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Article(id=1324078173977183083, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324078037817504735, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202509055, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1757001600000, receivedDateStr=2025-09-05, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793614436858, onlineDateStr=2026-11-02, pubDate=1770652800000, pubDateStr=2026-02-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793614436858, onlineIssueDateStr=2026-11-02, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793614436858, creator=13701087609, updateTime=1793614436858, updator=13701087609, issue=Issue{id=1324078037817504735, tenantId=1146029695717560320, journalId=1227665162245664772, year='2026', volume='53', issue='3', pageStart='385', pageEnd='576', issueExtLink='null', onlineDate='null', pubDate='1770652800000', pubDateStr='2026-02-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1793614404396, creator='13701087609', updateTime=1793614474144, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1324078330420527919, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324078037817504735, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1324078330420527920, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324078037817504735, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=492, endPage=497, ext={EN=ArticleExt(id=1324078174182703980, articleId=1324078173977183083, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Outpatient cost standards for diabetic patients in tertiary hospitals based on ambulatory patient groups, columnId=1228016567846367388, journalTitle=Modern Preventive Medicine, columnName=Health Policy and Management, runingTitle=null, highlight=null, articleAbstract=
Objective

To investigate the influencing factors of outpatient expenses for diabetic patients and conduct case-mix grouping and expenses estimation, providing evidence for the reform of outpatient medical insurance payment methods.

Methods

Outpatient medical insurance settlement data of diabetic patients from tertiary hospitals in Lanzhou between January 2022 and December 2023 were collected. Univariate analysis and multivariable linear regression models were used to analyze the influencing factors of total outpatient medical expenses. Subsequently, a decision tree model was applied for ambulatory patient groups(APG) classification, and relevant indicators were employed to evaluate APGs and estimate expenses.

Results

A total of 48 948 valid records were included. The total outpatient medical expenses of diabetic patients were associated with gender (Z=-5.702, P<0.001), ethnicity (Z=-2.180, P=0.029), age (Z=1 096.615, P<0.001), type of diabetes (Z=1 463.467, P<0.001), complications (Z=-13.593, P<0.001), medication use (Z=-10.370, P<0.001), diagnostic testing (Z=-4.676, P<0.001), and medical consumables usage (Z=-16.509, P<0.001). Higher outpatient expenses were observed in male patients, other ethnic groups, individuals aged <45 years, type 2 diabetes cases, and patients with complications, medication use, diagnostic testing, and medical consumables usage. Based on the decision tree model, 13 APGs were established. The number of cases per APG group ranged from 114(APG8) to 11 619(APG5), with significant differences among groups based on a nonparametric test(H=3 266.675, P<0.001). The reduction in variance (RIV) was 0.945, the coefficient of variation (CV) ranged from 0.93 (APG2)to 1.56 (APG12), the relative weight (RW) ranged from 0.44 (APG11) to 1.69 (APG1), the standardized cost ranged from 58.55 CNY (APG12) to 324.83 CNY (APG1), and the excess cost ratio ranged from 1.81%(APG1) to 8.93% (APG3).

Conclusion

The economic burden of outpatient diabetes in tertiary hospitals is substantial, with significant cost variations among different patient subgroups. The decision tree-based case-mix grouping performed well, demonstrating strong inter-group heterogeneity and good intra-group homogeneity. It is recommended to strengthen outpatient security and precise cost control, optimize diagnosis and treatment as well as precise classification of disease groups, and build a diversified and precise payment system, so as to promote the optimization of outpatient medical insurance payment methods and reduce the medical burden of diabetic patients.

, authors=Meng-en CHEN1, 2, Jing YU2, Shi-ji XIA2, Yu-han WANG2, Jing-yu YANG3, Qian ZHANG4, authorsList=Meng-en CHEN, Jing YU, Shi-ji XIA, Yu-han WANG, Jing-yu YANG, Qian ZHANG, authorCompany=null, correspAuthors=Qian ZHANG, 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=1324078174597940077, articleId=1324078173977183083, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=基于病例组合的三级医院糖尿病患者门诊费用标准研究, columnId=1228016568014139551, journalTitle=现代预防医学, columnName=卫生政策与管理, runingTitle=null, highlight=null, articleAbstract=
目的

探究糖尿病患者门诊费用影响因素并进行病例组合和费用测算，为门诊医保支付方式改革提供借鉴参考。

方法

采集兰州市2022年1月—2023年12月三级医院糖尿病门诊患者医保结算资料，运用单因素分析和多因素线性回归模型分析门诊医疗费用总额的影响因素，后建立决策树模型进行门诊病例组合（ambulatory patient groups，APG）分组，并利用相关指标进行APGs评价和费用测算。

结果

共纳入48 948条有效数据。糖尿病患者门诊医疗费总额与性别（Z=-5.702，P<0.001）、民族（Z=-2.180，P=0.029）、年龄（Z=1 096.615，P<0.001）、糖尿病类型（Z=1 463.467，P<0.001）、是否有并发症（Z=-13.593，P<0.001）、是否用药（Z=-10.370，P<0.001）、是否检查诊断（Z=-4.676，P<0.001）、是否使用医用耗材（Z=-16.509，P<0.001）相关，男性、其他民族、<45岁、Ⅱ型糖尿病、有并发症、用药、检查诊断、使用医用耗材的患者门诊医疗费总额更高。基于决策树模型建立13个APGs，病例数范围是114例（APG8）～11 619例（APG5）,组间非参数检验差异有统计学意义（H=3 266.675，P<0.001），方差减少量值是0.945，变异系数值范围是0.93（APG2）～1.56（APG12），病种权重值范围是0.44（APG11）～1.69（APG1），标准费用区间是58.55元（APG12）～324.83元（APG1），超标比例范围是1.81%（APG1）～8.93%（APG3）。

