响均在10%的显著水平上显著,且各省市自治区每万平方公里三级医院数增加1家,孕产妇死亡率约降低0.25/10万。相关研究结果表明,县级医院孕产妇死亡数高于省(市)级医院[17],更优质的医疗资源对应更低的孕产妇死亡率。
就控制变量而言,列(2)和(4)显示,其他可观测变量对于婴儿死亡率和孕产妇死亡率具有一定影响。城乡居民人均可支配收入与孕产妇死亡率、婴儿死亡率负相关,即个体或家庭收入与健康水平正相关[18]。建成区绿化率负向影响婴儿死亡率,健康环境正向影响居民健康结果[19]
考虑到变量自相关及解释变量和被解释变量的内生性、因果倒置等问题,以婴儿死亡率作为被解释变量,进行稳健性检验。一是参考陈强远、黄伊靖等[20-21]做法,解释变量、被解释变量、控制变量均进行1%缩尾处理。如表3列(1)和列(2)所示,优质医疗资源对婴儿死亡率的作用始终通过了5%的显著性检验,结果稳健。二是调整解释变量滞后阶数进行验证,通常来讲前期解释变量会对婴儿死亡率产生持续影响,对各解释变量取滞后一期放入模型重新验证优质医疗资源对婴儿死亡率的影响。如表3列(3)和列(4)所示,核心解释变量的显著性未发生本质性改变,表明估计结果稳健。
2012—2021年,我国三级医院数由1 624家增加至3 275家,优质医疗资源总量呈上升趋势,增幅为101.66%。其中2018年,我国优质医疗资源总量增长率为8.89%,在十年间达到一个小峰值,这与国家政策密切关联。2018年,国家卫健委出台《关于印发全面提升县级医院综合能力工作方案(2018—2020年)的通知》,通过推动县级医院达到三级医院的服务能力要求,缩小城乡医疗服务资源的差距。我国优质医疗资源虽持续增长,但仍存在总量不足、结构不合理的问题,而我国城乡二元制结构使得城乡医疗服务、医疗资源、医疗技术差异愈加凸显,这种差异性最终表现为城乡居民的健康不公平[22]。当前,需加快推动优质医疗资源向县域下沉,兜牢基层医疗卫生服务网底,通过城乡“传帮带式”对口支援,组团式帮扶乡村振兴重点县,推动人才和技术下沉,提高县域医疗服务能力。
2021年,我国优质医疗资源的Moran I指数为0.264,省级优质医疗资源分布在空间上呈正相关,且优质医疗资源高水平区集中分布于长三角地区、珠三角地区、京津冀地区,“东-中-西”阶梯式分异格局显著。我国优质医疗资源分布格局与区域经济聚集效应密切关联。经济的快速增长会加速中高端人力资本的积累,相关研究也表明人口从中部、西部流向东部[23]。医疗人才本质上仍是一种优质医疗资源,特大、超大城市的“虹吸效应”则会加剧人力资源流向大型医疗机构,这就导致了医疗的马太效应—优质医疗资源愈加呈倒三角分布,甚至部分大型医疗机构规模冗余。在医疗高质量发展背景下,亟需解决医疗资源配置的“供给侧失衡”,医疗需回归公益价值的本质,从规模扩张转向提质增效,实现精细化管理的“小而美”。
本文结果显示,优质医疗资源负向影响婴儿死亡率及孕产妇死亡率,每万平方公里三级医院数增加1家,婴儿死亡率约减少2.73‰,孕产妇死亡率约减少0.25/10万。我国婴儿死亡率、孕产妇死亡率逐年下降,但截至2021年全国各省市自治区孕产妇死亡率高位前三名分别是西藏(45.50/10万)、青海(22.39/10万)、新疆(16.05/10万),三者的显著特点为地广人稀,以每万平方千里三级医院数作为评价指标,优质医疗资源分布极不均衡且居民医疗服务可及性较低。因此,以西藏、青海、新疆为代表的西部地区,需整合有限的优质医疗资源,以市为单位组建医疗健康服务集团,可成立专项妇幼健康专业团队,并根据孕产妇需求让有限医疗人力资源在集团内医院流动,合理调配;此外,以区域人口、地理分布、特色病种为依据在西部地区建设国家区域医疗中心,重点集中于提升当地医疗机构的医疗服务能力,变“输血”为“造血”,提升人民群众就医获得感。
本研究从地理服务的可及性探究了我国优质医疗资源区域上分布不均衡,在西部地区医疗资源扩容和均衡布局的同时,也不能“矫枉过正”,忽视人口对超大型城市优质医疗资源配置的导向作用。我国流动人口聚集于超大型城市且以青年劳动力为主,相对生育需求较强。在人口高质量发展背景下,近年来羊水栓塞、胎儿畸形、先天疾病、围生期疾病等不良妊娠结局却高发[24]。超大型城市集中了我国最丰富的优质医疗资源,但在区域分布上集中于城市中心区。以深圳市为例,其中心城区有全市60%的三级医院,却仅占全市40%的人口。因此,超大型城市(如北京、上海、天津等)需均衡中心城区与外围区域的优质医疗资源分布情况,对于远离城市中心区的郊区和工业区,有计划地建设区域危重孕产妇、危重新生儿中心,提高妇女儿童急危重症的救治能力。
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2024年第51卷第21期
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doi: 10.20043/j.cnki.MPM.202405451
  • 接收时间:2024-05-24
  • 首发时间:2026-03-20
  • 出版时间:2024-11-10
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  • 收稿日期:2024-05-24
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    深圳市宝安区妇幼保健院,广东 深圳 518102

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2种不同金属材料的力学参数

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Percentage of
total species (%)

Genus
种数
Number of
species
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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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