Article(id=1322608136687571011, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1322608013010120712, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202505329, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1748016000000, receivedDateStr=2025-05-24, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793263952657, onlineDateStr=2026-10-29, pubDate=1762704000000, pubDateStr=2025-11-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793263952657, onlineIssueDateStr=2026-10-29, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793263952657, creator=13701087609, updateTime=1793263952657, updator=13701087609, issue=Issue{id=1322608013010120712, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='21', pageStart='3841', pageEnd='4032', issueExtLink='null', onlineDate='null', pubDate='1762704000000', pubDateStr='2025-11-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793263923169, creator='13701087609', updateTime=1793264266929, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1322609454932149086, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1322608013010120712, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1322609454932149087, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1322608013010120712, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=3968, endPage=3976, ext={EN=ArticleExt(id=1322608137035698244, articleId=1322608136687571011, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Systematic review and meta-analysis of global real-world evidence: cross-country comparison of the economic burden in patients with multimorbidity, columnId=1228016567846367388, journalTitle=Modern Preventive Medicine, columnName=Health Policy and Management, runingTitle=null, highlight=null, articleAbstract=
Objective

To assess the economic burden of multimorbidity and complex multimorbidity, focusing on cost variations across medical insurance system, synergistic cost effects of multimorbidity clusters, and expenditure patterns among older versus non-older adults, thereby providing evidence to optimize disease management, health resource allocation, and targeted interventions for high-risk populations.

Methods

Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Meta-analysis Of Observational Studies in Epidemiology (MOOSE) guidelines, CNKI, WanFang Data, SinoMed, PubMed, Embase, Web of Science,Scopus, and Cochrane Library were systematically searched for studies on the economic burden of multimorbidity until July 2024. Two reviewers independently screened studies and extracted data. Meta-analysis was performed using Review Manager 5.4 and Stata 18.0.

Results

A total of 27 studies with 13 266 248 participants were included. Patients with multimorbidity had significantly higher annual per capita costs across all categories compared to those with a single condition. Healthcare costs (Total: SMD=0.34, 95% CI: 0.08-0.60; Out-of-pocket: SMD=0.36, 95% CI: 0.11-0.60), hospitalization costs (Total: SMD=0.36, 95% CI: 0.20-0.51; Out-of-pocket SMD=0.20, 95% CI: 0.02-0.39), and outpatient costs (Total: SMD=0.34, 95% CI:-0.02-0.70; Out-of-pocket: SMD=0.20, 95% CI: 0.04-0.36). Costs were also higher for ≥4 conditions than for ≥2.Geographically, total costs were higher in the US and the Eurozone than in mainland China and Singapore. The cost increase effect was highest in the US (SMD=0.38, 95% CI: 0.36-0.40), followed by Eurozone (SMD=0.26, 95% CI: 0.21-0.30) and China (SMD=0.26, 95% CI: 0.12-0.40), with significant subgroup differences (P<0.001). Costs varied by multimorbidity patterns (e.g., higher for diabetes/hypertension), severity (positively correlated with cumulative illness scores and CCI), and age (higher in adults ≥65 years).

Conclusion

Multimorbidity imposes a significant economic burden with regional and group variations. Optimized disease management, improved health insurance coverage, and targeted health policies to reduce the burden are urgently needed. Future studies should focus on economic impacts of specific multimorbidity patterns to develop precise interventions.

, authors=Zi-han ZHOU1, Li YAO2, Jia-jia YIN1, Ting-rui WANG1, Qin-qin LI1, Yan LIU1, authorsList=Zi-han ZHOU, Li YAO, Jia-jia YIN, Ting-rui WANG, Qin-qin LI, Yan LIU, authorCompany=null, correspAuthors=Li YAO, 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=1322608139938156619, articleId=1322608136687571011, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=全球真实世界证据的系统评价与Meta分析——多重慢病患者经济负担的跨国比较, columnId=1228016568014139551, journalTitle=现代预防医学, columnName=卫生政策与管理, runingTitle=null, highlight=null, articleAbstract=
目的

评估多重及复杂多重慢病的经济负担,重点分析不同医疗保障体系下的费用差异、共病组合的协同成本效应,以及老年与非老年人群的费用增长模式。为优化疾病管理、卫生资源配置与高危人群干预策略提供证据支持。

方法

遵循Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRiSMA)和Meta-analysis of Observational Studies in Epidemiology(MOOSE)指南,系统检索中、外数据库CNKI、WanFang Date、SinoMed、PubMed、Embase、Web of Science、Scopus和Cochrane Library中收录的有关多重慢病经济负担的研究,检索建库至2024年7月。由二名研究者独立筛选文献、提取数据,使用Review Manager 5.4和Stata 18.0软件进行meta分析。

结果

共纳入27篇文献,样本量13 266 248人。结果显示,≥2种慢病患者各项年人均费用均显著高于单一慢病患者,医疗保健费用总SMD=0.34(95% CI:0.08~0.60)、自付SMD=0.36(95% CI:0.11~0.60),住院费用总SMD=0.36(95% CI:0.20~0.51)、自付SMD=0.20(95% CI:0.02~0.39),门诊费用总SMD=0.34(95% CI:-0.02~0.70)、自付SMD=0.20(95% CI:0.04~0.36)。≥4种慢病者费用亦显著高于≥2种者。地区分析显示美国、欧元区总费用普遍高于中国大陆、新加坡;总费用增长效应表现为美国(SMD=0.38,95% CI:0.36~0.40)>欧元区(SMD=0.26,95% CI:0.21~0.30)≈中国(SMD=0.26,95% CI:0.12~0.40),且亚组间差异显著(P<0.001)。此外,医疗费用在疾病模式(如糖尿病/高血压共病费用更高)、严重程度(与累积多病评分、Charlson指数正相关)及年龄组(≥65岁老年患者费用较高)间差异显著。

结论

多重慢病经济负担显著,存在地域与人群差异。亟需优化疾病管理、完善医疗保障并制定针对性卫生政策以减轻负担。未来研究应聚焦不同共病模式的经济负担,开发精准干预措施。

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周梓涵(2001—),男,硕士在读,研究方向:慢性病护理与管理

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姚丽,E-mail:
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周梓涵(2001—),男,硕士在读,研究方向:慢性病护理与管理

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周梓涵(2001—),男,硕士在读,研究方向:慢性病护理与管理

