Article(id=1322609031823340376, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1322609030938346427, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202506355, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1750608000000, receivedDateStr=2025-06-23, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793264166074, onlineDateStr=2026-10-29, pubDate=1764000000000, pubDateStr=2025-11-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793264166074, onlineIssueDateStr=2026-10-29, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793264166074, creator=13701087609, updateTime=1793264166074, updator=13701087609, issue=Issue{id=1322609030938346427, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='22', pageStart='4033', pageEnd='4224', issueExtLink='null', onlineDate='null', pubDate='1764000000000', pubDateStr='2025-11-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793264165863, creator='13701087609', updateTime=1793264299902, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1322609593264489401, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1322609030938346427, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1322609593264489402, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1322609030938346427, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=4132, endPage=4137, ext={EN=ArticleExt(id=1322609032255353689, articleId=1322609031823340376, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Analysis of influencing factors on payment differences in spinal surgery patients under DRG payment, columnId=1228016567846367388, journalTitle=Modern Preventive Medicine, columnName=Health Policy and Management, runingTitle=null, highlight=null, articleAbstract=
Objective

To explore the influencing factors of payment differences in patients undergoing spine-related surgeries under the Diagnosis-Related Groups(DRG)payment system, and to provide evidencefor improving hospital medical insurance fund surplus and promoting high-quality hospital development.

Methods

We collected data from 1 798 inpatients undergoing spine-related surgeries and grouped under the DRG system, along with their medical insurance settlement cost information, at a large Grade-A tertiary hospital in Guangxi from January 1,2022 to December 31,2024. Descriptive statistics, univariate analysis, and multivariate regression models were employed to analyze factors influencing medical insurance payment differences. Structural equation modeling was further applied to validate correlations among variables.

Results

Univariate analysis revealed that age, average length of stay, ADRG group, insurance fund type, case type, presence of complications, primary diagnosis group, and VBP participation status were significant factors influencing medical insurance payment differences in spine-related surgical patients(P<0.05). The results of multiple linear regression analysis indicated that the top three factors influencing payment differences were ADRG group(β=-1.704,t=-29.369,P<0.001), centralized procurement status(β=-1.244,t=-17.705,P<0.001), and case type(β=-1.085,t=-11.257,P<0.001). Structural equation modeling showed ADRG group as the most influential factor with a path coefficient of 0.55, followed by procurement policy(0.36)and case type(0.21).

Conclusion

ADRG grouping is the primary determinant of payment differences. Under DRG payment systems, healthcare authorities should optimize disease group weights to reflect actual medical resource consumption and technical complexity. They should actively promote centralized volume procurement of high-value consumables while strengthening synergies between DRG payment and procurement policies. Hospitals need to optimize clinical pathways, control medical costs through rational diagnosis and treatment, thereby improving DRG payment difference levels.

, authors=Ying ZHOU1, Feng-lei CHEN1, Jian-hua MENG1, Neng-hai BIN1, Yu-yin HU2, Jing QIAN1, authorsList=Ying ZHOU, Feng-lei CHEN, Jian-hua MENG, Neng-hai BIN, Yu-yin HU, Jing QIAN, authorCompany=null, correspAuthors=Jing QIAN, 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=1322609033173906268, articleId=1322609031823340376, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=DRG付费下脊柱有关手术患者支付差影响因素分析, columnId=1228016568014139551, journalTitle=现代预防医学, columnName=卫生政策与管理, runingTitle=null, highlight=null, articleAbstract=
目的

探讨疾病诊断相关分组(DRG)付费下脊柱有关手术患者支付差的影响因素,为合理控制医疗成本,提高医院医保基金结余提供参考。

方法

收集广西某大型三甲医院2022年1月1日至2024年12月31日住院收治的1 798例脊柱有关手术DRG入组患者资料及医保结算费用信息,利用描述性统计、单因素分析及多元回归模型分析患者医保支付差的影响因素,通过结构方程模型验证各变量之间的相关性。