结论

三级医院糖尿病患者门诊疾病经济负担较重，不同特征群体费用存在显著差异；基于决策树模型展开病例分组效果较好，组间异质性强、组内同质性好。建议强化门诊保障与精准控费，优化诊疗与病组精准分类，构建多元精准支付体系，以推进门诊医保支付方式优化和降低糖尿病患者医疗负担。

, authors=陈蒙恩1, 2, 郁菁2, 夏士霁2, 王昱涵2, 杨敬宇3, 张倩4, authorsList=陈蒙恩, 郁菁, 夏士霁, 王昱涵, 杨敬宇, 张倩, authorCompany=null, correspAuthors=张倩, authorNote=

陈蒙恩（1996—），男，博士在读，研究方向：卫生政策与医疗保障

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张倩，E-mail:
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陈蒙恩（1996—），男，博士在读，研究方向：卫生政策与医疗保障

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(In Chinese), articleTitle=Practice and exploration of big data innovation DRG intelligent management, refAbstract=null), Reference(id=1324078188380423111, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078173977183083, doi=null, pmid=null, pmcid=null, year=2025, volume=45, issue=4, pageStart=30, pageEnd=34, url=null, language=null, rfNumber=[15], rfOrder=27, authorNames=顾梅, 赵宁, 李进, journalName=中国医院管理, refType=null, unstructuredReference=顾梅，赵宁，李进，等.我国门诊医保支付方式改革的实践探索和启示[J].中国医院管理，2025，45（4）：30-34., articleTitle=我国门诊医保支付方式改革的实践探索和启示, refAbstract=null), Reference(id=1324078188447531976, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078173977183083, doi=null, pmid=null, pmcid=null, year=2025, volume=45, issue=4, pageStart=30, pageEnd=34, url=null, language=null, rfNumber=[15], rfOrder=28, authorNames=Gu M, Zhao N, Li J, journalName=Chinese Hospital Management, refType=null, unstructuredReference=Gu M, Zhao N, Li J, et al. Practical exploration and Enlightenment of reforming for ambulatory care payment methods in China[J]. Chinese Hospital Management, 2025, 45(4): 30-34. (In Chinese), articleTitle=Practical exploration and Enlightenment of reforming for ambulatory care payment methods in China, refAbstract=null)], funds=[Fund(id=1324078182290293675, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078173977183083, awardId=null, language=CN, fundingSource=甘肃省医疗保障局2022年课题委托项目, fundOrder=null, country=null)], companyList=[AuthorCompany(id=1324078174874764142, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078173977183083, xref=1., ext=[AuthorCompanyExt(id=1324078174887347055, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078173977183083, companyId=1324078174874764142, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing 102400, China), AuthorCompanyExt(id=1324078174895735664, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078173977183083, companyId=1324078174874764142, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.北京中医药大学中医学院，北京 102400)]), AuthorCompany(id=1324078174971233137, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078173977183083, xref=2., ext=[AuthorCompanyExt(id=1324078174979621746, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078173977183083, companyId=1324078174971233137, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.北京中医药大学管理学院，北京 102400)]), AuthorCompany(id=1324078175046730611, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078173977183083, xref=3., ext=[AuthorCompanyExt(id=1324078175055119220, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078173977183083, companyId=1324078175046730611, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3.甘肃中医药大学卫生管理学院)]), AuthorCompany(id=1324078176766395253, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078173977183083, xref=4., ext=[AuthorCompanyExt(id=1324078176774783862, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078173977183083, companyId=1324078176766395253, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=4.四川省肿瘤医院·研究所、四川省肿瘤临床医学研究中心、四川省癌症防治中心、电子科技大学附属肿瘤医院总务处，四川 成都 610045)])], figs=[ArticleFig(id=1324078181573067683, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078173977183083, language=EN, label=Table 1, caption=

Results of univariate analysis of total outpatient costs for diabetic patients in tertiary hospitals ［n（%），M（P25，P75）］

, figureFileSmall=null, figureFileBig=null, tableContent=
变量分类人数（%）医疗费总额（元）Z/H值P值
性别男性30 844(63.01)171.57（58.27，364.95）-5.702<0.001
女性18 104(36.99)154.76（51.08，356.86）
民族汉族48 057(98.18)164.91（55.20，361.67）-2.1800.029
其他891(1.82)184.12（68.82，396.84）
年龄（岁）<457 621(15.57)241.86（89.33，502.50）1 096.615<0.001
45~6020 177(41.22)173.26（61.76，361.55）
>6021 150(43.21)135.00（44.17，311.76）
糖尿病类型Ⅰ型645(1.32)97.38（28.77,241.45）1 463.467<0.001
Ⅱ型35 678(72.89)191.02（71.18,402.94）
其他12 625(25.79)106.44（29.98,264.68）
是否有并发症否24 879(50.83)151.69（51.14,323.63）-13.593<0.001
是24 069(49.17)181.73（59.88,400.98）
是否用药否9 784(19.99)149.02（58.82，311.00）-10.370<0.001
是39 164(80.01)169.45（55.06，380.39）
是否检查诊断否31 088(63.51)160.63（49.69，367.48）-4.676<0.001
是17 860(36.49)173.50（70.22，353.32）
是否使用医用耗材否47 427(96.89)161.31（54.76，354.54）-16.509<0.001
是1 521(3.11)276.50（107.38，547.58）
), ArticleFig(id=1324078181656953764, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078173977183083, language=CN, label=表1, caption=

