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Article(id=1322607936472470271, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1322607837742747790, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202506035, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1748880000000, receivedDateStr=2025-06-03, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793263904922, onlineDateStr=2026-10-29, pubDate=1761321600000, pubDateStr=2025-10-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793263904922, onlineIssueDateStr=2026-10-29, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793263904922, creator=13701087609, updateTime=1793263904922, updator=13701087609, issue=Issue{id=1322607837742747790, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='20', pageStart='3649', pageEnd='3840', issueExtLink='null', onlineDate='null', pubDate='1761321600000', pubDateStr='2025-10-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793263881383, creator='13701087609', updateTime=1793264238791, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1322609336933794638, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1322607837742747790, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1322609336933794639, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1322607837742747790, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=3761, endPage=3766, ext={EN=ArticleExt(id=1322607936770265856, articleId=1322607936472470271, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Analysis on the Structural Change of Total Health Expenditure from 2009 to 2021 and Its Influencing Factors, Qinghai, columnId=1228016567846367388, journalTitle=Modern Preventive Medicine, columnName=Health Policy and Management, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze the evolution characteristics and influencing factors of total health expenditure structure in Qinghai Province from 2009 to 2021, and to provide reference for regional health policy optimization.

Methods

The data of total health expenditure and influencing factors of total health expenditure in Qinghai Province from 2009 to 2021 were selected. Based on the financing source method, the structural change degree analysis method was used to explore the dynamic changes of health financing structure, and the principal component regression model was used to identify the key influencing factors.

Results

From 2009 to 2021, the average annual growth rate of total health expenditure in Qinghai Province was 13.86%, the proportion of government health expenditure increased from 39.81% to 49.21%, the proportion of personal expenditure decreased from 30.04% to 22.09%, the overall structural change degree was 18.79%, and the financing balance was significantly improved. Principal component regression showed that population size (β=0.114), economic development (β=0.114), medical resource supply (β=0.113) and urbanization rate (β=0.112) were the main positive driving factors, while the proportion of personal expenditure (β=-0.091) was significantly inhibited.

Conclusion

The scale of health financing in Qinghai Province continues to expand, and the burden of residents is gradually reduced. However, it is necessary to optimize the structure of government investment, improve the efficiency of resource utilization, and optimize the structure of medical insurance payment.

, authors=Jin-peng WANG, Wen-jie BAI, Jian-xiu ZHANG, Ying-hua GUO, authorsList=Jin-peng WANG, Wen-jie BAI, Jian-xiu ZHANG, Ying-hua GUO, authorCompany=null, correspAuthors=Ying-hua GUO, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1322607940046017287, articleId=1322607936472470271, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=2009—2021青海省卫生总费用结构变动及其影响因素分析, columnId=1228016568014139551, journalTitle=现代预防医学, columnName=卫生政策与管理, runingTitle=null, highlight=null, articleAbstract=
目的

分析2009—2021年青海省卫生总费用结构演变特征及其影响因素，为区域卫生政策优化提供参考。

方法

选取2009—2021年青海省卫生总费用及卫生总费用影响因素指标数据，基于筹资来源法，采用结构变动度分析探究卫生筹资结构动态变化，运用主成分回归识别关键影响因素。

结果

2009—2021年青海省卫生总费用年均增长13.86%，政府卫生支出占比从39.81%升至49.21%，个人支出占比由30.04%降至22.09%，整体结构变动度18.79%，筹资均衡性显著提升；主成分回归显示，人口规模（β=0.114）、经济发展（β=0.114）、医疗资源供给（β=0.113）和城镇化率（β=0.112）为主要正向驱动因素，个人支出占比（β=-0.091）则呈显著抑制作用。

结论

青海省卫生筹资规模持续扩大，居民负担逐步减轻，但需优化政府投入结构、提升资源利用效率，并通过优化医保支付结构、强化资源配置协同性，平衡费用压力，以促进卫生事业可持续发展。

, authors=王金鹏, 白文洁, 张建秀, 郭映花, authorsList=王金鹏, 白文洁, 张建秀, 郭映花, authorCompany=null, correspAuthors=郭映花, authorNote=