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BMC Public Health, 2025, 25 (1): 283., articleTitle=Equity and efficiency of public health resource allocation in China, refAbstract=null)], funds=[Fund(id=1322608146523213963, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322608136687571011, awardId=黔科合成果LC(2025)一般057, language=CN, fundingSource=贵州省科技厅资助项目(黔科合成果LC(2025)一般057), fundOrder=null, country=null), Fund(id=1322608146598711436, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322608136687571011, awardId=ZHKYQ202316, language=CN, fundingSource=中华护理学会2023年度科研课题项目(ZHKYQ202316), fundOrder=null, country=null), Fund(id=1322608146695180429, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322608136687571011, awardId=[2022]-4-2-2号, language=CN, fundingSource=贵阳市科技计划项目([2022]-4-2-2号), fundOrder=null, country=null), Fund(id=1322608146770677902, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322608136687571011, awardId=gyfynsfc[2023]-35, language=CN, fundingSource=贵州医科大学附属医院国家自然科学基金培育计划(gyfynsfc[2023]-35), fundOrder=null, country=null), Fund(id=1322608146837786767, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322608136687571011, awardId=gyfyhlxz-2023-2, language=CN, fundingSource=贵州医科大学附属医院护理科研基金项目(gyfyhlxz-2023-2), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1322608140198203468, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322608136687571011, xref=1., ext=[AuthorCompanyExt(id=1322608140206592077, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322608136687571011, companyId=1322608140198203468, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=The School of Nursing, Guizhou Medical University, Guiyang, Guizhou 561113, China), AuthorCompanyExt(id=1322608140214980686, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322608136687571011, companyId=1322608140198203468, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.贵州医科大学护理学院,贵州 贵阳 561113)]), AuthorCompany(id=1322608140277895247, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322608136687571011, xref=2., ext=[AuthorCompanyExt(id=1322608140286283856, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322608136687571011, companyId=1322608140277895247, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.贵州医科大学附属医院呼吸与危重症医学科,贵州 贵阳 550004)])], figs=[ArticleFig(id=1322608144874852473, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322608136687571011, language=EN, label=Figure 1, caption=Data standardization flowchart, figureFileSmall=dKN2toVXDm+ohb/gvvJsDg==, figureFileBig=jtr47AlAgU6QeIssBZ23gg==, tableContent=null), ArticleFig(id=1322608144962932858, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322608136687571011, language=CN, label=图1, caption=数据标准化流程图, figureFileSmall=dKN2toVXDm+ohb/gvvJsDg==, figureFileBig=jtr47AlAgU6QeIssBZ23gg==, tableContent=null), ArticleFig(id=1322608145130705019, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322608136687571011, language=EN, label=Figure 2, caption=Flowchart of literature screening, figureFileSmall=kiLGQSUMKSkL7beMRssRXg==, figureFileBig=eKNQis6EESl3k2hkh0OoNA==, tableContent=null), ArticleFig(id=1322608145202008188, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322608136687571011, language=CN, label=图2, caption=文献筛选流程图, figureFileSmall=kiLGQSUMKSkL7beMRssRXg==, figureFileBig=eKNQis6EESl3k2hkh0OoNA==, tableContent=null), ArticleFig(id=1322608145264922749, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322608136687571011, language=EN, label=Figure 3, caption=Funnel plot of publication bias in prevalence of multimorbidity, figureFileSmall=K/R+vd9cRSzRoBql2LBeUg==, figureFileBig=c2QroWLmsiV0aEf+y6z6zQ==, tableContent=null), ArticleFig(id=1322608145353003134, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322608136687571011, language=CN, label=图3, caption=多重慢病患病率发表偏倚漏斗图, figureFileSmall=K/R+vd9cRSzRoBql2LBeUg==, figureFileBig=c2QroWLmsiV0aEf+y6z6zQ==, tableContent=null), ArticleFig(id=1322608145474637951, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322608136687571011, language=EN, label=Table 1, caption=

Search strategies of PubMed databases

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序号检索策略
#1(“Multimorbidity”[Mesh] OR multimorbidity[Title] OR comorbidity[Title] OR“Multiple Chronic Diseases”[Title] OR“Multiple Chronic Illnesses”[Title] OR “Multiple Chronic Health Conditions”[Title])
#2(“Health Expenditures”[Mesh] OR cost*[Title] OR financ*[Title] OR economic*[Title] OR expenditure*[Title] OR expense*[Title] OR spend*[Title] OR payment*[Title])
#3#1 AND #2
), ArticleFig(id=1322608145550135424, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322608136687571011, language=CN, label=表1, caption=

PubMed数据库检索策略

, figureFileSmall=null, figureFileBig=null, tableContent=
序号检索策略
#1(“Multimorbidity”[Mesh] OR multimorbidity[Title] OR comorbidity[Title] OR“Multiple Chronic Diseases”[Title] OR“Multiple Chronic Illnesses”[Title] OR “Multiple Chronic Health Conditions”[Title])
#2(“Health Expenditures”[Mesh] OR cost*[Title] OR financ*[Title] OR economic*[Title] OR expenditure*[Title] OR expense*[Title] OR spend*[Title] OR payment*[Title])
#3#1 AND #2
), ArticleFig(id=1322608145634021505, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322608136687571011, language=EN, label=Table 2, caption=

Basic characteristics and quality evaluation of the included studies

, figureFileSmall=null, figureFileBig=null, tableContent=
第一作者/年份调查时间
(年)
地区年龄(岁)
(人群)
样本/数据来源样本量研究设计多病诊断标准≥2CC/NCD%≥4CC%质量评分
卢延晴2024[13]2018中国≥65(社区)CLHLS20187 483A≥2CC38.1110.787
李潇2020[14]2016—2017中国≥60(农村)档案记录+体检4 833A≥2CC16.060.219
金琇泽2019[15]2015中国≥60(社区)CHARLS 20155 265A≥2CC44.4611.157
Mei—ju Chi 2011[16]2001中国台湾≥50(社区)NLCE/HIC221 256A≥2CC27.333.857
范潇茹2022[17]2018中国≥45(社区)CHARLS 201816 674A≥2CC57.3422.118
Puxian Peng 2023[18]2018中国≥35(社区)NHSS 201811 304A≥2CC10.12NR9
Nancy E.Schoenberg,PhD 2007[19]2002美国≥65(社区)HRS(1998,2002)8 180B≥2CC70.8119.828
Jennifer L Wolff 2002[20]1999美国≥65(社区)CMS1 217 103A≥2CC64.7024.108
Nicholas K. Schiltz 2022[21]2016—2019美国≥18(社区)MEPS(2016—2019)89 947A≥2CC32.9012.309
Wenjun Zhong 2015[22]2004—2007美国0~17(社区)Mayo Clinic14 727B≥2CC17.042.508
Anup Karan 2022[23]2017—2018印度≥40(社区)NSSO(2017—2018)37 202A≥2NCD4.57NR6
Sanghamitra Pati 2014[24]2007印度≥18(社区)SAGE10 973A≥2NCD8.90NR10
Mahendra M.Reddy 2022[25]2019—2021印度≥18(农村)GHDSS75 037A≥2NCD1.81NR7
Sharon Walsh 2023[26]2009—2011爱尔兰≥50(社区)TILDA(first wave)8 447A≥2CC51.4015.397
Umesh T Kadam 2013[27]2007—2009英国≥40(社区)住院病历60 660A≥2CC33.36NR6
Phuong Bich Tran 2024[28]2017—2020比利时≥15(社区)BHIS(2018)/IMA9 753C≥2CC48.0121.006
Juan F.Orueta 2014[29]2011西班牙≥0(社区)PREST2 262 698A≥2CC23.617.756
Louisa Picco 2 016[30]2012—2013新加坡≥60(社区)WiSE2 565A≥2CC55.36NR9
刘梦竹2021[31]2016—2020中国5~98(住院)住院病历2 385A≥2CC93.0870.828
于建星2022[32]2019中国>0(住院)住院病历397 787A≥2SD74.7216.027
Yun Wu 2022[33]2018中国≥45(慢病患者)CHARLS 201812 458A≥2CC66.5021.527
Cother Hajat 2020[34]2015美国≥18(慢病患者)IBM MarketScan1 878 951A≥2CC49.55NR8
Shu Yun Tan 2021[35]2015—2017新加坡≥21(慢病患者)NHGP254 377B≥2CC85.1536.336
Kednapa Thavorn 2017[36]2009—2010加拿大>0(慢病患者)DAD/OHIP6 639 089B≥2CC47.8011.308
Abdulkarim M. Meraya 2015[37]2011美国≥21(多病患者)MEPS(2009,2011)9 296A≥2CCNRNR7
Mary Charlson,MD 2007[38]1993美国住院患者住院病历5 861BCCINRNR8
A Nagl 2012[39]2010德国≥72(多病患者)PRISCUS trial1 937AMCINRNR7
), ArticleFig(id=1322608145726296194, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322608136687571011, language=CN, label=表2, caption=