三级医院糖尿病患者门诊医疗费总额的单因素分析结果［n（%），M（P25，P75）］

, figureFileSmall=null, figureFileBig=null, tableContent=
变量分类人数（%）医疗费总额（元）Z/H值P值
性别男性30 844(63.01)171.57（58.27，364.95）-5.702<0.001
女性18 104(36.99)154.76（51.08，356.86）
民族汉族48 057(98.18)164.91（55.20，361.67）-2.1800.029
其他891(1.82)184.12（68.82，396.84）
年龄（岁）<457 621(15.57)241.86（89.33，502.50）1 096.615<0.001
45~6020 177(41.22)173.26（61.76，361.55）
>6021 150(43.21)135.00（44.17，311.76）
糖尿病类型Ⅰ型645(1.32)97.38（28.77,241.45）1 463.467<0.001
Ⅱ型35 678(72.89)191.02（71.18,402.94）
其他12 625(25.79)106.44（29.98,264.68）
是否有并发症否24 879(50.83)151.69（51.14,323.63）-13.593<0.001
是24 069(49.17)181.73（59.88,400.98）
是否用药否9 784(19.99)149.02（58.82，311.00）-10.370<0.001
是39 164(80.01)169.45（55.06，380.39）
是否检查诊断否31 088(63.51)160.63（49.69，367.48）-4.676<0.001
是17 860(36.49)173.50（70.22，353.32）
是否使用医用耗材否47 427(96.89)161.31（54.76，354.54）-16.509<0.001
是1 521(3.11)276.50（107.38，547.58）
), ArticleFig(id=1324078181736645541, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078173977183083, language=EN, label=Table 2, caption=

Results of multivariable analysis on total outpatient costs for diabetic patients in tertiary hospitals

, figureFileSmall=null, figureFileBig=null, tableContent=
变量B（95%CI）标准误Betat值P值
常量4.37 （4.26~4.48）0.0677.744<0.001
性别（参照：男性）-0.08 （-0.10~-0.05）0.01-0.03-6.102<0.001
民族（参照：汉族）0.15 （0.06~0.24）0.050.013.2060.001
年龄（岁，参照：<45）
45~60-0.34 （-0.37~-0.30）0.02-0.12-18.558<0.001
>60-0.56 （-0.60~-0.53）0.02-0.20-31.010<0.001
糖尿病类型（参照：其他类型）
Ⅰ型-0.11 （-0.22~-0.01）0.05-0.01-2.0560.040
Ⅱ型0.52 （0.49~0.54）0.010.1736.452<0.001
是否有并发症（参照：否）0.08 （0.06~0.10）0.010.036.339<0.001
是否用药（参照：否）0.40 （0.36~0.43）0.020.1121.383<0.001
是否检查诊断（参照：否）0.27 （0.24~0.30）0.020.1017.824<0.001
是否使用医用耗材（参照：否）0.55 （0.49~0.62）0.040.0715.649<0.001
), ArticleFig(id=1324078181824725926, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078173977183083, language=CN, label=表2, caption=

三级医院糖尿病患者门诊医疗费总额的多因素影响分析结果

, figureFileSmall=null, figureFileBig=null, tableContent=
变量B（95%CI）标准误Betat值P值
常量4.37 （4.26~4.48）0.0677.744<0.001
性别（参照：男性）-0.08 （-0.10~-0.05）0.01-0.03-6.102<0.001
民族（参照：汉族）0.15 （0.06~0.24）0.050.013.2060.001
年龄（岁，参照：<45）
45~60-0.34 （-0.37~-0.30）0.02-0.12-18.558<0.001
>60-0.56 （-0.60~-0.53）0.02-0.20-31.010<0.001
糖尿病类型（参照：其他类型）
Ⅰ型-0.11 （-0.22~-0.01）0.05-0.01-2.0560.040
Ⅱ型0.52 （0.49~0.54）0.010.1736.452<0.001
是否有并发症（参照：否）0.08 （0.06~0.10）0.010.036.339<0.001
是否用药（参照：否）0.40 （0.36~0.43）0.020.1121.383<0.001
是否检查诊断（参照：否）0.27 （0.24~0.30）0.020.1017.824<0.001
是否使用医用耗材（参照：否）0.55 （0.49~0.62）0.040.0715.649<0.001
), ArticleFig(id=1324078181904417703, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078173977183083, language=EN, label=Table 3, caption=

Ambulatory patient groups and disease weights for diabetic patients in tertiary hospitals