结果

单因素分析结果显示,年龄、平均住院日、ADRG组、基金类型、病例类型、是否并发症、主诊组、是否集采均为脊柱有关手术患者医保支付差的影响因素(P<0.05);多元线性回归分析结果提示,对支付差影响最大的前三位因素分别是ADRG组(β=-1.704,t=-29.369,P<0.001)、是否集采(β=-1.244,t=-17.705,P<0.001)和病例类型(β=-1.085,t=-11.257,P<0.001);结构方程模型结果显示ADRG组是支付差的最大影响因素,路径系数是0.55,其次是集采政策(0.36),再次是病例类型(0.21)。

结论

ADRG组是支付差的最大影响因素,DRG付费下医保行政部门应合理设置各病组的权重,体现真实的医疗消耗和技术难度;积极推动高值耗材集中带量采购政策,进一步强化DRG付费与集采政策的协同联动;同时医院要优化临床路径,合理诊疗的前提下控制医疗成本,从而提高DRG支付差水平。

, authors=周颖1, 陈凤磊1, 蒙健华1, 宾能海1, 胡雨茵2, 钱静1, authorsList=周颖, 陈凤磊, 蒙健华, 宾能海, 胡雨茵, 钱静, authorCompany=null, correspAuthors=钱静, authorNote=

周颖(1990—),男,硕士,主治医师,研究方向:医保管理

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钱静,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=2VRMqv+NPlRBisK7Y7GFpw==, magXml=JeXWRyY/jPZLJMTxPjy7KA==, pdfUrl=null, pdf=k+ClWlxgO1vs2Anm3tBp4A==, pdfFileSize=782849, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=fXWaov6orLcFIExSchrNOw==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=oqLyuQ0H7TErBLxIGPOqUA==, mapNumber=null, fund=null)}, authors=[Author(id=1322609033660445539, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322609031823340376, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1322609035463996261, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322609031823340376, authorId=1322609033660445539, language=EN, stringName=Ying ZHOU, firstName=Ying, middleName=null, lastName=ZHOU, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=Medical Insurance Management Office, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1322609035552076646, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322609031823340376, authorId=1322609033660445539, language=CN, stringName=周颖, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1.广西医科大学第一附属医院,广西 南宁 530021, bio={"content":"

周颖(1990—),男,硕士,主治医师,研究方向:医保管理

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China Health Insurance, 2022 (8): 103-105.(In Chinese), articleTitle=Research on impact of centralized procurement on hospitalization expenses of patients with coronary stent implantation, refAbstract=null)], funds=[Fund(id=1322609040455218070, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322609031823340376, awardId=Z-A20240558, language=CN, fundingSource=广西卫健委自筹经费科研课题(Z-A20240558), fundOrder=null, country=null), Fund(id=1322609040526521239, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322609031823340376, awardId=YYZS2023039, language=CN, fundingSource=广西医科大学第一附属医院自设培育项目(YYZS2023039), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1322609033484284765, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322609031823340376, xref=1., ext=[AuthorCompanyExt(id=1322609033492673374, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322609031823340376, companyId=1322609033484284765, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Medical Insurance Management Office, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, China), AuthorCompanyExt(id=1322609033501061983, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322609031823340376, companyId=1322609033484284765, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.广西医科大学第一附属医院,广西 南宁 530021)]), AuthorCompany(id=1322609033580753760, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322609031823340376, xref=2., ext=[AuthorCompanyExt(id=1322609033589142369, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322609031823340376, companyId=1322609033580753760, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.南宁春瑞康华医院)])], figs=[ArticleFig(id=1322609037817000842, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322609031823340376, language=EN, label=Fig.1, caption=Structural equation model of influencing factors on DRG payment difference, figureFileSmall=5SuGEykkj133XN4egsiNaQ==, figureFileBig=fXWaov6orLcFIExSchrNOw==, tableContent=null), ArticleFig(id=1322609037896692619, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322609031823340376, language=CN, label=图1, caption=DRG支付差影响因素结构方程模型, figureFileSmall=5SuGEykkj133XN4egsiNaQ==, figureFileBig=fXWaov6orLcFIExSchrNOw==, tableContent=null), ArticleFig(id=1322609038093824908, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322609031823340376, language=EN, label=Table 1, caption=