纳入研究的基本特征与质量评价

, figureFileSmall=null, figureFileBig=null, tableContent=
第一作者/年份调查时间
(年)
地区年龄(岁)
(人群)
样本/数据来源样本量研究设计多病诊断标准≥2CC/NCD%≥4CC%质量评分
卢延晴2024[13]2018中国≥65(社区)CLHLS20187 483A≥2CC38.1110.787
李潇2020[14]2016—2017中国≥60(农村)档案记录+体检4 833A≥2CC16.060.219
金琇泽2019[15]2015中国≥60(社区)CHARLS 20155 265A≥2CC44.4611.157
Mei—ju Chi 2011[16]2001中国台湾≥50(社区)NLCE/HIC221 256A≥2CC27.333.857
范潇茹2022[17]2018中国≥45(社区)CHARLS 201816 674A≥2CC57.3422.118
Puxian Peng 2023[18]2018中国≥35(社区)NHSS 201811 304A≥2CC10.12NR9
Nancy E.Schoenberg,PhD 2007[19]2002美国≥65(社区)HRS(1998,2002)8 180B≥2CC70.8119.828
Jennifer L Wolff 2002[20]1999美国≥65(社区)CMS1 217 103A≥2CC64.7024.108
Nicholas K. Schiltz 2022[21]2016—2019美国≥18(社区)MEPS(2016—2019)89 947A≥2CC32.9012.309
Wenjun Zhong 2015[22]2004—2007美国0~17(社区)Mayo Clinic14 727B≥2CC17.042.508
Anup Karan 2022[23]2017—2018印度≥40(社区)NSSO(2017—2018)37 202A≥2NCD4.57NR6
Sanghamitra Pati 2014[24]2007印度≥18(社区)SAGE10 973A≥2NCD8.90NR10
Mahendra M.Reddy 2022[25]2019—2021印度≥18(农村)GHDSS75 037A≥2NCD1.81NR7
Sharon Walsh 2023[26]2009—2011爱尔兰≥50(社区)TILDA(first wave)8 447A≥2CC51.4015.397
Umesh T Kadam 2013[27]2007—2009英国≥40(社区)住院病历60 660A≥2CC33.36NR6
Phuong Bich Tran 2024[28]2017—2020比利时≥15(社区)BHIS(2018)/IMA9 753C≥2CC48.0121.006
Juan F.Orueta 2014[29]2011西班牙≥0(社区)PREST2 262 698A≥2CC23.617.756
Louisa Picco 2 016[30]2012—2013新加坡≥60(社区)WiSE2 565A≥2CC55.36NR9
刘梦竹2021[31]2016—2020中国5~98(住院)住院病历2 385A≥2CC93.0870.828
于建星2022[32]2019中国>0(住院)住院病历397 787A≥2SD74.7216.027
Yun Wu 2022[33]2018中国≥45(慢病患者)CHARLS 201812 458A≥2CC66.5021.527
Cother Hajat 2020[34]2015美国≥18(慢病患者)IBM MarketScan1 878 951A≥2CC49.55NR8
Shu Yun Tan 2021[35]2015—2017新加坡≥21(慢病患者)NHGP254 377B≥2CC85.1536.336
Kednapa Thavorn 2017[36]2009—2010加拿大>0(慢病患者)DAD/OHIP6 639 089B≥2CC47.8011.308
Abdulkarim M. Meraya 2015[37]2011美国≥21(多病患者)MEPS(2009,2011)9 296A≥2CCNRNR7
Mary Charlson,MD 2007[38]1993美国住院患者住院病历5 861BCCINRNR8
A Nagl 2012[39]2010德国≥72(多病患者)PRISCUS trial1 937AMCINRNR7
), ArticleFig(id=1322608145822765187, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322608136687571011, language=EN, label=Table 3, caption=

Subgroup analysis of the prevalence of multimorbidity in the included studies

, figureFileSmall=null, figureFileBig=null, tableContent=
亚组纳入研究数异质性检验效应模型meta分析结果组间差异
I2(%)P值PPM(%)95% CIZP值I2 (%)/ P值
人群类型24[13-36]100.0<0.001随机42.6133.85,51.379.54<0.001100.0/<0.001
社区人群16[13,15-24,26-30]100.0<0.001随机36.7524.64,48.865.95<0.001
农村人群2[14,25]99.9<0.001随机8.92-5.04,22.881.250.210
慢性病患者4[33-36]100.0<0.001随机62.2549.26,75.249.39<0.001
住院人群2[31-32]99.9<0.001随机83.8965.90,101.899.14<0.001
社区人群年龄(岁)100.0/<0.001
年龄≥01[29]NN随机23.6123.55,23.67836.26<0.001
儿童(0~17)1[22]NN随机17.0416.43,17.6454.99<0.001
青少年和成人(≥15 ≥18)3[21,24,28]100.0<0.001随机29.9310.84,49.033.070.002
中老年人(≥35 ≥40 ≥50)6[16-18,23,26-27]100.0<0.001随机30.6817.36,44.014.51<0.001
老年人(≥60 ≥65)5[13-15,19-20,30]99.9<0.001随机54.7043.47,65.929.55<0.001
社区人群地区100.0/<0.001
中国5[13,15-18]100.0<0.001随机35.4721.60,49.345.01<0.001
美国4[19-22]100.0<0.001随机46.3622.65,70.073.83<0.001
印度2[23-24]100.0<0.001随机6.732.48,10.983.110.002
欧元区4[26-29]100.0<0.001随机39.0828.85,49.327.48<0.001
新加坡1[30]NN随机55.3653.44,57.2856.40<0.001
), ArticleFig(id=1322608145898262660, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322608136687571011, language=CN, label=表3, caption=

纳入研究的多重慢病患病率亚组分析

, figureFileSmall=null, figureFileBig=null, tableContent=
亚组纳入研究数异质性检验效应模型meta分析结果组间差异
I2(%)P值PPM(%)95% CIZP值I2 (%)/ P值
人群类型24[13-36]100.0<0.001随机42.6133.85,51.379.54<0.001100.0/<0.001
社区人群16[13,15-24,26-30]100.0<0.001随机36.7524.64,48.865.95<0.001
农村人群2[14,25]99.9<0.001随机8.92-5.04,22.881.250.210
慢性病患者4[33-36]100.0<0.001随机62.2549.26,75.249.39<0.001
住院人群2[31-32]99.9<0.001随机83.8965.90,101.899.14<0.001
社区人群年龄(岁)100.0/<0.001
年龄≥01[29]NN随机23.6123.55,23.67836.26<0.001
儿童(0~17)1[22]NN随机17.0416.43,17.6454.99<0.001
青少年和成人(≥15 ≥18)3[21,24,28]100.0<0.001随机29.9310.84,49.033.070.002
中老年人(≥35 ≥40 ≥50)6[16-18,23,26-27]100.0<0.001随机30.6817.36,44.014.51<0.001
老年人(≥60 ≥65)5[13-15,19-20,30]99.9<0.001随机54.7043.47,65.929.55<0.001
社区人群地区100.0/<0.001
中国5[13,15-18]100.0<0.001随机35.4721.60,49.345.01<0.001
美国4[19-22]100.0<0.001随机46.3622.65,70.073.83<0.001
印度2[23-24]100.0<0.001随机6.732.48,10.983.110.002
欧元区4[26-29]100.0<0.001随机39.0828.85,49.327.48<0.001
新加坡1[30]NN随机55.3653.44,57.2856.40<0.001
), ArticleFig(id=1322608145982148741, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322608136687571011, language=EN, label=Table 4, caption=

Distribution of cost components by number of chronic conditions and regional comparisons (standardized data)