, figureFileSmall=null, figureFileBig=null, tableContent=
分组门诊病例组合样本量比例（%）门诊医疗费用总额（元）变异系数病种权重
均值标准差
APG1<45岁，Ⅱ型糖尿病，用药4 5749.34460.49454.090.991.69
APG2<45岁，Ⅱ型糖尿病，未用药1 0722.19254.67235.780.930.94
APG3<45岁，非Ⅱ型糖尿病，有并发症6161.26172.87245.381.420.64
APG4<45岁，非Ⅱ型糖尿病，无并发症1 3592.78259.38294.031.130.95
APG545~60岁，Ⅱ型糖尿病，用药11 61923.74320.77379.371.181.18
APG645~60岁，Ⅱ型糖尿病，未用药3 3066.75222.18218.820.980.82
APG745~60岁，非Ⅱ型糖尿病，未使用医用耗材5 13810.50201.11258.101.280.74
APG845~60岁，非Ⅱ型糖尿病，使用医用耗材1140.23356.74393.771.101.31
APG9>60岁，Ⅱ型糖尿病，有并发症8 65417.68282.34350.671.241.04
APG10>60岁，Ⅱ型糖尿病，无并发症6 45313.18220.64285.831.300.81
APG11>60岁，Ⅰ型糖尿病2170.44120.10152.541.270.44
APG12>60岁，其他类型糖尿病，有并发症2 5425.19146.47228.201.560.54
APG13>60岁，其他类型糖尿病，无并发症3 2846.71203.46270.681.330.75
), ArticleFig(id=1324078181992498088, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078173977183083, language=CN, label=表3, caption=

三级医院糖尿病患者APG分组与病种权重情况

, figureFileSmall=null, figureFileBig=null, tableContent=
分组门诊病例组合样本量比例（%）门诊医疗费用总额（元）变异系数病种权重
均值标准差
APG1<45岁，Ⅱ型糖尿病，用药4 5749.34460.49454.090.991.69
APG2<45岁，Ⅱ型糖尿病，未用药1 0722.19254.67235.780.930.94
APG3<45岁，非Ⅱ型糖尿病，有并发症6161.26172.87245.381.420.64
APG4<45岁，非Ⅱ型糖尿病，无并发症1 3592.78259.38294.031.130.95
APG545~60岁，Ⅱ型糖尿病，用药11 61923.74320.77379.371.181.18
APG645~60岁，Ⅱ型糖尿病，未用药3 3066.75222.18218.820.980.82
APG745~60岁，非Ⅱ型糖尿病，未使用医用耗材5 13810.50201.11258.101.280.74
APG845~60岁，非Ⅱ型糖尿病，使用医用耗材1140.23356.74393.771.101.31
APG9>60岁，Ⅱ型糖尿病，有并发症8 65417.68282.34350.671.241.04
APG10>60岁，Ⅱ型糖尿病，无并发症6 45313.18220.64285.831.300.81
APG11>60岁，Ⅰ型糖尿病2170.44120.10152.541.270.44
APG12>60岁，其他类型糖尿病，有并发症2 5425.19146.47228.201.560.54
APG13>60岁，其他类型糖尿病，无并发症3 2846.71203.46270.681.330.75
), ArticleFig(id=1324078182076384169, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078173977183083, language=EN, label=Table 4, caption=

Standard cost of ambulatory patient groups for diabetic patients in tertiary hospitals

, figureFileSmall=null, figureFileBig=null, tableContent=
分组门诊病例组合标准费用
（元）		P25（元）P75（元）四分位间距
（元）		费用上限
（元）		超标条数
（条）		超标比例
（%）
APG1<45岁，Ⅱ型糖尿病，用药324.83131.48734.17602.691 638.21831.81
APG2<45岁，Ⅱ型糖尿病，未用药201.9689.46366.42276.96781.86282.61
APG3<45岁，非Ⅱ型糖尿病，有并发症80.0029.54208.28178.74476.39558.93
APG4<45岁，非Ⅱ型糖尿病，无并发症169.0563.10337.25274.15748.481017.43
APG545岁~60岁，Ⅱ型糖尿病，用药204.6877.30427.27349.97952.236555.64
APG645岁~60岁，Ⅱ型糖尿病，未用药161.7676.00316.67240.67677.681143.45
APG745岁~60岁，非Ⅱ型糖尿病，未使用医用耗材114.0032.65272.21239.56631.553065.96
APG845岁~60岁，非Ⅱ型糖尿病，使用医用耗材230.69135.46462.09326.63952.0465.26
APG9>60岁，Ⅱ型糖尿病，有并发症176.5861.76379.41317.65855.894665.38
APG10>60岁，Ⅱ型糖尿病，无并发症136.2745.10296.56251.46673.753415.28
APG11>60岁，Ⅰ型糖尿病66.6723.07179.82156.75414.9594.15
APG12>60岁，其他类型糖尿病，有并发症58.5514.60194.12179.52463.401807.08
APG13>60岁，其他类型糖尿病，无并发症118.9638.16271.71233.55622.041855.63
), ArticleFig(id=1324078182168658858, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078173977183083, language=CN, label=表4, caption=