Cost comparison before and after centralized procurement

, figureFileSmall=null, figureFileBig=null, tableContent=
项目集采前(707例)集采后(1 091例)t值P值
平均住院日(天)6.066.670.0360.849
例均检查费(元)4 177.584 210.892.6840.333
例均耗材费(元)45 014.3014 470.24514.858<0.001
例均治疗费(元)7 641.749 333.0917.927<0.001
例均总费用(元)58 842.6830 365.11299.409<0.001
例均支付差(元)-2 159.1413 277.3218.076<0.001
), ArticleFig(id=1322609038177710989, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322609031823340376, language=CN, label=表1, caption=

集采前后的费用对比

, figureFileSmall=null, figureFileBig=null, tableContent=
项目集采前(707例)集采后(1 091例)t值P值
平均住院日(天)6.066.670.0360.849
例均检查费(元)4 177.584 210.892.6840.333
例均耗材费(元)45 014.3014 470.24514.858<0.001
例均治疗费(元)7 641.749 333.0917.927<0.001
例均总费用(元)58 842.6830 365.11299.409<0.001
例均支付差(元)-2 159.1413 277.3218.076<0.001
), ArticleFig(id=1322609039842849678, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322609031823340376, language=EN, label=Table 2, caption=

Univariate analysis of influencing factors on DRG payment difference

, figureFileSmall=null, figureFileBig=null, tableContent=
项目病例数
(例)
占比
(%)
例均支付差
(元)
t/F值P值
性别0.5760.982
男79944.448 423.45
女99955.568 376.72
年龄段(岁)6.4610.002
≤4533518.638 954.90
46~6065836.608 284.19
≥6180544.775 600.20
平均住院日(天)17.026<0.001
≤448927.204 980.56
5~898854.959 332.73
≥932117.854 058.62
ADRG组236.778<0.001
IB1965.3419 656.24
IB21 15664.2911 698.93
IB354630.37-4 490.69
基金类型32.419<0.001
省本级医保1538.518 814.52
省内异地医保33718.7410 477.93
市职工医保34719.3013 067.96
市居民医保96153.453 688.64
病例类型234.185<0.001
低倍率病例341.89-3 354.44
正常倍率病例1 58888.3210 016.81
高倍率病例1769.79-16 099.96
并发症类型12.965<0.001
无并发症53329.645 443.25
一般并发症1 07659.847 089.37
严重并发症18910.5112 855.18
主诊组43.612<0.001
主诊组A21511.9613 655.72
主诊组B30817.1314 550.18
主诊组C21712.0710 267.21
主诊组D33718.74624.80
主诊组E23212.90-1 216.20
主诊组F48927.206 922.76
是否集采418.495<0.001
是1 09160.6813 277.32
否70739.32-2 159.14
), ArticleFig(id=1322609039930930063, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322609031823340376, language=CN, label=表2, caption=

DRG支付差影响因素的单因素分析

, figureFileSmall=null, figureFileBig=null, tableContent=
项目病例数
(例)
占比
(%)
例均支付差
(元)
t/F值P值
性别0.5760.982
男79944.448 423.45
女99955.568 376.72
年龄段(岁)6.4610.002
≤4533518.638 954.90
46~6065836.608 284.19
≥6180544.775 600.20
平均住院日(天)17.026<0.001
≤448927.204 980.56
5~898854.959 332.73
≥932117.854 058.62
ADRG组236.778<0.001
IB1965.3419 656.24
IB21 15664.2911 698.93
IB354630.37-4 490.69
基金类型32.419<0.001
省本级医保1538.518 814.52
省内异地医保33718.7410 477.93
市职工医保34719.3013 067.96
市居民医保96153.453 688.64
病例类型234.185<0.001
低倍率病例341.89-3 354.44
正常倍率病例1 58888.3210 016.81
高倍率病例1769.79-16 099.96
并发症类型12.965<0.001
无并发症53329.645 443.25
一般并发症1 07659.847 089.37
严重并发症18910.5112 855.18
主诊组43.612<0.001
主诊组A21511.9613 655.72
主诊组B30817.1314 550.18
主诊组C21712.0710 267.21
主诊组D33718.74624.80
主诊组E23212.90-1 216.20
主诊组F48927.206 922.76
是否集采418.495<0.001
是1 09160.6813 277.32
否70739.32-2 159.14
), ArticleFig(id=1322609039998038928, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322609031823340376, language=EN, label=Table 3, caption=