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医疗成本类型
(年人均)
慢病数量
(种)
报告研究数量范围(元)均值(元)地区费用对比(元)
报告研究数量地区范围(元)均值(元)
医疗保健总费用111[15-16,20-22,26,28-30,33,35]117.27~44 262.2412 296.513[20-22]美国18 175.50~44 262.2420 382.97
1[16]中国台湾—13 541.96
3[26,28-29]欧元区8 394.75~19 284.588 803.33
2[30,35]新加坡2 735.68~21 968.923 081.69
2[15,33]中国大陆117.27~4 007.742 677.07
≥213[15-16,18,20-22,26,28,30,33-35,37]1 410.37~116 235.0098 136.665[20-22,34,37]美国78 336.72~116 235.00112 705.90
2[26,28]欧元区15 058.89~44 617.2330 394.90
1[16]中国台湾—28 285.12
3[15,18,33]中国大陆1 410.37~11 334.187 169.30
2[30,35]新加坡5 864.08~40 935.386 092.50
≥410[15-16,20-22,26,28,33-35]2 556.74~241 739.09142 912.224[20-22,34]美国92 497.68~241 739.09160 086.10
1[16]中国台湾—50 786.13
2[26,28]欧元区22 320.74~61 753.3746 442.01
2[15,33]中国大陆2 556.74~13 381.629 967.22
1[35]新加坡—7 534.99
医疗保健自付费用13[19,21,25]909.00~34 602.846 056.832[19,21]美国5 570.40~34 602.848 080.45
1[25]印度—909.00
≥23[19,21,25]2 070.00~58 374.1415 043.122[19,21]美国7 834.31~58 374.1415 536.95
1[25]印度—2 070.00
≥42[19,21]8 754.24~69 086.5915 341.782[19,21]美国8 754.24~69 086.5915 341.78
住院费用14[13,17,31-32]6 032.17~13 527.0113 124.464[13,17,31-32]中国大陆6 032.17~13 527.0113 124.46
≥26[13,17-18,31-32,34]4 431.88~19 448.8818 754.201[34]美国—19 448.88
5[13,17-18,31-32]中国大陆4 431.88~17 219.2716 819.78
≥45[13,17,31-32,34]10 865.36~29 760.2828 338.971[34]美国—29 760.28
4[13,17,31-32]中国大陆10 865.36~18 711.0018 121.12
住院自付费用14[13,17,23-24]1 506.49~3 966.203 574.832[23-24]印度1 506.49~3 966.203 691.75
2[13,17]中国大陆3 087.05~3 282.923 210.40
≥24[13,17,23-24]1 606.29~4 794.34 442.592[23-24]印度1 606.29~4 794.304 936.00
2[13,17]中国大陆4 506.45~4 565.744 552.42
≥42[13,17]4 787.99~5 377.464 893.872[13,17]中国大陆4 787.99~5 377.464 893.87
门诊费用12[13,17]496.77~1 348.37812.082[13,17]中国大陆496.77~1 348.37812.08
≥23[13,17,34]616.42~26 408.8026 145.141[34]美国—26 408.80
2[13,17]中国大陆616.42~3 278.671 228.10
≥43[13,17,34]722.30~29 760.3229 511.431[34]美国—29 760.32
2[13,17]中国大陆722.30~5 966.661 664.25
门诊自付费用13[13,17,24]78.49~1 029.02462.102[13,17]中国大陆340.64~1 029.02595.51
1[24]印度—78.49
≥23[13,17,24]99.90~1 684.09690.132[13,17]中国大陆454.26~1 684.09736.82
1[24]印度—99.90
≥42[13,17]710.54~1 667.72894.482[13,17]中国大陆710.54~1 667.72894.48
药费12[31-32]1 450.69~3 746.363 742.602[31-32]中国大陆1 450.69~3 746.363 742.60
≥22[31-32]2 820.96~4 686.434 672.602[31-32]中国大陆2 820.96~4 686.434 672.60
≥41[32]—5 326.401[32]中国大陆—5 326.40
检查费12[31-32]863.82~1 357.04864.632[31-32]中国大陆863.82~1 357.04864.63
≥22[31-32]1 196.55~2 210.941 204.072[31-32]中国大陆1 196.55~2 210.941 204.07
≥41[32]—1 353.431[32]中国大陆—1 353.43
床位费12[31-32]426.20~735.19426.712[31-32]中国大陆426.20~735.19426.71
≥22[31-32]500.31~980.26503.872[31-32]中国大陆500.31~980.26503.87
≥41[32]—539.501[32]中国大陆—539.50
护理费12[31-32]89.86~281.70281.392[31-32]中国大陆89.86~281.70281.39
≥22[31-32]200.14~356.76355.602[31-32]中国大陆200.14~356.76355.60
≥41[32]—423.081[32]中国大陆—423.08
手术费11[32]1 768.191[32]中国大陆1 768.19
≥21[32]904.931[32]中国大陆904.93
≥41[32]—744.281[32]中国大陆—744.28
), ArticleFig(id=1322608146066034822, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322608136687571011, language=CN, label=表4, caption=

不同慢性病数量下的各项费用分布及地区对比(标准化数据)

, figureFileSmall=null, figureFileBig=null, tableContent=
医疗成本类型
(年人均)
慢病数量
(种)
报告研究数量范围(元)均值(元)地区费用对比(元)
报告研究数量地区范围(元)均值(元)
医疗保健总费用111[15-16,20-22,26,28-30,33,35]117.27~44 262.2412 296.513[20-22]美国18 175.50~44 262.2420 382.97
1[16]中国台湾—13 541.96
3[26,28-29]欧元区8 394.75~19 284.588 803.33
2[30,35]新加坡2 735.68~21 968.923 081.69
2[15,33]中国大陆117.27~4 007.742 677.07
≥213[15-16,18,20-22,26,28,30,33-35,37]1 410.37~116 235.0098 136.665[20-22,34,37]美国78 336.72~116 235.00112 705.90
2[26,28]欧元区15 058.89~44 617.2330 394.90
1[16]中国台湾—28 285.12
3[15,18,33]中国大陆1 410.37~11 334.187 169.30
2[30,35]新加坡5 864.08~40 935.386 092.50
≥410[15-16,20-22,26,28,33-35]2 556.74~241 739.09142 912.224[20-22,34]美国92 497.68~241 739.09160 086.10
1[16]中国台湾—50 786.13
2[26,28]欧元区22 320.74~61 753.3746 442.01
2[15,33]中国大陆2 556.74~13 381.629 967.22
1[35]新加坡—7 534.99
医疗保健自付费用13[19,21,25]909.00~34 602.846 056.832[19,21]美国5 570.40~34 602.848 080.45
1[25]印度—909.00
≥23[19,21,25]2 070.00~58 374.1415 043.122[19,21]美国7 834.31~58 374.1415 536.95
1[25]印度—2 070.00
≥42[19,21]8 754.24~69 086.5915 341.782[19,21]美国8 754.24~69 086.5915 341.78
住院费用14[13,17,31-32]6 032.17~13 527.0113 124.464[13,17,31-32]中国大陆6 032.17~13 527.0113 124.46
≥26[13,17-18,31-32,34]4 431.88~19 448.8818 754.201[34]美国—19 448.88
5[13,17-18,31-32]中国大陆4 431.88~17 219.2716 819.78
≥45[13,17,31-32,34]10 865.36~29 760.2828 338.971[34]美国—29 760.28
4[13,17,31-32]中国大陆10 865.36~18 711.0018 121.12
住院自付费用14[13,17,23-24]1 506.49~3 966.203 574.832[23-24]印度1 506.49~3 966.203 691.75
2[13,17]中国大陆3 087.05~3 282.923 210.40
≥24[13,17,23-24]1 606.29~4 794.34 442.592[23-24]印度1 606.29~4 794.304 936.00
2[13,17]中国大陆4 506.45~4 565.744 552.42
≥42[13,17]4 787.99~5 377.464 893.872[13,17]中国大陆4 787.99~5 377.464 893.87
门诊费用12[13,17]496.77~1 348.37812.082[13,17]中国大陆496.77~1 348.37812.08
≥23[13,17,34]616.42~26 408.8026 145.141[34]美国—26 408.80
2[13,17]中国大陆616.42~3 278.671 228.10
≥43[13,17,34]722.30~29 760.3229 511.431[34]美国—29 760.32
2[13,17]中国大陆722.30~5 966.661 664.25
门诊自付费用13[13,17,24]78.49~1 029.02462.102[13,17]中国大陆340.64~1 029.02595.51
1[24]印度—78.49
≥23[13,17,24]99.90~1 684.09690.132[13,17]中国大陆454.26~1 684.09736.82
1[24]印度—99.90
≥42[13,17]710.54~1 667.72894.482[13,17]中国大陆710.54~1 667.72894.48
药费12[31-32]1 450.69~3 746.363 742.602[31-32]中国大陆1 450.69~3 746.363 742.60
≥22[31-32]2 820.96~4 686.434 672.602[31-32]中国大陆2 820.96~4 686.434 672.60
≥41[32]—5 326.401[32]中国大陆—5 326.40
检查费12[31-32]863.82~1 357.04864.632[31-32]中国大陆863.82~1 357.04864.63
≥22[31-32]1 196.55~2 210.941 204.072[31-32]中国大陆1 196.55~2 210.941 204.07
≥41[32]—1 353.431[32]中国大陆—1 353.43
床位费12[31-32]426.20~735.19426.712[31-32]中国大陆426.20~735.19426.71
≥22[31-32]500.31~980.26503.872[31-32]中国大陆500.31~980.26503.87
≥41[32]—539.501[32]中国大陆—539.50
护理费12[31-32]89.86~281.70281.392[31-32]中国大陆89.86~281.70281.39
≥22[31-32]200.14~356.76355.602[31-32]中国大陆200.14~356.76355.60
≥41[32]—423.081[32]中国大陆—423.08
手术费11[32]1 768.191[32]中国大陆1 768.19
≥21[32]904.931[32]中国大陆904.93
≥41[32]—744.281[32]中国大陆—744.28
), ArticleFig(id=1322608146170892423, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322608136687571011, language=EN, label=Table 5, caption=