王金鹏(2001—)，男，硕士在读，研究方向：卫生统计学

, correspAuthorsNote=
郭映花，E-mail:
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王金鹏(2001—)，男，硕士在读，研究方向：卫生统计学

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(In Chinese), articleTitle=Macroeconomic analysis of influencing factors of per capita health expenditure in China, refAbstract=null), Reference(id=1322607952331133791, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607936472470271, doi=null, pmid=null, pmcid=null, year=2025, volume=null, issue=7, pageStart=224, pageEnd=248, url=null, language=null, rfNumber=[21], rfOrder=39, authorNames=肖楠, 刘国恩, journalName=世界经济, refType=null, unstructuredReference=肖楠，刘国恩. 基层首诊政策对患者就医选择和医疗费用的影响 [J]. 世界经济, 2025, (7): 224-248., articleTitle=基层首诊政策对患者就医选择和医疗费用的影响, refAbstract=null), Reference(id=1322607952398242656, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607936472470271, doi=null, pmid=null, pmcid=null, year=2025, volume=null, issue=7, pageStart=224, pageEnd=248, url=null, language=null, rfNumber=[21], rfOrder=40, authorNames=Xiao N, Liu GE, journalName=The Journal of World Economy, refType=null, unstructuredReference=Xiao N, Liu GE. The impact of mandatory gatekeeping policy on hospital choices and medical expenditure [J]. The Journal of World Economy, 2025, (7): 224-248. (In Chinese), articleTitle=The impact of mandatory gatekeeping policy on hospital choices and medical expenditure, refAbstract=null)], funds=[Fund(id=1322607945628635958, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607936472470271, awardId=2024-wjzd-12, language=CN, fundingSource=2024年青海省卫生健康系统重点课题(2024-wjzd-12), fundOrder=null, country=null), Fund(id=1322607945695744823, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607936472470271, awardId=qddt-2511, language=CN, fundingSource=青海大学2025年研究生导师创新团队建设项目(qddt-2511), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1322607940499002120, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607936472470271, xref=null, ext=[AuthorCompanyExt(id=1322607940507390729, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607936472470271, companyId=1322607940499002120, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Department of Public Health, Qinghai University, Xining, Qinghai 810001, China), AuthorCompanyExt(id=1322607940519973642, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607936472470271, companyId=1322607940499002120, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=青海大学医学部公共卫生系，青海　西宁　810001)])], figs=[ArticleFig(id=1322607944412287784, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607936472470271, language=EN, label=Table 1, caption=

Indicators of influencing factors of total health expenditure

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指标指标编号指标单位
经济系统X1人均国内生产总值元
X2个人卫生支出占卫生总费用比重%
人口系统X3年末总人口数万人
X4城镇化率%
X5死亡率%
X6出生率%
卫生系统供给X7医疗机构床位数张
X8卫生技术人员人
X9医院诊疗人次万人
需求X10医院入院人次万人
X11医院病床使用率%
), ArticleFig(id=1322607944475202345, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607936472470271, language=CN, label=表1, caption=

卫生总费用影响因素指标

, figureFileSmall=null, figureFileBig=null, tableContent=
指标指标编号指标单位
经济系统X1人均国内生产总值元
X2个人卫生支出占卫生总费用比重%
人口系统X3年末总人口数万人
X4城镇化率%
X5死亡率%
X6出生率%
卫生系统供给X7医疗机构床位数张
X8卫生技术人员人
X9医院诊疗人次万人
需求X10医院入院人次万人
X11医院病床使用率%
), ArticleFig(id=1322607944550699818, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607936472470271, language=EN, label=Table 2, caption=

The composition and proportion of health expenditure in Qinghai Province in 2009,2011-2021

, figureFileSmall=null, figureFileBig=null, tableContent=
年份（年）总费用（亿元）政府支出（亿元）社会支出（亿元）个人支出（亿元）
数值构成（%）数值构成（%）数值构成（%）
200977.9931.0539.8123.5130.1423.4330.04
2011109.2747.6943.6431.2828.6330.3027.73
2012142.4961.7243.3242.2629.6638.5027.02
2013162.5478.1048.0543.0626.4941.3725.45
2014175.3187.2549.7746.6726.6241.3823.60
2015215.82107.0849.6257.1726.4951.5823.90
2016239.75111.8346.6461.9525.8465.9827.52
2017270.08127.3547.1572.5026.8470.2326.00
2018308.08141.6145.9788.2228.6478.2525.40
2019355.16158.0044.49108.7330.6188.4324.90
2020382.11186.4748.80103.7627.1591.8824.05
2021388.07190.9649.21111.3828.7085.7322.09
), ArticleFig(id=1322607944638780203, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607936472470271, language=CN, label=表2, caption=