Variable assignment for univariate analysis of DRG payment difference

, figureFileSmall=null, figureFileBig=null, tableContent=
变量名称变量赋值
年龄段X1≤45岁=1,46~60岁=2,≥61岁=3
平均住院日X2≤4天=1,5~8天=2,≥9天=3
ADRG组X3IB1=1,IB2=2,IB3=3
基金类型X4省本级医保=1,省内异地=2,市职工医保=3,市居民医保=4
病例类型X5低倍率=1,正常倍率=2,高倍率=3
并发症类型X6无并发症=1,一般并发症=2,严重并发症=3,不分是否合并症=4
主诊组X7主诊组A=1,主诊组B=2,主诊组C=3,主诊组D=4,主诊组E=5,主诊组F=6
是否集采X8是=1,否=2
), ArticleFig(id=1322609040073536401, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322609031823340376, language=CN, label=表3, caption=

DRG支付差单因素分析变量赋值情况表

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变量名称变量赋值
年龄段X1≤45岁=1,46~60岁=2,≥61岁=3
平均住院日X2≤4天=1,5~8天=2,≥9天=3
ADRG组X3IB1=1,IB2=2,IB3=3
基金类型X4省本级医保=1,省内异地=2,市职工医保=3,市居民医保=4
病例类型X5低倍率=1,正常倍率=2,高倍率=3
并发症类型X6无并发症=1,一般并发症=2,严重并发症=3,不分是否合并症=4
主诊组X7主诊组A=1,主诊组B=2,主诊组C=3,主诊组D=4,主诊组E=5,主诊组F=6
是否集采X8是=1,否=2
), ArticleFig(id=1322609040144839570, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322609031823340376, language=EN, label=Table 4, caption=

Results of multivariate linear regression analysis on DRG payment difference

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变量非标准化回归系数标准误标准回归系数t值P值
常量10.4480.29535.397<0.001
年龄段-0.1070.039-0.046-2.7260.006
平均住院日-0.4600.048-0.176-9.650<0.001
ADRG组-1.7040.058-0.533-29.369<0.001
基金类型-0.1950.029-0.114-6.616<0.001
病例类型-1.0850.096-0.208-11.257<0.001
并发症类型0.0590.0520.0411.1540.368
主诊组-0.0700.018-0.070-3.913<0.001
是否集采-1.2440.070-0.350-17.705<0.001
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DRG支付差多元线性回归分析结果

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变量非标准化回归系数标准误标准回归系数t值P值
常量10.4480.29535.397<0.001
年龄段-0.1070.039-0.046-2.7260.006
平均住院日-0.4600.048-0.176-9.650<0.001
ADRG组-1.7040.058-0.533-29.369<0.001
基金类型-0.1950.029-0.114-6.616<0.001
病例类型-1.0850.096-0.208-11.257<0.001
并发症类型0.0590.0520.0411.1540.368
主诊组-0.0700.018-0.070-3.913<0.001
是否集采-1.2440.070-0.350-17.705<0.001
), ArticleFig(id=1322609040300028820, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322609031823340376, language=EN, label=Table 5, caption=

Goodness of fit evaluation results of structural equation model

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模型拟合指标结果判断标准
绝对拟合指数
拟合优度指数(GFI)0.921取值在0~1,>0.9表示拟合好
调整的拟合优度指数(AGFI)0.938取值在0~1,>0.9表示拟合好
近似误差均方根(RMSEA)0.004<0.05表示拟合好
χ2/v5.376<3表示拟合好
相对拟合指数
规范拟合指数(NFI)0.912取值在0~1,>0.9表示拟合好
增值拟合指数(IF1)0.925>0.9表示拟合好
比较拟合指数(CFI)0.913取值在0~1,>0.9表示拟合好
), ArticleFig(id=1322609040362943381, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1322609031823340376, language=CN, label=表5, caption=