Heterogeneity test and subgroup analysis of medical costs

, figureFileSmall=null, figureFileBig=null, tableContent=
医疗成本类型
(年人均)
慢病亚组纳入研究数异质性检验效应模型meta分析结果组间差异
χ2值I2(%)P值SMD95% CIZP值I2(%) / P值
医疗保健总费用≥2种 vs. 1种7[15,21,26,28,30,33,35]3 049.94100.0<0.001随机0.340.08~0.602.590.01089.9/<0.001
中国2[15~33]11.6291.0<0.001随机0.260.12~0.403.71<0.001
美国1[21]NNN随机0.380.36~0.4039.53<0.001
欧元区2[26~28]1.3425.00.250固定0.260.21~0.3011.90<0.001
新加坡2[30~35]241.06100.0<0.001随机0.49-0.22~1.201.340.180
≥4种 vs. ≥2种6[15~21~26~28~33~35]691.7899.0<0.001随机0.210.06~0.362.800.00599.5/<0.001
中国2[15~33]1.7242.0<0.001固定0.160.09~0.234.52<0.001
美国1[21]NNN随机0.120.10~0.1511.09<0.001
欧元区2[26~28]2.5561.00.110随机0.190.13~0.265.79<0.001
新加坡1[35]NNN随机0.400.39~0.41101.16<0.001
医疗保健自付费用≥2种 vs. 1种3[19~21~25]412.9799.0<0.001随机0.360.11~0.602.800.00599.4/<0.001
美国2[19~21]27.2593.0<0.001随机0.190.11~0.284.34<0.001
印度1[25]NNN随机0.860.80~0.9228.28<0.001
≥4种 vs. ≥2种N
美国2[19~21]2.6424.0<0.001固定0.090.06~0.126.27<0.001
住院费用≥2种 vs. 1种N
中国3[13~17~32]144.2699.0<0.001随机0.360.20~0.514.50<0.001
≥4种 vs. ≥2种N
中国3[13~17~32]14.7386.0<0.001随机0.120.06~0.184.14<0.001
住院自付费用≥2种 vs. 1种3[13~17~24]65.7397.0<0.001随机0.200.02~0.392.120.03098.5/<0.001
中国2[13~17]0.420.00.520固定0.290.25~0.3314.96<0.001
印度1[24]NNN随机0.01-0.04~0.070.430.660
≥4种 vs. ≥2种N
中国2[13~17]6.0383.00.010随机0.10-0.02~0.221.590.110
门诊费用≥2种 vs. 1种N
中国2[13~17]114.0299.0<0.001随机0.34-0.02~0.701.860.060
≥4种 vs. ≥2种N
中国2[13~17]67.5899.0<0.001随机0.31-0.05~0.671.700.090
门诊自付费用≥2种 vs. 1种3[13~17~24]52.9196.0<0.001随机0.200.04~0.362.420.02089.0/0.003
中国2[13~17]21.1395.0<0.001随机0.280.13~0.443.62<0.001
印度1[24]NNN随机0.02-0.05~0.100.530.590
≥4种 vs. ≥2种N
中国2[13~17]26.2896.0<0.001随机0.250.03~0.482.210.030
), ArticleFig(id=1322608146254778504, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322608136687571011, language=CN, label=表5, caption=

医疗成本异质性检验与亚组分析

, figureFileSmall=null, figureFileBig=null, tableContent=
医疗成本类型
(年人均)
慢病亚组纳入研究数异质性检验效应模型meta分析结果组间差异
χ2值I2(%)P值SMD95% CIZP值I2(%) / P值
医疗保健总费用≥2种 vs. 1种7[15,21,26,28,30,33,35]3 049.94100.0<0.001随机0.340.08~0.602.590.01089.9/<0.001
中国2[15~33]11.6291.0<0.001随机0.260.12~0.403.71<0.001
美国1[21]NNN随机0.380.36~0.4039.53<0.001
欧元区2[26~28]1.3425.00.250固定0.260.21~0.3011.90<0.001
新加坡2[30~35]241.06100.0<0.001随机0.49-0.22~1.201.340.180
≥4种 vs. ≥2种6[15~21~26~28~33~35]691.7899.0<0.001随机0.210.06~0.362.800.00599.5/<0.001
中国2[15~33]1.7242.0<0.001固定0.160.09~0.234.52<0.001
美国1[21]NNN随机0.120.10~0.1511.09<0.001
欧元区2[26~28]2.5561.00.110随机0.190.13~0.265.79<0.001
新加坡1[35]NNN随机0.400.39~0.41101.16<0.001
医疗保健自付费用≥2种 vs. 1种3[19~21~25]412.9799.0<0.001随机0.360.11~0.602.800.00599.4/<0.001
美国2[19~21]27.2593.0<0.001随机0.190.11~0.284.34<0.001
印度1[25]NNN随机0.860.80~0.9228.28<0.001
≥4种 vs. ≥2种N
美国2[19~21]2.6424.0<0.001固定0.090.06~0.126.27<0.001
住院费用≥2种 vs. 1种N
中国3[13~17~32]144.2699.0<0.001随机0.360.20~0.514.50<0.001
≥4种 vs. ≥2种N
中国3[13~17~32]14.7386.0<0.001随机0.120.06~0.184.14<0.001
住院自付费用≥2种 vs. 1种3[13~17~24]65.7397.0<0.001随机0.200.02~0.392.120.03098.5/<0.001
中国2[13~17]0.420.00.520固定0.290.25~0.3314.96<0.001
印度1[24]NNN随机0.01-0.04~0.070.430.660
≥4种 vs. ≥2种N
中国2[13~17]6.0383.00.010随机0.10-0.02~0.221.590.110
门诊费用≥2种 vs. 1种N
中国2[13~17]114.0299.0<0.001随机0.34-0.02~0.701.860.060
≥4种 vs. ≥2种N
中国2[13~17]67.5899.0<0.001随机0.31-0.05~0.671.700.090
门诊自付费用≥2种 vs. 1种3[13~17~24]52.9196.0<0.001随机0.200.04~0.362.420.02089.0/0.003
中国2[13~17]21.1395.0<0.001随机0.280.13~0.443.62<0.001
印度1[24]NNN随机0.02-0.05~0.100.530.590
≥4种 vs. ≥2种N
中国2[13~17]26.2896.0<0.001随机0.250.03~0.482.210.030
), ArticleFig(id=1322608146342858889, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322608136687571011, language=EN, label=Table 6, caption=