三级医院糖尿病患者APG分组的标准费用情况

, figureFileSmall=null, figureFileBig=null, tableContent=
分组门诊病例组合标准费用
（元）		P25（元）P75（元）四分位间距
（元）		费用上限
（元）		超标条数
（条）		超标比例
（%）
APG1<45岁，Ⅱ型糖尿病，用药324.83131.48734.17602.691 638.21831.81
APG2<45岁，Ⅱ型糖尿病，未用药201.9689.46366.42276.96781.86282.61
APG3<45岁，非Ⅱ型糖尿病，有并发症80.0029.54208.28178.74476.39558.93
APG4<45岁，非Ⅱ型糖尿病，无并发症169.0563.10337.25274.15748.481017.43
APG545岁~60岁，Ⅱ型糖尿病，用药204.6877.30427.27349.97952.236555.64
APG645岁~60岁，Ⅱ型糖尿病，未用药161.7676.00316.67240.67677.681143.45
APG745岁~60岁，非Ⅱ型糖尿病，未使用医用耗材114.0032.65272.21239.56631.553065.96
APG845岁~60岁，非Ⅱ型糖尿病，使用医用耗材230.69135.46462.09326.63952.0465.26
APG9>60岁，Ⅱ型糖尿病，有并发症176.5861.76379.41317.65855.894665.38
APG10>60岁，Ⅱ型糖尿病，无并发症136.2745.10296.56251.46673.753415.28
APG11>60岁，Ⅰ型糖尿病66.6723.07179.82156.75414.9594.15
APG12>60岁，其他类型糖尿病，有并发症58.5514.60194.12179.52463.401807.08
APG13>60岁，其他类型糖尿病，无并发症118.9638.16271.71233.55622.041855.63
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基于病例组合的三级医院糖尿病患者门诊费用标准研究
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陈蒙恩 1, 2 , 郁菁 2 , 夏士霁 2 , 王昱涵 2 , 杨敬宇 3 , 张倩 4
现代预防医学 | 卫生政策与管理 2026,53(3): 492-497
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现代预防医学 |卫生政策与管理 2026 , 53 (3) : 492 -497
基于病例组合的三级医院糖尿病患者门诊费用标准研究
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陈蒙恩（1996—），男，博士在读，研究方向：卫生政策与医疗保障

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陈蒙恩1, 2, 郁菁2, 夏士霁2, 王昱涵2, 杨敬宇3, 张倩4
作者信息
  • 1.北京中医药大学中医学院，北京 102400
  • 2.北京中医药大学管理学院，北京 102400
  • 3.甘肃中医药大学卫生管理学院
  • 4.四川省肿瘤医院·研究所、四川省肿瘤临床医学研究中心、四川省癌症防治中心、电子科技大学附属肿瘤医院总务处，四川 成都 610045
通讯作者:
张倩，E-mail:
作者简介:

陈蒙恩（1996—），男，博士在读，研究方向：卫生政策与医疗保障

Outpatient cost standards for diabetic patients in tertiary hospitals based on ambulatory patient groups
Meng-en CHEN1, 2, Jing YU2, Shi-ji XIA2, Yu-han WANG2, Jing-yu YANG3, Qian ZHANG4
Affiliations
  • School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing 102400, China
出版时间: 2026-02-10 doi: 10.20043/j.cnki.MPM.202509055
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摘要
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目的

探究糖尿病患者门诊费用影响因素并进行病例组合和费用测算，为门诊医保支付方式改革提供借鉴参考。

方法

采集兰州市2022年1月—2023年12月三级医院糖尿病门诊患者医保结算资料，运用单因素分析和多因素线性回归模型分析门诊医疗费用总额的影响因素，后建立决策树模型进行门诊病例组合（ambulatory patient groups，APG）分组，并利用相关指标进行APGs评价和费用测算。

结果

共纳入48 948条有效数据。糖尿病患者门诊医疗费总额与性别（Z=-5.702，P<0.001）、民族（Z=-2.180，P=0.029）、年龄（Z=1 096.615，P<0.001）、糖尿病类型（Z=1 463.467，P<0.001）、是否有并发症（Z=-13.593，P<0.001）、是否用药（Z=-10.370，P<0.001）、是否检查诊断（Z=-4.676，P<0.001）、是否使用医用耗材（Z=-16.509，P<0.001）相关，男性、其他民族、<45岁、Ⅱ型糖尿病、有并发症、用药、检查诊断、使用医用耗材的患者门诊医疗费总额更高。基于决策树模型建立13个APGs，病例数范围是114例（APG8）～11 619例（APG5）,组间非参数检验差异有统计学意义（H=3 266.675，P<0.001），方差减少量值是0.945，变异系数值范围是0.93（APG2）～1.56（APG12），病种权重值范围是0.44（APG11）～1.69（APG1），标准费用区间是58.55元（APG12）～324.83元（APG1），超标比例范围是1.81%（APG1）～8.93%（APG3）。

结论

三级医院糖尿病患者门诊疾病经济负担较重，不同特征群体费用存在显著差异；基于决策树模型展开病例分组效果较好，组间异质性强、组内同质性好。建议强化门诊保障与精准控费，优化诊疗与病组精准分类，构建多元精准支付体系，以推进门诊医保支付方式优化和降低糖尿病患者医疗负担。

APGs  /  糖尿病  /  三级医院  /  门诊费用  /  决策树模型
Objective

To investigate the influencing factors of outpatient expenses for diabetic patients and conduct case-mix grouping and expenses estimation, providing evidence for the reform of outpatient medical insurance payment methods.

Methods

Outpatient medical insurance settlement data of diabetic patients from tertiary hospitals in Lanzhou between January 2022 and December 2023 were collected. Univariate analysis and multivariable linear regression models were used to analyze the influencing factors of total outpatient medical expenses. Subsequently, a decision tree model was applied for ambulatory patient groups(APG) classification, and relevant indicators were employed to evaluate APGs and estimate expenses.