结构方程模型拟合优度评价结果

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模型拟合指标结果判断标准
绝对拟合指数
拟合优度指数(GFI)0.921取值在0~1,>0.9表示拟合好
调整的拟合优度指数(AGFI)0.938取值在0~1,>0.9表示拟合好
近似误差均方根(RMSEA)0.004<0.05表示拟合好
χ2/v5.376<3表示拟合好
相对拟合指数
规范拟合指数(NFI)0.912取值在0~1,>0.9表示拟合好
增值拟合指数(IF1)0.925>0.9表示拟合好
比较拟合指数(CFI)0.913取值在0~1,>0.9表示拟合好
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DRG付费下脊柱有关手术患者支付差影响因素分析
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周颖 1 , 陈凤磊 1 , 蒙健华 1 , 宾能海 1 , 胡雨茵 2 , 钱静 1
现代预防医学 | 卫生政策与管理 2025,52(22): 4132-4137
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现代预防医学 |卫生政策与管理 2025 , 52 (22) : 4132 -4137
DRG付费下脊柱有关手术患者支付差影响因素分析
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周颖(1990—),男,硕士,主治医师,研究方向:医保管理

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周颖(1990—),男,硕士,主治医师,研究方向:医保管理

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周颖1, 陈凤磊1, 蒙健华1, 宾能海1, 胡雨茵2, 钱静1
作者信息
  • 1.广西医科大学第一附属医院,广西 南宁 530021
  • 2.南宁春瑞康华医院
通讯作者:
钱静,E-mail:
作者简介:

周颖(1990—),男,硕士,主治医师,研究方向:医保管理

Analysis of influencing factors on payment differences in spinal surgery patients under DRG payment
Ying ZHOU1, Feng-lei CHEN1, Jian-hua MENG1, Neng-hai BIN1, Yu-yin HU2, Jing QIAN1
Affiliations
  • Medical Insurance Management Office, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, China
出版时间: 2025-11-25 doi: 10.20043/j.cnki.MPM.202506355
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目的

探讨疾病诊断相关分组(DRG)付费下脊柱有关手术患者支付差的影响因素,为合理控制医疗成本,提高医院医保基金结余提供参考。

方法

收集广西某大型三甲医院2022年1月1日至2024年12月31日住院收治的1 798例脊柱有关手术DRG入组患者资料及医保结算费用信息,利用描述性统计、单因素分析及多元回归模型分析患者医保支付差的影响因素,通过结构方程模型验证各变量之间的相关性。

结果

单因素分析结果显示,年龄、平均住院日、ADRG组、基金类型、病例类型、是否并发症、主诊组、是否集采均为脊柱有关手术患者医保支付差的影响因素(P<0.05);多元线性回归分析结果提示,对支付差影响最大的前三位因素分别是ADRG组(β=-1.704,t=-29.369,P<0.001)、是否集采(β=-1.244,t=-17.705,P<0.001)和病例类型(β=-1.085,t=-11.257,P<0.001);结构方程模型结果显示ADRG组是支付差的最大影响因素,路径系数是0.55,其次是集采政策(0.36),再次是病例类型(0.21)。

结论

ADRG组是支付差的最大影响因素,DRG付费下医保行政部门应合理设置各病组的权重,体现真实的医疗消耗和技术难度;积极推动高值耗材集中带量采购政策,进一步强化DRG付费与集采政策的协同联动;同时医院要优化临床路径,合理诊疗的前提下控制医疗成本,从而提高DRG支付差水平。

疾病诊断相关分组  /  支付差  /  影响因素  /  集采  /  结构方程模型
Objective

To explore the influencing factors of payment differences in patients undergoing spine-related surgeries under the Diagnosis-Related Groups(DRG)payment system, and to provide evidencefor improving hospital medical insurance fund surplus and promoting high-quality hospital development.

Methods

We collected data from 1 798 inpatients undergoing spine-related surgeries and grouped under the DRG system, along with their medical insurance settlement cost information, at a large Grade-A tertiary hospital in Guangxi from January 1,2022 to December 31,2024. Descriptive statistics, univariate analysis, and multivariate regression models were employed to analyze factors influencing medical insurance payment differences. Structural equation modeling was further applied to validate correlations among variables.