Cost analysis of multimorbidity in different dimensions

, figureFileSmall=null, figureFileBig=null, tableContent=
费用类型(年人均)分析维度具体分类或比较费用/范围(元)或增幅(%)
医疗保健总费用最高费用共病组合高血压/糖尿病[18]12 481.20
关节炎/糖尿病/心脏病/高血压[37]197 153.66
多病评分CCI评分[38](1~≥7分)9 885.00~47 448.00(380.00%)
累积多病评分[39](0~≥10分)10 900.00~59 836.64(448.95%)
归因成本均值差[36]2种 vs. 1种<65岁:2 417.13/≥65岁:6 585.38
3种 vs. 2种<65岁:3 430.46/≥65岁:8 217.34
4种 vs. 3种<65岁:5 123.35/≥65岁:10 605.33
≥5种 vs. 4种<65岁:13 305.90/≥65岁:24 597.59
医疗保健自付费用最高费用共病组合关节炎/糖尿病/心脏病/高血压[37]17 862.98
住院费用最高费用共病组合冠心病共病[14]2 086.18
高血压/糖尿病[18]5 114.09
慢性心力衰竭/慢性肾病(3年费用)[27]54 669.12
多病评分累积多病评分[39](0~≥10分)2 057.92~20 230.40(883.05%)
归因成本均值差[36]2种 vs. 1种<65岁:1 188.47/≥65岁:1 486.87
3种 vs. 2种<65岁:1 330.35/≥65岁:1 590.62
4种 vs. 3种<65岁:1 699.70/≥65岁:2 270.11
≥5种 vs. 4种<65岁:5 146.53/≥65岁:6 805.20
门诊费用最高费用共病组合糖尿病共病[14]790.24
归因成本均值差[36]2种 vs. 1种<65岁:1 285.67/≥65岁:1 068.80
3种 vs. 2种<65岁:1 529.76/≥65岁:1 291.70
4种 vs. 3种<65岁:1 837.98/≥65岁:1 457.60
≥5种 vs. 4种<65岁:3 311.44/≥65岁:2 571.66
门诊医师费用多病评分累积多病评分[39](0~≥10分)3 706.00~8 397.36(126.59%)
门诊非医师费用多病评分累积多病评分[39](0~≥10分)584.24~3 950.16(576.12%)
药费最高费用共病组合冠心病共病[14]1 386.53
多病评分累积多病评分[39](0~≥10分)3 252.56~10 559.92(224.66%)
归因成本均值差[36]2种 vs. 1种<65岁:1 491.82/≥65岁:2 248.86
3种 vs. 2种<65岁:1 623.23/≥65岁:2 590.86
4种 vs. 3种<65岁:2 031.48/≥65岁:2 754.24
≥5种 vs. 4种<65岁:4 276.55/≥65岁:4 326.37
), ArticleFig(id=1322608146418356362, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322608136687571011, language=CN, label=表6, caption=

不同维度多重慢病成本分析

, figureFileSmall=null, figureFileBig=null, tableContent=
费用类型(年人均)分析维度具体分类或比较费用/范围(元)或增幅(%)
医疗保健总费用最高费用共病组合高血压/糖尿病[18]12 481.20
关节炎/糖尿病/心脏病/高血压[37]197 153.66
多病评分CCI评分[38](1~≥7分)9 885.00~47 448.00(380.00%)
累积多病评分[39](0~≥10分)10 900.00~59 836.64(448.95%)
归因成本均值差[36]2种 vs. 1种<65岁:2 417.13/≥65岁:6 585.38
3种 vs. 2种<65岁:3 430.46/≥65岁:8 217.34
4种 vs. 3种<65岁:5 123.35/≥65岁:10 605.33
≥5种 vs. 4种<65岁:13 305.90/≥65岁:24 597.59
医疗保健自付费用最高费用共病组合关节炎/糖尿病/心脏病/高血压[37]17 862.98
住院费用最高费用共病组合冠心病共病[14]2 086.18
高血压/糖尿病[18]5 114.09
慢性心力衰竭/慢性肾病(3年费用)[27]54 669.12
多病评分累积多病评分[39](0~≥10分)2 057.92~20 230.40(883.05%)
归因成本均值差[36]2种 vs. 1种<65岁:1 188.47/≥65岁:1 486.87
3种 vs. 2种<65岁:1 330.35/≥65岁:1 590.62
4种 vs. 3种<65岁:1 699.70/≥65岁:2 270.11
≥5种 vs. 4种<65岁:5 146.53/≥65岁:6 805.20
门诊费用最高费用共病组合糖尿病共病[14]790.24
归因成本均值差[36]2种 vs. 1种<65岁:1 285.67/≥65岁:1 068.80
3种 vs. 2种<65岁:1 529.76/≥65岁:1 291.70
4种 vs. 3种<65岁:1 837.98/≥65岁:1 457.60
≥5种 vs. 4种<65岁:3 311.44/≥65岁:2 571.66
门诊医师费用多病评分累积多病评分[39](0~≥10分)3 706.00~8 397.36(126.59%)
门诊非医师费用多病评分累积多病评分[39](0~≥10分)584.24~3 950.16(576.12%)
药费最高费用共病组合冠心病共病[14]1 386.53
多病评分累积多病评分[39](0~≥10分)3 252.56~10 559.92(224.66%)
归因成本均值差[36]2种 vs. 1种<65岁:1 491.82/≥65岁:2 248.86
3种 vs. 2种<65岁:1 623.23/≥65岁:2 590.86
4种 vs. 3种<65岁:2 031.48/≥65岁:2 754.24
≥5种 vs. 4种<65岁:4 276.55/≥65岁:4 326.37
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全球真实世界证据的系统评价与Meta分析——多重慢病患者经济负担的跨国比较
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周梓涵 1 , 姚丽 2 , 尹佳佳 1 , 王庭瑞 1 , 李钦钦 1 , 刘焱 1
现代预防医学 | 卫生政策与管理 2025,52(21): 3968-3976
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现代预防医学 |卫生政策与管理 2025 , 52 (21) : 3968 -3976
全球真实世界证据的系统评价与Meta分析——多重慢病患者经济负担的跨国比较
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周梓涵1, 姚丽2 , 尹佳佳1, 王庭瑞1, 李钦钦1, 刘焱1
作者信息
  • 1.贵州医科大学护理学院,贵州 贵阳 561113
  • 2.贵州医科大学附属医院呼吸与危重症医学科,贵州 贵阳 550004
通讯作者:
姚丽,E-mail:
作者简介:

周梓涵(2001—),男,硕士在读,研究方向:慢性病护理与管理

Systematic review and meta-analysis of global real-world evidence: cross-country comparison of the economic burden in patients with multimorbidity
Zi-han ZHOU1, Li YAO2 , Jia-jia YIN1, Ting-rui WANG1, Qin-qin LI1, Yan LIU1
Affiliations
  • The School of Nursing, Guizhou Medical University, Guiyang, Guizhou 561113, China
出版时间: 2025-11-10 doi: 10.20043/j.cnki.MPM.202505329
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目的

评估多重及复杂多重慢病的经济负担,重点分析不同医疗保障体系下的费用差异、共病组合的协同成本效应,以及老年与非老年人群的费用增长模式。为优化疾病管理、卫生资源配置与高危人群干预策略提供证据支持。

方法

遵循Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRiSMA)和Meta-analysis of Observational Studies in Epidemiology(MOOSE)指南,系统检索中、外数据库CNKI、WanFang Date、SinoMed、PubMed、Embase、Web of Science、Scopus和Cochrane Library中收录的有关多重慢病经济负担的研究,检索建库至2024年7月。由二名研究者独立筛选文献、提取数据,使用Review Manager 5.4和Stata 18.0软件进行meta分析。

结果

共纳入27篇文献,样本量13 266 248人。结果显示,≥2种慢病患者各项年人均费用均显著高于单一慢病患者,医疗保健费用总SMD=0.34(95% CI:0.08~0.60)、自付SMD=0.36(95% CI:0.11~0.60),住院费用总SMD=0.36(95% CI:0.20~0.51)、自付SMD=0.20(95% CI:0.02~0.39),门诊费用总SMD=0.34(95% CI:-0.02~0.70)、自付SMD=0.20(95% CI:0.04~0.36)。≥4种慢病者费用亦显著高于≥2种者。地区分析显示美国、欧元区总费用普遍高于中国大陆、新加坡;总费用增长效应表现为美国(SMD=0.38,95% CI:0.36~0.40)>欧元区(SMD=0.26,95% CI:0.21~0.30)≈中国(SMD=0.26,95% CI:0.12~0.40),且亚组间差异显著(P<0.001)。此外,医疗费用在疾病模式(如糖尿病/高血压共病费用更高)、严重程度(与累积多病评分、Charlson指数正相关)及年龄组(≥65岁老年患者费用较高)间差异显著。

结论

多重慢病经济负担显著,存在地域与人群差异。亟需优化疾病管理、完善医疗保障并制定针对性卫生政策以减轻负担。未来研究应聚焦不同共病模式的经济负担,开发精准干预措施。

多重慢病  /  复杂多重慢病  /  经济负担  /  系统评价  /  Meta分析
Objective

To assess the economic burden of multimorbidity and complex multimorbidity, focusing on cost variations across medical insurance system, synergistic cost effects of multimorbidity clusters, and expenditure patterns among older versus non-older adults, thereby providing evidence to optimize disease management, health resource allocation, and targeted interventions for high-risk populations.