Results

A total of 48 948 valid records were included. The total outpatient medical expenses of diabetic patients were associated with gender (Z=-5.702, P<0.001), ethnicity (Z=-2.180, P=0.029), age (Z=1 096.615, P<0.001), type of diabetes (Z=1 463.467, P<0.001), complications (Z=-13.593, P<0.001), medication use (Z=-10.370, P<0.001), diagnostic testing (Z=-4.676, P<0.001), and medical consumables usage (Z=-16.509, P<0.001). Higher outpatient expenses were observed in male patients, other ethnic groups, individuals aged <45 years, type 2 diabetes cases, and patients with complications, medication use, diagnostic testing, and medical consumables usage. Based on the decision tree model, 13 APGs were established. The number of cases per APG group ranged from 114(APG8) to 11 619(APG5), with significant differences among groups based on a nonparametric test(H=3 266.675, P<0.001). The reduction in variance (RIV) was 0.945, the coefficient of variation (CV) ranged from 0.93 (APG2)to 1.56 (APG12), the relative weight (RW) ranged from 0.44 (APG11) to 1.69 (APG1), the standardized cost ranged from 58.55 CNY (APG12) to 324.83 CNY (APG1), and the excess cost ratio ranged from 1.81%(APG1) to 8.93% (APG3).

Conclusion

The economic burden of outpatient diabetes in tertiary hospitals is substantial, with significant cost variations among different patient subgroups. The decision tree-based case-mix grouping performed well, demonstrating strong inter-group heterogeneity and good intra-group homogeneity. It is recommended to strengthen outpatient security and precise cost control, optimize diagnosis and treatment as well as precise classification of disease groups, and build a diversified and precise payment system, so as to promote the optimization of outpatient medical insurance payment methods and reduce the medical burden of diabetic patients.