Results

Univariate analysis revealed that age, average length of stay, ADRG group, insurance fund type, case type, presence of complications, primary diagnosis group, and VBP participation status were significant factors influencing medical insurance payment differences in spine-related surgical patients(P<0.05). The results of multiple linear regression analysis indicated that the top three factors influencing payment differences were ADRG group(β=-1.704,t=-29.369,P<0.001), centralized procurement status(β=-1.244,t=-17.705,P<0.001), and case type(β=-1.085,t=-11.257,P<0.001). Structural equation modeling showed ADRG group as the most influential factor with a path coefficient of 0.55, followed by procurement policy(0.36)and case type(0.21).

Conclusion

ADRG grouping is the primary determinant of payment differences. Under DRG payment systems, healthcare authorities should optimize disease group weights to reflect actual medical resource consumption and technical complexity. They should actively promote centralized volume procurement of high-value consumables while strengthening synergies between DRG payment and procurement policies. Hospitals need to optimize clinical pathways, control medical costs through rational diagnosis and treatment, thereby improving DRG payment difference levels.

Diagnosis Related Groups  /  Payment difference  /  Influencing factors  /  Centralized volume-based procurement  /  Structural equation modeling
周颖, 陈凤磊, 蒙健华, 宾能海, 胡雨茵, 钱静. DRG付费下脊柱有关手术患者支付差影响因素分析. 现代预防医学, 2025 , 52 (22) : 4132 -4137 . DOI: 10.20043/j.cnki.MPM.202506355
Ying ZHOU, Feng-lei CHEN, Jian-hua MENG, Neng-hai BIN, Yu-yin HU, Jing QIAN. Analysis of influencing factors on payment differences in spinal surgery patients under DRG payment[J]. Modern Preventive Medicine, 2025 , 52 (22) : 4132 -4137 . DOI: 10.20043/j.cnki.MPM.202506355
近年来,在疾病诊断相关分组(Diagnosis Related Groups,DRG)医保支付方式改革全面铺开的背景下,公立医院需要清晰地认识到,除了提高工作效率之外,还必须加强效益的提升[1]。医院需要改变传统思维,平衡治疗的效果和成本,避免过度医疗产生浪费,在成本管控的前提下进一步提高医院的医保基金结余。DRG付费的理念是按病种打包支付,“超支分担、节余留用”[2],支付差是指按DRG付费与按项目付费的差额[3]。DRG付费下,支付差是评价医院成本控制成效的关键指标,更是助推医院医保基金结余的决定性因素。目前对DRG住院费用方面的研究较多,但针对医保支付差影响因素的研究较少[4]。