Methods

Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Meta-analysis Of Observational Studies in Epidemiology (MOOSE) guidelines, CNKI, WanFang Data, SinoMed, PubMed, Embase, Web of Science,Scopus, and Cochrane Library were systematically searched for studies on the economic burden of multimorbidity until July 2024. Two reviewers independently screened studies and extracted data. Meta-analysis was performed using Review Manager 5.4 and Stata 18.0.

Results

A total of 27 studies with 13 266 248 participants were included. Patients with multimorbidity had significantly higher annual per capita costs across all categories compared to those with a single condition. Healthcare costs (Total: SMD=0.34, 95% CI: 0.08-0.60; Out-of-pocket: SMD=0.36, 95% CI: 0.11-0.60), hospitalization costs (Total: SMD=0.36, 95% CI: 0.20-0.51; Out-of-pocket SMD=0.20, 95% CI: 0.02-0.39), and outpatient costs (Total: SMD=0.34, 95% CI:-0.02-0.70; Out-of-pocket: SMD=0.20, 95% CI: 0.04-0.36). Costs were also higher for ≥4 conditions than for ≥2.Geographically, total costs were higher in the US and the Eurozone than in mainland China and Singapore. The cost increase effect was highest in the US (SMD=0.38, 95% CI: 0.36-0.40), followed by Eurozone (SMD=0.26, 95% CI: 0.21-0.30) and China (SMD=0.26, 95% CI: 0.12-0.40), with significant subgroup differences (P<0.001). Costs varied by multimorbidity patterns (e.g., higher for diabetes/hypertension), severity (positively correlated with cumulative illness scores and CCI), and age (higher in adults ≥65 years).

Conclusion

Multimorbidity imposes a significant economic burden with regional and group variations. Optimized disease management, improved health insurance coverage, and targeted health policies to reduce the burden are urgently needed. Future studies should focus on economic impacts of specific multimorbidity patterns to develop precise interventions.