青海省2009，2011—2021年卫生费用构成及构成比

, figureFileSmall=null, figureFileBig=null, tableContent=
年份（年）总费用（亿元）政府支出（亿元）社会支出（亿元）个人支出（亿元）
数值构成（%）数值构成（%）数值构成（%）
200977.9931.0539.8123.5130.1423.4330.04
2011109.2747.6943.6431.2828.6330.3027.73
2012142.4961.7243.3242.2629.6638.5027.02
2013162.5478.1048.0543.0626.4941.3725.45
2014175.3187.2549.7746.6726.6241.3823.60
2015215.82107.0849.6257.1726.4951.5823.90
2016239.75111.8346.6461.9525.8465.9827.52
2017270.08127.3547.1572.5026.8470.2326.00
2018308.08141.6145.9788.2228.6478.2525.40
2019355.16158.0044.49108.7330.6188.4324.90
2020382.11186.4748.80103.7627.1591.8824.05
2021388.07190.9649.21111.3828.7085.7322.09
), ArticleFig(id=1322607944760415020, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607936472470271, language=EN, label=Table 3, caption=

Changes in the structure of total health expenditure in Qinghai Province from 2009 to 2021

, figureFileSmall=null, figureFileBig=null, tableContent=
年份（年）政府卫生支出社会卫生支出个人卫生支出结构变动度（%）
结构变动值(%)结构变动贡献率(%)结构变动值(%)结构变动贡献率(%)结构变动值(%)结构变动贡献率(%)
2009—20123.5150.76-0.487.05-3.0243.817.01
2013—2016-1.4134.06-0.6515.823.6250.135.68
2017—20212.0626.261.8623.74-3.9150.007.83
2009—20219.4050.00-1.447.68-7.9542.3218.79
), ArticleFig(id=1322607944844301101, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607936472470271, language=CN, label=表3, caption=

青海省2009—2021年卫生总费用结构变动情况

, figureFileSmall=null, figureFileBig=null, tableContent=
年份（年）政府卫生支出社会卫生支出个人卫生支出结构变动度（%）
结构变动值(%)结构变动贡献率(%)结构变动值(%)结构变动贡献率(%)结构变动值(%)结构变动贡献率(%)
2009—20123.5150.76-0.487.05-3.0243.817.01
2013—2016-1.4134.06-0.6515.823.6250.135.68
2017—20212.0626.261.8623.74-3.9150.007.83
2009—20219.4050.00-1.447.68-7.9542.3218.79
), ArticleFig(id=1322607944919798574, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607936472470271, language=EN, label=Table 4, caption=

Explains the total variance

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成分初始特征值
总计方差百分比（%）累积方差贡献率（%）
18.63978.53378.533
21.28211.65090.183
30.6656.05096.233
40.2502.27698.509
50.0690.63099.139
60.0570.51499.653
70.0250.22699.879
80.0090.08599.964
90.0030.02599.988
100.0010.00999.997
11<0.0010.003100.000
), ArticleFig(id=1322607944999490351, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607936472470271, language=CN, label=表4, caption=

解释的总方差

, figureFileSmall=null, figureFileBig=null, tableContent=
成分初始特征值
总计方差百分比（%）累积方差贡献率（%）
18.63978.53378.533
21.28211.65090.183
30.6656.05096.233
40.2502.27698.509
50.0690.63099.139
60.0570.51499.653
70.0250.22699.879
80.0090.08599.964
90.0030.02599.988
100.0010.00999.997
11<0.0010.003100.000
), ArticleFig(id=1322607945108542256, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607936472470271, language=EN, label=Table 5, caption=