随着我国人口老龄化加速发展和骨质疏松患病率逐年提高,脊柱退行性疾病患者接受脊柱融合手术的需求日益增加[5]。为减轻患者就医负担,样本医院所在统筹区于2023年3月15起开展骨科脊柱类高值耗材集中带量采购和使用工作[6]。集采前后脊柱有关手术病组的DRG支付数据变动较大,由原来负差异变成了正差异。本研究以广西某大型三甲医院脊柱有关手术患者(ADRG编码为IB1、IB2和IB3)作为研究对象,分析DRG付费下支付差的影响因素,提出针对性建议,为医院合理控制成本、助推医院医保基金结余,进一步推动公立医院高质量发展提供参考。
挑选2022年1月1日至2024年12月31日广西某大型三甲医院收治的脊柱有关手术DRG入组患者作为研究对象,共计1 798例。
运用Excel 2010对收集的数据进行归纳整理并建立数据库,使用SPSS 25.0对入组数据进行统计描述与分析。运用描述统计方法对研究对象和费用构成进行描述分析,对入组病例的性别、年龄、平均住院日、ADRG组、基金类型、病例类型、是否并发症、主诊组、是否集采等因素进行单因素分析;由于DRG支付差是包含正、负数的非正态分布数据,故将其作数据平移后对数转换再设定为因变量进行多元线性回归分析,探索与脊柱有关病组支付差的影响因素;使用AMOS 28.0软件构建结构方程模型,验证影响因素与DRG支付差的关系,模型采用最小均方差法进行拟合估算,并对结构方程的建模进行评价[7]。所有检验均为双侧检验,检验水准为α=0.05。
本研究共纳入1 798例与脊柱有关的住院手术患者,其中男性患者799例(44.44%),女性999例(55.56%),平均年龄57.10岁,平均住院日6.43天,例均支付差7 207.48元,支付差最高65 527.19元,最低为-55 429.33元。骨科脊柱类高值耗材集采前例均支付差-2 159.14元,集采后例均支付差13 277.32元,例均总费用和耗材费用显著下降(P<0.001),例均治疗费用显著上升(P<0.001),平均住院日和例均检查费无显著性差异(P>0.05),详见表1。
通过Welch ANOVA分析方法,对支付差的各影响因素进行统计分析,单因素分析结果显示,年龄、平均住院日、ADRG组、基金类型、病例类型、是否并发症、主诊组、是否集采等方面的差异具有统计学意义(P<0.001),性别方面的支付差无统计学意义(P=0.982)。结果详见表2。
将DRG支付差数据进行统计学转换处理后作为因变量,单因素分析中的所有因素作为自变量,纳入影响支付差的多元线性回归分析模型,对自变量的赋值见表3。多元线性回归模型校正R2=0.504,F=227.419,P<0.001,有统计学意义,模型拟合较好,结果显示对支付差影响最大的前3位因素分别是ADRG组、是否集采和病例类型(见表4)。
在AMOS 28.0软件中构建结构方程模型,将数据统计学转换后的支付差作为新变量,导入数据进行拟合优化。结构方程模型结果显示,ADRG组是支付差的最大影响因素,路径系数是0.55,其次是集采政策(0.36),再次是病例类型(0.21),其他因素对其几乎没有影响(详见图1)。
在拟合指数方面,卡方值(χ2)和自由度(v)的比值大于判断标准,原因可能是样本数较多,导致χ2偏大;其他拟合指数处于良好区间,模型方程对各变量的拟合情况较好,结果详见表5。
DRG付费改革建立了一种动态的价格调整机制和服务监督机制,通过“结余留用、合理超支分担”的风险分担机制,激励医院形成控制费用的内生动力,在保证医疗质量的前提下尽可能地控制成本,提高医保基金结余,提升医院运行效率,推动医院高质量发展。因此,对DRG医保支付差影响因素的研究不仅有助于完善医保支付政策,还能降低医疗资源消耗、提高医院管理水平[8]。
本研究中脊柱骨科的高值耗材集中带量采购前,脊骨相关手术患者例均总费用58 842.68元,例均耗材费用45 014.30元,例均治疗费7 641.74元,例均支付差-2 159.14元。集采后高值耗材价格大幅下降,同时提高了部分医疗服务价格,相同手术例均总费用下降到30 365.11元,例均耗材费用14 470.24元,例均治疗费9 333.09元,例均支付差13 277.32元,在集采政策实行后,脊骨科在我院由亏损前几名立刻转为盈余靠前的科室。集采前后不仅例均总费用大幅下降,住院费用结构也进行了合理的调整,多项研究结果也证实了集采对住院医疗费用调整有积极的作用[9-10]。本研究结果显示集采前后平均住院日和例均检查费用差异无统计学意义,但体现了医务人员劳动价值的治疗费占比由12.99%显著提高到30.70%,而“零加成”的耗材费用占比由76.50%大幅下降到47.60%,实现了医保高值耗材集采“腾笼换鸟”的效果。2021年1月,国务院办公厅《关于推动药品集中带量采购工作常态化制度化开展的意见》提出,对因集中带量采购节约的医保资金,按照相关规定给予医院结余留用激励[11]。因此,医院应该积极响应国家集采政策,通过“以量换价”挤出高值医用耗材中价格虚高的水分,减轻患者就医负担,同时积极推动“医耗联动”改革,持续完善医疗服务价格管理,充分体现其技术劳动价值[12-13]。