Multimorbidity  /  Complex multimorbidity  /  Economic burden  /  Systematic review  /  Meta-analysis
周梓涵, 姚丽, 尹佳佳, 王庭瑞, 李钦钦, 刘焱. 全球真实世界证据的系统评价与Meta分析——多重慢病患者经济负担的跨国比较. 现代预防医学, 2025 , 52 (21) : 3968 -3976 . DOI: 10.20043/j.cnki.MPM.202505329
Zi-han ZHOU, Li YAO, Jia-jia YIN, Ting-rui WANG, Qin-qin LI, Yan LIU. Systematic review and meta-analysis of global real-world evidence: cross-country comparison of the economic burden in patients with multimorbidity[J]. Modern Preventive Medicine, 2025 , 52 (21) : 3968 -3976 . DOI: 10.20043/j.cnki.MPM.202505329
全球人口老龄化加速使慢性病成为主要健康威胁[1]。中国老龄化形势严峻,预计2035年60岁及以上人口将突破4亿,占比超30%,进入重度老龄化阶段[2]。多重慢病(≥2种)与复杂多重慢病(≥4种)患病率显著上升[3-4],导致患者躯体功能障碍、死亡风险及医疗支出显著增加[5-6]。研究表明,多重慢病患者医疗支出可达单病患者的数倍,且因治疗复杂需更频繁的医疗服务[7-8]。当前多重慢病经济负担的系统性研究仍不足:国内多聚焦单一或少数疾病组合[9-10],缺乏对多重/复杂多重慢病的量化分析[11],并且中低收入国家相关证据尤为匮乏[12]。本研究旨在通过全球真实世界证据的系统评价与meta分析,量化评估多重及复杂多重慢病在不同国家、地区和人群中的经济负担,重点解析:不同医疗保障体系下的费用差异;呈现协同成本效应(超叠加成本)的共病组合;老年与非老年人群的医疗费用增长模式特征;为优化疾病管理、卫生资源配置与高危人群干预策略提供证据支持。
遵循Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRiSMA)和Meta-analysis of Observational Studies in Epidemiology(MOOSE)指南,并在PROSPERO(CRD420251115613)上前瞻性注册。系统检索中文数据库CNKI、WanFang Date、SinoMed以及英文数据库PubMed、Embase、Web of Science、Scopus、Cochrane Library,收集建库至2024年7月发表的多重慢病经济负担研究。采用主题词与自由词结合策略,核心检索词包括:Multimorbidity,Multiple chronic diseases,Multiple Chronic Illnesses,Multiple Chronic Health Conditions,comorbidity;Health Expenditures,cost*,financ*,economic*,expenditure*,expense*,spend*,payment*等;共病、多重慢病、多重慢性病、慢性病共病、慢性合并症、合并慢性疾病,经济性、经济学评价、药物经济、成本、成本效果、成本效益、最小成本、经济负担、疾病负担、费用等。以PubMed数据库为例检索策略见表1。
(1)研究对象:多重慢病患者(不限年龄、国别);(2)结局指标:直接医疗成本、自付医疗费用或卫生支出数据(如医疗保健费、住院费、门诊费、药品费等);(3)研究类型:观察性研究(横断面、队列、病例对照、纵向)及疾病成本研究;(4)数据来源:医疗记录、管理数据库、医患报告等客观数据;(5)文献语种:中文或英文。
(1)非医疗相关支出(如交通、住宿费用等)、仅报告增量成本或间接成本(如误工损失、照护支出等);(2)单一慢病研究、非人类研究、综述/荟萃分析、定性研究、会议摘要;(3)未实际测量多重慢病(如仅研究特定疾病合并症);(4)文献质量低或无法获取全文。
由二名研究者独立筛选文献、提取资料,如有争议与第三名研究者协商决定。内容提取:(1)文献特征:作者/年份、地区、调查时间、研究设计;(2)样本特征:人群、年龄、性别、样本量;(3)疾病数据:多重慢病定义、测量方法、患病人数;(4)成本数据:费用类型、总额、构成、货币年份。质量评价,横断面研究采用美国卫生保健质量和研究机构(agency for healthcare research and quality,AHRQ)的11条评价标准,总分≥8分为高质量,4~7分为中等质量,0~3分为低质量。队列研究采用纽卡斯尔-渥太华量表(Newcastle-Ottawa scale,NOS)进行评价,满分9分,≥7分为高质量,4~6分为中等质量,1~3分为低质量。
采用Stata18.0测算多重慢病合并多病率(95% CI),成本分析用RevMan 5.4:(1)连续性变量采用标准化均数差(standardized mean difference,SMD)或加权均数差(weighted mean difference, WMD),中位数统一转换为(均值±标准差);(2)数据标准化:费用经消费价格指数(CPI)与汇率贴现至2023年人民币水平,流程见图1,基于样本量加权计算合并平均值;(3)异质性采用Q检验(α=0.1)及I2值评估,I2 ≤50%用固定效应模型,I2>50%采用随机效应模型;(4)通过亚组分析、模型调整及逐篇剔除进行敏感性分析。(5)发表偏倚采用Egger检验与漏斗图评估,P>0.05提示无明显发表偏倚。
初检获文献3 519篇,逐层筛选后纳入27篇[13-39](中文6,英文21),筛选流程见图2。
纳入研究的基本特征见表2。质量评价显示:1篇纵向和6篇队列研究,NOS评分6~8分(中质2篇,高质4篇);21篇横断面研究,AHRQ评分6~10分(中质12篇,高质9篇)。
总体多病率为42.61%,亚组间差异显著(P<0.001),由高至低依次为:住院人群(83.89%)、慢性病患者(62.25%)、社区人群(36.75%)、农村人群(8.92%),见表3。
 除个别费用外(手术费则呈反向梯度),各项费用均随慢病数量增加而显著上升,见表4。Meta分析见表5,≥2种 vs. 1种慢病:医疗保健总费用、医疗保健自付费用、住院费用、住院自付费用、门诊费用、门诊自付费用的SMD分别为0.34、0.36、0.36、0.20、0.34、0.20(P值分别为0.010、0.005、<0.001、0.030、0.060、0.020);≥4种 vs. ≥2种慢病:医疗保健总费用、医疗保健自付费用、住院费用、门诊费用、门诊自付费用的SMD分别为0.21、0.09、0.12、0.31、0.25(P值分别为0.005、<0.001、<0.001、0.090)。此外,儿童慢病数量与医疗保健总费用呈强正相关(1种~≥2种~≥4种:32 431元~83 861.37元~241 739.09元)[22];≥65岁患者门诊费用的各项归因成本均值差均低于<65岁患者。见表6[36]。
采用逐一剔除文献的方法进行敏感性分析,剔除前后合并效应量均未发生明显变化,表明结果稳定性较好。多病率漏斗图对称性欠佳,提示可能存在发表偏倚,见图3。但Egger检验P=0.911,表明无足够证据证明存在发表偏倚,需谨慎判断发表偏倚。
Meta分析显示,慢性病数量增加(1种~≥2种~≥4种)与医疗费用增长存在显著的梯度关联,且呈现区域异质性。(1)高负担区(如美国):市场化医疗体系下,慢性病费用基数最高,增长效应最强(≥2种 vs. 1种:总费用SMD=0.38,P<0.001;≥4种慢病总费用均值远超中国),凸显私立主导和保险碎片化体系应对多病共存的高成本弊端[40]。(2)政策缓冲区:中国依托公立体系和广覆盖医保(参保率>95%),有效控制费用增幅(总费用SMD:≥2种 vs. 1种为0.26;≥4种 vs. ≥2种为0.16)和绝对水平。中国数据表明多病显著增加住院费用和自付负担,门诊自付负担增长较突出,提示需加强门诊保障;医保对高额住院费用具有兜底作用[41]。新加坡强制储蓄型医保(MediSave)在应对≥4种慢病时增长效应显著(SMD=0.40),提示其对超多重疾病负担控制面临挑战[42]。欧元区费用增长效应介于中美之间(总费用SMD:≥2种 vs. 1种为0.26;≥4种 vs. ≥2种为0.19),其混合型医保体系在平衡可及性与成本控制方面效果显现。(3)保障薄弱区(如印度):总自付费用增长效应异常突出(≥2种 vs. 1种SMD= 0.86),而住院/门诊自付增长不显著,提示因保障缺位,患者可能限制服务利用,灾难性支出风险高[43]。
疾病数量累积显著推升医疗费用(≥2种 vs. 1种:总费用SMD=0.34;≥4 vs. ≥2种:SMD=0.21),边际效应随数量增加递减,但绝对负担持续加重。严重程度叠加(如CCI评分1~≥7分患者总费用增幅达380%、累积多病评分0~≥10分增幅达449%)是比单纯数量更敏感的费用预测指标,揭示多病共存由于病情复杂化(器官交互损伤、治疗冲突)指数级放大资源消耗[44]。
≥65岁患者总费用及归因成本更高,符合常规认知。但该人群门诊费用归因成本显著低于年轻群体(如≥5种 vs. 4种慢病:2 571.66元 vs. 3 311.44元)。此现象可能源于:(1)政策缓冲(如中国基层免挂号费、慢病长处方);(2)老年群体住院率更高,部分门诊需求转移至住院服务;(3)行为适应差异(在职者多依赖高价特需门诊,老年人更依赖基层门诊)[45]。
特定疾病组合呈现超叠加费用负担:(1)代谢-循环系统共病(如高血压/糖尿病);(2)器官衰竭共病(如慢性心力衰竭/慢性肾病)。这可能与病情复杂、治疗难度和并发症风险高有关,提示器官系统交互的协同损伤效应加剧资源消耗[46]。
(1)老年群体:归因成本显著更高(如≥5种 vs. 4种 慢病归因成本:≥65岁24 597.59元/<65岁13 305.90元),凸显整合慢病管理与养老照护的紧迫性[47]。(2)儿童群体:≥4种慢病费用高昂(241 739.09元),提示特殊人群保障缺口。(3)随慢病数量增加,手术费呈反常下降趋势(1种:1 768.19元,≥4种:744.28元),核心机制为共病增加围术期风险,限制手术适应症。
本研究揭示了多重慢病负担的三重异质性:区域梯度分化(美>欧/中>印)、年龄利用悖论(老年高总负担-低门诊成本)、共病协同损伤(心肾组合费用激增)。为破解困境,建议:(1)体系改革:高负担区推行共病导向支付改革(如DRG),抑制私立体系逐利性费用膨胀[48];保障薄弱区优先扩大门诊慢病报销,完善医疗保障体系,扩大覆盖范围,降低自付费用;政策缓冲区(如中国)强化门诊共病保障与分级诊疗[49]。(2)人群聚焦:老年群体整合医保与养老支付;儿童群体设立专项基金;在职患者发展“职场-社区”联动门诊。(3)临床优化:制定共病组合指南,革新手术准入评估[50]。(4)预防前移:基层聚焦高危人群与共病组合筛查干预,赋能患者管理交互用药。通过“体系-人群-临床-预防”联动,实现成本可控与健康公平。
(1)纳入研究总体异质性较高,限制外推;(2)区域成本可比性受物价、医保政策、通胀差异影响;(3)部分结局纳入研究<10篇,Egger检验效能不足;(4)未量化共病间交互效应;(5)未纳入间接成本(如误工损失、照护支出),可能低估总体负担;(6)未校正不同国家医保报销比例差异,影响直接医疗费用的跨体系比较;(7)关键指标定义差异(如CCI评分、累积多病评分的疾病权重与截断值不一)可能引入合并偏倚。未来需统一成本核算标准、开发医保支付差异校正模型、制定CCI等工具的多病研究标准化定义,深化共病组合经济学研究,构建慢病组合-费用关联矩阵以支持精准保障。
  • 贵州省科技厅资助项目(黔科合成果LC(2025)一般057)
  • 中华护理学会2023年度科研课题项目(ZHKYQ202316)
  • 贵阳市科技计划项目([2022]-4-2-2号)
  • 贵州医科大学附属医院国家自然科学基金培育计划(gyfynsfc[2023]-35)
  • 贵州医科大学附属医院护理科研基金项目(gyfyhlxz-2023-2)
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2025年第52卷第21期
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doi: 10.20043/j.cnki.MPM.202505329
  • 接收时间:2025-05-24
  • 首发时间:2026-10-29
  • 出版时间:2025-11-10
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  • 收稿日期:2025-05-24
基金
贵州省科技厅资助项目(黔科合成果LC(2025)一般057)
中华护理学会2023年度科研课题项目(ZHKYQ202316)
贵阳市科技计划项目([2022]-4-2-2号)
贵州医科大学附属医院国家自然科学基金培育计划(gyfynsfc[2023]-35)
贵州医科大学附属医院护理科研基金项目(gyfyhlxz-2023-2)
作者信息
    1.贵州医科大学护理学院,贵州 贵阳 561113
    2.贵州医科大学附属医院呼吸与危重症医学科,贵州 贵阳 550004

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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
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