Principal component load matrix and coefficient matrix

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标准化后的自变量载荷矩阵系数矩阵
Z1Z2Z1Z2
Z(X1)0.9780.1690.167-0.048
Z(X2)-0.792-0.071-0.107-0.004
Z(X3)0.9780.1540.161-0.038
Z(X4)0.992-0.0530.0730.098
Z(X5)-0.7340.6040.188-0.440
Z(X6)0.985-0.0310.0820.083
Z(X7)0.9660.1770.169-0.054
Z(X8)0.9120.3470.237-0.168
Z(X9)0.9080.3950.257-0.200
Z(X10)-0.7190.2950.057-0.238
Z(X11)0.707-0.679-0.2230.487
), ArticleFig(id=1322607945171456817, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607936472470271, language=CN, label=表5, caption=

主成分载荷矩阵及系数矩阵

, figureFileSmall=null, figureFileBig=null, tableContent=
标准化后的自变量载荷矩阵系数矩阵
Z1Z2Z1Z2
Z(X1)0.9780.1690.167-0.048
Z(X2)-0.792-0.071-0.107-0.004
Z(X3)0.9780.1540.161-0.038
Z(X4)0.992-0.0530.0730.098
Z(X5)-0.7340.6040.188-0.440
Z(X6)0.985-0.0310.0820.083
Z(X7)0.9660.1770.169-0.054
Z(X8)0.9120.3470.237-0.168
Z(X9)0.9080.3950.257-0.200
Z(X10)-0.7190.2950.057-0.238
Z(X11)0.707-0.679-0.2230.487
), ArticleFig(id=1322607945242759986, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607936472470271, language=EN, label=Table 6, caption=

Coefficients of regression model

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模型Β（95% CI） βP
常量<0.0010.061-1.000
Z10.833（0.690~0.977）0.0640.833<0.001
Z20.519（0.375~0.662）0.0640.519<0.001
), ArticleFig(id=1322607945339228979, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607936472470271, language=CN, label=表6, caption=

回归模型系数

, figureFileSmall=null, figureFileBig=null, tableContent=
模型Β（95% CI） βP
常量<0.0010.061-1.000
Z10.833（0.690~0.977）0.0640.833<0.001
Z20.519（0.375~0.662）0.0640.519<0.001
), ArticleFig(id=1322607945402143540, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607936472470271, language=EN, label=Table 7, caption=

The influence degree of each index on total health expenditure

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指标编号指标名称标化后的偏回归系数（β）排序结果
X3年末总人口数（万人）0.114 3911
X1人均国内生产总值（元）0.114 1992
X7医疗机构床位数（张）0.112 7513
X4城镇化率（%）0.111 6714
X6出生率（%）0.111 3835
X9医院诊疗人次（万人）0.110 2816
X8卫生技术人员（人）0.110 2297
X2个人卫生支出占卫生总费用比重(%)-0.091 2078
X10医院入院人次（万人）-0.076 0419
X5死亡率（%）-0.071 75610
X11医院病床使用率（%）0.066 99411
), ArticleFig(id=1322607945507001141, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322607936472470271, language=CN, label=表7, caption=

各指标对卫生总费用的影响程度

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指标编号指标名称标化后的偏回归系数（β）排序结果
X3年末总人口数（万人）0.114 3911
X1人均国内生产总值（元）0.114 1992
X7医疗机构床位数（张）0.112 7513
X4城镇化率（%）0.111 6714
X6出生率（%）0.111 3835
X9医院诊疗人次（万人）0.110 2816
X8卫生技术人员（人）0.110 2297
X2个人卫生支出占卫生总费用比重(%)-0.091 2078
X10医院入院人次（万人）-0.076 0419
X5死亡率（%）-0.071 75610
X11医院病床使用率（%）0.066 99411
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2009—2021青海省卫生总费用结构变动及其影响因素分析
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王金鹏 , 白文洁 , 张建秀 , 郭映花
现代预防医学 | 卫生政策与管理 2025,52(20): 3761-3766
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现代预防医学 |卫生政策与管理 2025 , 52 (20) : 3761 -3766
2009—2021青海省卫生总费用结构变动及其影响因素分析
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王金鹏, 白文洁, 张建秀, 郭映花
作者信息
  • 青海大学医学部公共卫生系，青海　西宁　810001
通讯作者:
郭映花，E-mail:
作者简介:

王金鹏(2001—)，男，硕士在读，研究方向：卫生统计学

Analysis on the Structural Change of Total Health Expenditure from 2009 to 2021 and Its Influencing Factors, Qinghai
Jin-peng WANG, Wen-jie BAI, Jian-xiu ZHANG, Ying-hua GUO
Affiliations
  • Department of Public Health, Qinghai University, Xining, Qinghai 810001, China
出版时间: 2025-10-25 doi: 10.20043/j.cnki.MPM.202506035
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摘要
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目的

分析2009—2021年青海省卫生总费用结构演变特征及其影响因素，为区域卫生政策优化提供参考。

方法

选取2009—2021年青海省卫生总费用及卫生总费用影响因素指标数据，基于筹资来源法，采用结构变动度分析探究卫生筹资结构动态变化，运用主成分回归识别关键影响因素。

结果

2009—2021年青海省卫生总费用年均增长13.86%，政府卫生支出占比从39.81%升至49.21%，个人支出占比由30.04%降至22.09%，整体结构变动度18.79%，筹资均衡性显著提升；主成分回归显示，人口规模（β=0.114）、经济发展（β=0.114）、医疗资源供给（β=0.113）和城镇化率（β=0.112）为主要正向驱动因素，个人支出占比（β=-0.091）则呈显著抑制作用。

结论

青海省卫生筹资规模持续扩大，居民负担逐步减轻，但需优化政府投入结构、提升资源利用效率，并通过优化医保支付结构、强化资源配置协同性，平衡费用压力，以促进卫生事业可持续发展。

卫生总费用  /  结构变动度  /  影响因素  /  主成分回归
Objective

To analyze the evolution characteristics and influencing factors of total health expenditure structure in Qinghai Province from 2009 to 2021, and to provide reference for regional health policy optimization.

Methods

The data of total health expenditure and influencing factors of total health expenditure in Qinghai Province from 2009 to 2021 were selected. Based on the financing source method, the structural change degree analysis method was used to explore the dynamic changes of health financing structure, and the principal component regression model was used to identify the key influencing factors.

Results

From 2009 to 2021, the average annual growth rate of total health expenditure in Qinghai Province was 13.86%, the proportion of government health expenditure increased from 39.81% to 49.21%, the proportion of personal expenditure decreased from 30.04% to 22.09%, the overall structural change degree was 18.79%, and the financing balance was significantly improved. Principal component regression showed that population size (β=0.114), economic development (β=0.114), medical resource supply (β=0.113) and urbanization rate (β=0.112) were the main positive driving factors, while the proportion of personal expenditure (β=-0.091) was significantly inhibited.

Conclusion

The scale of health financing in Qinghai Province continues to expand, and the burden of residents is gradually reduced. However, it is necessary to optimize the structure of government investment, improve the efficiency of resource utilization, and optimize the structure of medical insurance payment.