Ambulatory patient groups  /  Diabetes  /  Tertiary hospitals  /  Outpatient expenses  /  Decision tree model
陈蒙恩, 郁菁, 夏士霁, 王昱涵, 杨敬宇, 张倩. 基于病例组合的三级医院糖尿病患者门诊费用标准研究. 现代预防医学, 2026 , 53 (3) : 492 -497 . DOI: 10.20043/j.cnki.MPM.202509055
Meng-en CHEN, Jing YU, Shi-ji XIA, Yu-han WANG, Jing-yu YANG, Qian ZHANG. Outpatient cost standards for diabetic patients in tertiary hospitals based on ambulatory patient groups[J]. Modern Preventive Medicine, 2026 , 53 (3) : 492 -497 . DOI: 10.20043/j.cnki.MPM.202509055
正文
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糖尿病作为全球增长最快的慢性疾病之一，已成为重大公共卫生挑战[1-3]。最新流行病学数据显示，全球约5.89亿成年人（占成年人口1/9）罹患糖尿病，其中中国患者占比达25%，患病人数持续居世界首位。更值得关注的是，预测表明到2050年中国糖尿病患者人数近1.68亿，患病率将持续增高[4]。这种高患病率不仅导致严重的健康损害，还造成了沉重的社会经济与医疗服务负担[5]。
在我国医疗卫生体系中，三级医院承担复杂病例诊疗、管理和科研的核心职能，其门诊服务效率直接影响疾病控制效果和医疗费用支出[6]。为控制医疗费用过快增长，在住院领域逐步推进的DRG/DIP医保支付改革取得一定成效[7-8]，然而门诊支付方面仍缺乏能够充分适应糖尿病等慢性病临床特点的管理工具。当前，我国门诊支付主要有按项目、按人头、按病种三种方式，而按项目付费可能会诱导过度医疗，按人头付费可能对于医疗服务质量控制产生不利影响，单病种付费覆盖的病种范围与数量有限[9]。国外的门诊付费方式呈多元化发展，包括按门诊病例组合（ambulatory patient groups，APG）、按人头、按绩效、按服务付费等，其中以美国为先的门诊病例组合付费系统正在有效推动按项目、按人头等传统付费方式向基于价值的复合型支付方式转变，而我国浙江金华、山东烟台等地也在试点推进门诊按病例分组付费的支付改革[10]。
病例组合方法通过量化患者临床特征与资源消耗之间的关系，建立基于实证的病例组合模型，对于揭示资源消耗规律、优化医保支付政策、提升分级诊疗效率具有重要价值，为弥补当前门诊支付政策的不足提供了理论依据与实践路径[11]。因此，本研究通过探讨三级医院糖尿病门诊患者的基本特征与诊疗情况，展开门诊费用影响因素分析并构建病例分组模型，以期为糖尿病门诊医疗质量管理和APG医保政策完善提供循证依据。
1　资料与方法
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1.1　资料来源
本研究数据来源于甘肃省兰州市医疗保障局的职工医保费用结算信息平台，从该平台获取2022年1月—2023年12月三级医院医保结算的相关资料。纳入标准为诊断病种名称是糖尿病，且门诊医疗类别为普通门诊，排除标准为患者诊疗关键信息缺失或存在逻辑错误。按照该纳入与排除标准，共计纳入48 948条有效数据。同时，基于职工门诊医保费用结算信息系统的现有数据与字段，并综合糖尿病患者流行病学特征对相关指标进行分类处理与赋值，以展开数据分析。此外，依据兰州市2023年的医疗保健类居民消费价格指数对糖尿病患者的门诊医疗费总额进行贴现处理(即2023年调整后费用为2023年实际费用除以兰州市2023年的医疗保健类居民消费价格指数),以减少研究偏倚。
1.2　研究方法
首先，对糖尿病患者门诊医疗费总额进行单因素和多因素线性回归分析，初步筛选出其影响因素；其次，以医疗费总额为因变量，将回归结果中有统计学意义变量作为自变量，建立决策树模型进行APG分组；最后，利用变异系数、病种权重、方差减少量（reduction in variance, RIV）和非参数检验（Kruskal-Wallis H检验）等指标和方法，评价APGs分组结果，并对各APG组的费用标准、费用上限等进行测算与设定。以上统计分析使用软件SPSS 26.0执行，检验水准α=0.05。
2　结果
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2.1　糖尿病患者门诊医疗费总额影响因素分析
由单因素分析结果可知，不同性别、民族、年龄、糖尿病类型、并发症、用药、检查诊断、使用医用耗材的糖尿病患者门诊医疗费总额情况，差异有统计学意义（P<0.05）；且男性患者的医疗费总额高于女性；其他民族患者医疗费总额高于汉族；<45岁患者医疗费总额高于其他年龄段；Ⅱ型糖尿病者医疗费总额高于Ⅰ型和其他类型；另有并发症、用药、检查诊断、使用医用耗材的医疗费总额较无并发症、未用药、未检查诊断、未使用医用耗材高。见表1。
以性别、民族、年龄、糖尿病类型、是否有并发症、是否用药、是否检查诊断、是否使用医用耗材为自变量，三级医院糖尿病患者门诊医疗费总额的自然对数（近似正态分布）为因变量，建立多因素线性回归模型。多因素线性回归结果显示，糖尿病患者门诊医疗费总额与性别、民族、年龄、糖尿病类型、是否有并发症、是否用药、是否检查诊断、是否使用医用耗材相关（P<0.05）。见表2。
2.2　糖尿病门诊医疗费总额APG分组分析
以多因素线性回归结果中有统计学意义的变量，即以性别、民族、年龄、糖尿病类型、是否有并发症、是否用药、是否检查诊断、是否使用医用耗材等为自变量，以三级医院糖尿病患者门诊医疗费总额为因变量，建立决策树模型进行门诊病例分类组合。由决策树模型分类结果可知，48 948条数据被划分为13个APG组，病例条数最多的是APG5（45～60岁，Ⅱ型糖尿病，用药），为11 619条，占比23.74%，最少的是APG8（45～60岁，非Ⅱ型糖尿病，使用医用耗材），为114条，占比仅0.23%，不同APGs的样本量差距较大；而APG1（<45岁，Ⅱ型糖尿病，用药）的门诊医疗费用水平最高，均值为460.49元，APG11（>60岁，Ⅰ型糖尿病）的费用水平最低，均值为120.10元，不同APGs的费用水平差距较大。见表3。
变异系数值用以评价APGs组内资源消耗的同质性，其越小则组内同质性越好；RIV值用以评价组间异质性，其越大则组间异质性越强；病种权重值用以评价各APG组对医疗资源消耗的相对程度，其越大则该APG组资源消耗越多。本研究中，三级医院糖尿病各APG组的变异系数值接近1，表明APGs组内资源消耗的同质性尚可，而RIV经计算为0.945，大于0.6，且对13个APG组进行非参数检验（Kruskal-Wallis H检验），检验结果有统计学意义（H=3 266.675，P<0.001），表明APGs组间异质性较强。此外，APG1（<45岁，Ⅱ型糖尿病，用药）的病种权重值最大，为1.69，而APG11（>60岁，Ⅰ型糖尿病）的病种权重值最小，仅为0.44，表明各APG组的资源消耗差距较大。见表3。