本研究单因素分析结果显示,年龄段越大,例均支付差越小,说明随着年龄增加患病的机会越大,同时年龄大基础疾病多,住院总费用高,而入同一个组DRG支付的费用是相同的,建议医保部门在制定DRG支付政策时应该把患者的年龄因素也考虑进去[14];平均住院日方面住院5~8天的例均支付差最高,≤4天的患者可能病情较轻,没有并发症,权重更低,DRG支付费用更少,≥9天的患者可能是病情危重,合并基础疾病较多,导致医疗总费用太高,所以支付差更少;不同ADRG组之间,IB1组(复杂脊柱疾患或3节段及以上脊柱融合手术或翻修手术)例均支付差最大,其次是IB2(脊柱2节段及以下脊柱融合术),最后是IB3(与脊柱有关的其他手术),主要是因为IB1手术难度最大,权重最高,DRG支付费用最多,而IB3是权重最低,DRG支付最少;不同基金类型导致支付差也是不同的,其中南宁市职工医保支付差最大,南宁市居民医保最少,因为不同医保基金类型的征缴力度不同[15],职工医保基金的DRG付费预算更加充足,DRG支付下职工医保的点值远高于居民医保,导致医院治疗同一种疾病,因为医保类型不同而医保DRG支付的费用相差特别大,建议相关政府部门进一步加大对居民医保基金的补贴力度,DRG付费下实现“同城、同病、同治、同价”[16]。不同病例类型例均支付差不同,只有正常倍率病例才能支付正差异,高倍率和低倍率病例都是负差异,医生应该在病情允许的情况合理控制患者的住院费用,同时也避免治疗不足[17]。并发症类型方面,严重并发症的支付差最大,无并发症支付差最小,因为严重并发症和一般并发症权重更高,DRG支付的费用更多,导致支付差更大。不同主诊组之间的支付差也是相差很大,最多的能够正差异14 550.18元,最少的是负差异-1 216.20元,可能是不同的主诊组负责的手术类型不同,同时也提示我们需要进一步规范诊疗、优化临床路径管理、促进相同病种诊疗的同质化[18]。
DRG支付差的影响因素是多方面的,单独分析某个自变量过程中,不仅会出现较大误差,还会忽略各自变量的相互影响,而结构方程模型可以分析含有一定误差的变量[19],且可以同时处理多个变量,以及分析各变量之间的相关性[20-21]。本研究为验证多元回归分析结果的合理性,通过结构方程模型进一步验证了相关变量对支付差的影响。多元回归线性分析和结构方程模型结果均显示,对支付差影响最大的前3位因素分别是ADRG组、是否集采和病例类型,平均住院日和基金类型也有一定的影响。因此,建议医保行政部门合理设置各病组的权重,着重考虑医疗技术难度,而不是单纯以历史费用衡量,因为脊柱骨科类手术的历史费用中耗材费用占比超过70%,病组权重不仅要反映患者真实的医疗消耗,还要体现医疗技术水平;同时要积极推动高值耗材集中带量采购政策,通过“以量换价”,挤出医用耗材中价格虚高的水分[22-23],合理提高医疗服务价格,进一步强化DRG付费与集采政策的协同联动。样本医院是当地区域医疗中心,聚焦疑难危重病例,合理诊疗情况下的大额医疗费用应该得到足够的医保补偿,以推动医疗机构高质量发展。
  • 广西卫健委自筹经费科研课题(Z-A20240558)
  • 广西医科大学第一附属医院自设培育项目(YYZS2023039)
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2025年第52卷第22期
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doi: 10.20043/j.cnki.MPM.202506355
  • 接收时间:2025-06-23
  • 首发时间:2026-10-29
  • 出版时间:2025-11-25
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  • 收稿日期:2025-06-23
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广西卫健委自筹经费科研课题(Z-A20240558)
广西医科大学第一附属医院自设培育项目(YYZS2023039)
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    1.广西医科大学第一附属医院,广西 南宁 530021
    2.南宁春瑞康华医院

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2种不同金属材料的力学参数
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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
栓菌属 Trametes 5 2.39
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