Total health expenditure  /  Degree of structural change  /  Influencing factors  /  Principal component regression
王金鹏, 白文洁, 张建秀, 郭映花. 2009—2021青海省卫生总费用结构变动及其影响因素分析. 现代预防医学, 2025 , 52 (20) : 3761 -3766 . DOI: 10.20043/j.cnki.MPM.202506035
Jin-peng WANG, Wen-jie BAI, Jian-xiu ZHANG, Ying-hua GUO. Analysis on the Structural Change of Total Health Expenditure from 2009 to 2021 and Its Influencing Factors, Qinghai[J]. Modern Preventive Medicine, 2025 , 52 (20) : 3761 -3766 . DOI: 10.20043/j.cnki.MPM.202506035
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卫生总费用指特定时期内，一个国家或地区投入医疗卫生事业的全部资金。其核算采用筹资来源法，统计政府、社会、个人现金三大卫生支出类别，反映医疗卫生体系效率与公平性，是保障居民健康、推进健康中国建设的物质基础[1-2]。青海省地处青藏高原东北部，作为西部欠发达省份，兼具生态脆弱、民族多元、区域发展不均衡的特征[3]。随着“健康中国”战略推进、医改深化及人口老龄化、城镇化加速，该省卫生总费用的规模、结构及筹资机制面临深刻调整[4]。因此系统分析其结构变动、影响因素及趋势预测，对优化资源配置、增强服务韧性、推动健康青海建设具有重要意义。青海省作为“一带一路”节点及黄河、长江上游生态保护核心区[5-6]，卫生健康事业受限于经济总量不足、地理环境复杂，同时承担保障民族地区健康、服务国家生态战略的特殊使命。2020年疫情更加凸显公共卫生建设重要性，对卫生资源合理分配提出更高要求[7-8]。侯积菲[9]、冯静[10]等学者研究虽已涵盖2023年青海省卫生总费用占地区生产总值比重、筹资结构中各部分支出占比等基础数据，但研究多停留在费用规模、占比等静态指标的呈现层面，对近十年卫生总费用的系统性结构测算仍存在明显欠缺。因此，本研究基于2009—2021年数据，采用结构变动度分析法探究卫生筹资结构动态变化，运用主成分回归模型识别关键影响因素，为持续优化区域卫生筹资体系、精准制定卫生健康领域决策提供依据，同时为西部同类地区提供区域研究样本。
1　研究资料与方法
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1.1　数据与变量
此次研究的数据主要来源于《青海省统计年鉴》、RESSET行业数据库。基于国内外既有定性、定量研究文献[11-12]，结合当下卫生服务供需现状及宏观政策环境分析[13-14]，本研究确立卫生总费用为核心分析变量。在结构分析层面，选取政府、社会及个人卫生支出三大核心指标，系统考察卫生筹资体系的结构性变迁。在影响因素分析层面，本研究构建了包含三大维度的解释框架：经济因素、人口因素以及卫生服务因素（卫生服务供给和需求），共计11个解释变量。见表1。
1.2　研究方法
1.2.1　结构变动分析法
本研究基于2009、2011—2021年青海省卫生总费用数据，采用结构变动度分析方法，运用Excel软件计算结构变动值（Value of Structural Variation, VSV）、结构变动度（Degree of Structural Variation, DSV）及结构变动贡献率三项核心指标，从变动方向、变动程度及各构成部分贡献度三个维度，结合新医改推进节点分为4个区间，并对不同年份区间及整体卫生筹资结构的演变特征进行描述性统计分析。（结构变动值计算公式为VSV=Xi1-Xi2，i代表费用项目序列号，0代表期初，1代表期末。当VSV>0，该项目占比增加，反之则表示占比减少。结构变动度的计算公式为DVS=∑｜Xi1-Xi0｜，DVS值越大则各组成部分变动越显著。结构变动度贡献率=｜Xi1-Xi2｜/DVS×100%，其反映各部分对总体变动的影响程度）。
1.2.2　主成分回归分析法
鉴于卫生总费用影响因素间可能存在的多重共线性问题，为提高模型估计的准确性和解释力，本研究运用主成分回归分析方法予以处理。首先对11个解释变量（X1~X11）进行标准化处理，消除量纲差异影响，再采用方差膨胀因子（VIF）检验法，对变量间可能存在的共线性问题进行分析，结果显示所有变量的VIF值均大于10，表明变量间存在高度共线性，需通过主成分分析进行降维处理。进一步通过KMO检验和Bartlett球形检验验证主成分分析的适用性，在此基础上，对变量X1~X11开展主成分分析，按照初始特征值>1的准则提取关键因子以实现变量维度的降低，随后建立多元线性回归模型展开实证分析。上述分析流程通过SPSS 28.0软件完成。