因糖尿病患者的门诊医疗费用总额呈现偏态分布，故本研究将各APG组的中位数设定为标准费用，并设置APGs的费用上限为各APG组的第75%百分位数加上1.5倍四分位间距。结果显示，APG1（<45岁，Ⅱ型糖尿病，用药）的标准费用最高，为324.83元，APG12（>60岁，其他类型糖尿病，有并发症）的标准费用最低，为58.55元，不同APGs的标准费用差距较大。另外，APG3（<45岁，非Ⅱ型糖尿病，有并发症）的超标比例最高，为8.93%，超标55条；APG1（<45岁，Ⅱ型糖尿病，用药）的超标比例最低，为1.81%，超标83条，整体看来各APG组的超标比例低于9%，表明APGs的标准费用设置相对合理，组内费用相对集中，资源消耗情况相近。见表4。
3　讨论
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3.1　糖尿病医疗费用负担与门诊精准控费保障
研究结果显示，糖尿病门诊医疗费总额与患者的性别、民族、年龄、糖尿病类型、是否有并发症、是否用药、是否检查诊断、是否使用医用耗材等相关，提示男性、其他民族、<45岁、Ⅱ型糖尿病、有并发症、用药、检查诊断、使用医用耗材的患者门诊费用水平更高。从研究结果来看，糖尿病患者的门诊医疗费用负担呈现出明显的群体差异，这为精准控费和强化门诊保障提供了明确的靶向依据。首先，对于45岁以下、Ⅱ型糖尿病、有并发症等疾病经济负担重的患者，应加强预防性支付补贴，从源头降低疾病进展风险；其次，适当降低其门诊统筹起付线、提高封顶线，确保这一群体能够“看得起病、用得起药”。同时，通过采取信息化监测手段与技术，加强对高门诊费用水平的糖尿病患者药品处方、检查诊断和医用耗材使用监管，建立智能化的处方审核系统和检查检验必要性评估机制，实现门诊费用的全面精准控制[12]，并协同APG支付方式改革深化，通过病例打包组合实现医疗成本控制和医疗服务质量提升，有效维护糖尿病患者门诊诊疗的合理权益。
3.2　决策树模型分组效果与病例精准分类优化
经决策树模型分组形成13个APGs，分类节点依次是年龄、糖尿病类型、是否有并发症、是否用药、是否使用医用耗材，说明糖尿病患者门诊医疗费用的核心影响因素是年龄、糖尿病类型、是否有并发症、是否用药、是否使用医用耗材等，有并发症、用药及耗材使用将推高门诊病例分组的医疗费用水平。另外，基于决策树模型进行糖尿病患者门诊病例分组，APGs组间异质性强、组内同质性好，且费用超标例数和占比整体情况良好，提示该方法设置的费用标准和费用上限较为合理，与先前病例分组的相关研究结果一致[11，13]，可为糖尿病门诊费用预警与管制提供科学参考，并为门诊APG支付改革实践探索提供借鉴。然现有研究中的病例分组依据指标，反映出的患者临床诊疗特征和资源消耗程度有限，故应在后续的门诊病例分组实践过程中，进一步扩展与疾病诊断和资源利用相关的统计分类变量，如将患者的病程、合并其他疾病情况等纳入分组模型，以提高病例分组和费用测算的精准度；同时，要不断优化提升分组模型，借助人工智能和大数据分析技术，使分组结果能更全面地反映患者的医疗需求和费用特征，为医疗资源的合理配置和费用控制提供更有力的支持[14]。
3.3　APG支付模式价值与多元精准支付体系构建
本研究基于决策树模型构建门诊病例分组体系具有良好的临床合理性和费用同质性特征[13]，而糖尿病患者门诊费用影响因素分析则为差异化支付政策制定提供了科学参考，为门诊APG支付改革提供了重要的理论和实践依据。然针对糖尿病诊疗的复杂性和疾病演进的多样性，仍需构建多层次、多元复合的精准支付体系：首先，对不同负担群体实施区别的门诊保障政策，通过优化起付线设置、差异化报销比例和结算方式，进一步提升保障精准度；其次，建立糖尿病的多元复合型医保支付制度，对稳定期患者推行基层首诊的慢性病打包支付或按人头付费等医保支付管理[15]，对病情复杂需基层转诊至更高级别医疗机构的普通病例执行APG支付，并辅以按项目或其他医保付费方式，以保证医疗服务的有效供给；同时配套价值医疗导向的激励机制，建立完善糖尿病专用医保药品目录、开展专项带量采购及实施分级支付政策。这一多元改革框架既能适应糖尿病患者的诊疗特点和费用差异，又能促进分级诊疗体系建设，提高医疗资源利用效率，可为门诊支付方式改革提供可推广的实施路径。然而，相对美国、英国等APG支付体系所采用的医疗保健通用程序编码系统和灵活的支付计算方式而言[9]，我国目前的门诊医保支付体系构建还存在较大差距，未来一段时期内应着力提升医疗系统的编码水平并优化门诊支付计算方案，以实现门诊多元精准支付体系的有效建立。
综上，三级医院糖尿病患者门诊医疗费用负担较重，不同患者群体的费用水平存在显著差异。糖尿病门诊APG支付相较于传统按人头、按项目付费模式，既能有效防范过度医疗行为又能克服临床多样性体现不足的局限，通过将糖尿病管理成本控制内化为医疗机构的自主动力，推动其持续优化服务流程与运营效率，并为医保精细化管理提供基于临床数据的有效支撑，从而在糖尿病治疗费用控制、管理效率与医疗资源公平性之间实现有机平衡。而本研究通过决策树模型构建的APG分组效果良好，具体表现为组间异质性突出且组内同质性好。依此设定的标准费用与费用上限兼具合理性与实用性，不仅为门诊费用的精准管控提供了科学依据，也为推进APG医保支付制度优化及其监测预警体系建设提供坚实的实证基础。然而，为进一步提升糖尿病患者门诊医疗保障待遇水平，仍需加强门诊医疗费用精准控制和医药使用的全过程监管，并不断优化提升门诊病例分组方案与技术，在推进门诊APG医保支付方式深入实践的同时，协同构建多元精准医保支付体系，从而促进门诊医疗保障制度健康可持续发展。
基金
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  • 甘肃省医疗保障局2022年课题委托项目
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参考文献 引证文献
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2026年第53卷第3期
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doi: 10.20043/j.cnki.MPM.202509055
  • 接收时间：2025-09-05
  • 首发时间：2026-11-02
  • 出版时间：2026-02-10
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  • 收稿日期：2025-09-05
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甘肃省医疗保障局2022年课题委托项目
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    1.北京中医药大学中医学院，北京 102400
    2.北京中医药大学管理学院，北京 102400
    3.甘肃中医药大学卫生管理学院
    4.四川省肿瘤医院·研究所、四川省肿瘤临床医学研究中心、四川省癌症防治中心、电子科技大学附属肿瘤医院总务处，四川 成都 610045

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