2　结果
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2.1　青海省卫生总费用结构变动分析
2.1.1　青海省卫生费用变动情况
近年来，随着区域经济实力逐步增强，青海省卫生总费用呈现出持续增长的态势。从2009年的77.99亿元升至2021年的388.07亿元，在这12年间，年均增长率达13.86%。2009—2021年间，政府、社会及个人卫生支出均呈现逐年递增的趋势。政府卫生支出从2009年的31.05亿元增长到2021年的190.96亿元，占比从39.81%稳步提升至49.21%。社会卫生支出从2009年的23.51亿元增加到2021年的111.38亿元，占比从30.14%经过波动后于2021年达到28.70%。个人卫生支出从2009年的23.43亿元上升至2021年的85.73亿元，占比则从30.04%逐年下降至22.09%。见表2。
2.1.2　青海省卫生总费用筹资结构变动分析
表3根据2009—2021年青海省卫生总费用结构变动数据显示，2009—2012年，政府卫生支出占比提升显著，结构变动值3.51%，贡献率达50.76%，主导结构变动，社会卫生支出占比微降，个人现金卫生支出占比明显下滑，结构变动值-3.02%，贡献率43.81%，此区间结构变动度7.01%。2013—2016年，政府和社会卫生支出占比双降，个人现金卫生支出占比上升，结构变动值3.62%，贡献率50.13%，成变动主因，结构变动度5.68%。2017—2021年，政府和社会卫生支出占比回升，个人现金卫生支出占比大幅下降，结构变动值-3.91%，贡献率50.00%，结构变动度7.83%。2009—2021年，政府卫生支出结构变动值累计9.40%，贡献率50.00%，主导长期结构变化；社会卫生支出变动较小；个人现金卫生支出负担总体下降，结构变动值-7.95%，贡献率42.32%，整体结构变动度18.79%。
2.2　青海省卫生总费用主成分回归分析结果
2.2.1　主成分分析
为排除变量间量纲差异带来的干扰，对所选取的变量实施标准化处理。处理完成后，进行VIF检验，经检验VIF均大于10，表明变量之间存在高度共线性问题，鉴于此进一步开展KMO和Bartlett检验，经检验，KMO值达到0.705>0.5；Bartlett检验中，近似χ2值为222.795，且P<0.001。这一检验结果清晰地显示出所选变量间存在较强的相关性，满足主成分分析的基本前提条件。接下来，对变量X1~X11开展主成分分析。按照初始特征值大于1这一筛选准则，最终成功提取出两个主成分。主成分1与主成分2的累计贡献率达到90.183%（表4），该提取效果较为理想，表明所提取的主成分能够高度解释原始变量，可认定主成分1和主成分2即为本次研究的主成分。基于主成分得分系数矩阵（表5），主成分表达式为：
2.2.2　青海省卫生总费用线性回归分析
将标准化处理后的青海省卫生总费用作为因变量，将主成分PC1和主成分PC2当作自变量实施多元线性回归分析，回归结果（详见表6）显示，决定系数R2=0.964，调整R2=0.956，表明回归模型拟合效果较好，方差分析的显著性检验结果显示，F=10.601，P<0.001，说明回归模型具有统计学意义，其中PC1的回归系数为0.833，PC2的回归系数为0.519。根据主成分分析得到的主成分PC1和主成分PC2的表达式（表5系数矩阵），利用上述回归系数，通过公式βj=0.833×αj+0.519×bj（其中αj为PC1得分系数矩阵中第j个变量的系数，bj为PC2得分系数矩阵中第j个变量的系数）计算得到标准化后各原始变量的偏回归系数（表7），最终回归方程表达式如下：
基于标准化回归系数分析（表7），卫生总费用的影响因素呈现显著梯度特征。正向效应中，人口规模（X3，β=0.114）与经济发展水平（X1，β=0.114）构成主要驱动力，其次为医疗资源供给（X9，β=0.110、X7，β=0.113）、城镇化进程（X4，β=0.112）及人口结构变动（X6，β=0.111），三类指标贡献度均稳定于0.11阈值及以上。负向维度中，个人卫生支出占比（X2，β=-0.091）呈显著拮抗效应，医院运营指标（X10/X11）其效应强度较核心变量显著较弱。
3　讨论
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本研究通过结构变动度分析、主成分回归分析，系统的揭示了青海省卫生总费用的结构演变规律及其影响因素，为欠发达地区卫生经济研究提供了方法论借鉴与政策参考。
3.1　卫生总费用结构变动的阶段特征
本研究基于结构变动度，将2009—2021年青海省卫生筹资结构划分为三个演进阶段：政府主导型变动期（2009—2012年），政府卫生支出占比提升39.81%至43.32%，结构变动贡献率达50.76%，与新医改初期政府加大公共卫生投入、完善基层卫生服务体系的政策路径高度契合[15]；结构调整阵痛期（2013—2016年），政府与社会支出占比双降，个人卫生支出占比反弹至27.52%，反映出医保报销范围扩容初期的制度调试效应与筹资责任的阶段性转移[16]；多元协同优化期（2017—2021年），政府与社会支出占比回升（分别达49.21%和28.70%），个人支出占比降至22.09%，结构变动度7.82%，彰显了医保支付方式改革（如按病种付费试点）与社会资本有序进入的政策成效。这一演进轨迹这一趋势与宁夏[17]、广西[18]等西部省份的研究结论一致，但相较东部发达地区存在明显差异（如北京、上海个人支出占比<25%）[10]，而青海省个人负担仍偏高。究其根本原因，主要包括三个方面：一是财政依赖度高，青海省卫生总费用中政府支出贡献率达50.00%，远高于同时期东部省份（如山东省政府支出贡献率17.24%）[14]。二是社会筹资能力薄弱，社会卫生支出占比长期在28%左右波动，显著低于东部（如上海社会支出占比60.17%）[10]。三是该省农村居民人均可支配收入仅为全国平均水平的72%（2023年全国统计年鉴），居民支付能力有限，较高个人负担易加剧健康不公平，故降低个人支出是保障基本健康权益的必然要求。
3.2　卫生总费用影响因素的作用机制
主成分回归分析进一步揭示，人口规模扩张与经济发展（β=0.114）是卫生费用增长的核心驱动力，城镇化（β=0.112）与医疗资源供给（β=0.113）的协同作用则反映了卫生服务可及性提升对需求的释放效应。值得注意的是，个人支出占比的负向抑制作用（β=-0.091）其作用机制体现在两个维度。一方面，控费政策直接约束供方行为。青海省2017年起推行的医保支付方式改革（如DRG/DIP试点、总额预付）通过设置病种支付标准、严控不合理诊疗项目，有效压缩了供方诱导需求空间[19]。另一方面，分级诊疗体系降低高成本服务利用。医疗援青政策实施后，个人自付比例下降与基层首诊率提升（2024年达68%）形成联动，而基层医疗机构服务单价仅为三级医院的30%~40%，从结构上降低了区域卫生总费用[20-21]。这与全国层面“个人支出占比从29.27%降至27.33%”的优化趋势形成协同，验证了医保制度在费用调控中的核心作用[1]。
3.3　政策启示与研究局限
结合青海省卫生总费用结构演变特征及影响因素，建议从五方面优化政策：一是优化政府卫生投入结构，向高原偏远及基层倾斜，建立与经济、人口挂钩的动态调整机制；二是深化医保支付改革，推进DRG/DIP全覆盖，强化分级诊疗与基层首诊联动，发挥个人支出占比的控费作用，切实降低居民负担；三是平衡医疗资源供给，结合城镇化布局资源，提升利用效率；四是激活社会筹资潜力，通过优化社会办医环境、发展特色商业健康保险及创新慈善模式，破解社会支出占比偏低（约28%）困境；五是建立卫生费用监测体系，动态跟踪费用结构与关键驱动因子，强化卫健、医保、财政政策联动，协同引导卫生费用合理增长与可持续优化。本研究的局限在于：未区分城乡差异，可能掩盖了牧区与城镇的机制异质性。未来可结合面板数据模型与田野调查，深化区域细分研究。
基于上述研究，本研究为西部省份卫生经济政策制定提供了基于区域特征的科学路径，尤其在政府主导型筹资体系优化、小样本数据建模等方面具有推广价值。但未来需持续关注人口结构变化与技术创新，推动卫生费用增长与居民健康福祉的协同提升。
基金
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  • 2024年青海省卫生健康系统重点课题(2024-wjzd-12)
  • 青海大学2025年研究生导师创新团队建设项目(qddt-2511)
文献
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2025年第52卷第20期
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doi: 10.20043/j.cnki.MPM.202506035
  • 接收时间：2025-06-03
  • 首发时间：2026-10-29
  • 出版时间：2025-10-25
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  • 收稿日期：2025-06-03
基金
2024年青海省卫生健康系统重点课题(2024-wjzd-12)
青海大学2025年研究生导师创新团队建设项目(qddt-2511)
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    青海大学医学部公共卫生系，青海　西宁　810001

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郭映花，E-mail:
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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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