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Article(id=1321169558573007014, tenantId=1146029695717560320, journalId=1319373219989389464, issueId=1321169495406785472, articleNumber=null, orderNo=null, doi=10.11847/zgggws1147539, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1743350400000, receivedDateStr=2025-03-31, revisedDate=1748880000000, revisedDateStr=2025-06-03, acceptedDate=1754064000000, acceptedDateStr=2025-08-02, onlineDate=1792920968907, onlineDateStr=2026-10-25, pubDate=1762704000000, pubDateStr=2025-11-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1792920968907, onlineIssueDateStr=2026-10-25, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792920968907, creator=13701087609, updateTime=1792920968907, updator=13701087609, issue=Issue{id=1321169495406785472, tenantId=1146029695717560320, journalId=1319373219989389464, year='2025', volume='41', issue='11', pageStart='1281', pageEnd='1408', 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=1792920953847, creator='13701087609', updateTime=1793011176900, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1321547918390178721, tenantId=1146029695717560320, journalId=1319373219989389464, issueId=1321169495406785472, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1321547918390178722, tenantId=1146029695717560320, journalId=1319373219989389464, issueId=1321169495406785472, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=1373, endPage=1378, ext={EN=ArticleExt(id=1321169558782722215, articleId=1321169558573007014, tenantId=1146029695717560320, journalId=1319373219989389464, language=EN, title=Impact of DIP payment method on the structure of medical service supply, columnId=1320427686514770171, journalTitle=Chinese Journal of Public Health, columnName=Survey and Report, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze the impact of diagnosis-intervention packet (DIP) payment method on the medical service structure and outpatient-inpatient structure.

Methods

Data were collected from public medical institutions in DIP pilot city A and non-DIP reform city B in China from 2019 to 2022. Descriptive and difference-in differences-analyses were conducted on the medical service structure (medical service costs, drug costs, material costs, and examination and testing costs) and outpatient-inpatient structure (outpatient and inpatient costs, outpatient visits, and number of inpatient discharges).

Results

In terms of medical service structure, the examination and testing costs in city A decreased by 19.0% compared with those in city B (P < 0.05). In terms of the outpatient-inpatient structure, compared with city B, city A saw a 14.1% decrease in inpatient costs (P < 0.05), a 15.8% decrease in the number of inpatient discharges (P < 0.05), and an 8.3% increase in outpatient visits (P < 0.05).

Conclusions

The DIP payment method promotes optimization of the medical service structure. It effectively suppresses the behavior of "rushing points" and helps to promote the diversion of mild patients to outpatient clinics, while it is still necessary to prevent unreasonable outpatient transfer.

, authors=Mingfang HUANG, Kunhe LIN, Li XIANG, authorsList=Mingfang HUANG, Kunhe LIN, Li XIANG, authorCompany=null, correspAuthors=Kunhe LIN, Li XIANG, authorNote=null, correspAuthorsNote=
LIN Kunhe, E-mail:
XIANG Li, E-mail:
, copyrightStatement=Copyright © 2025 Chinese Journal of Public Health. All rights reserved., 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=1321169565988536540, articleId=1321169558573007014, tenantId=1146029695717560320, journalId=1319373219989389464, language=CN, title=DIP支付方式对医疗服务供给结构的影响, columnId=1320427686770622717, journalTitle=中国公共卫生, columnName=调查报告与分析, runingTitle=null, highlight=null, articleAbstract=
目的

分析区域点数法总额预算和按病种分值付费（DIP）支付方式对医疗服务结构和门诊住院结构的影响。

方法

以我国DIP试点A市和未DIP改革B市为例，收集两市2019—2022年公立医疗机构数据，分别从医疗服务结构（医疗服务性费用、药品费用、材料费用、检查检验费用）和门诊住院结构（门诊和住院费用、门诊和出院人次数）进行描述性和双重差分法分析。

结果

医疗服务结构上，DIP试点A市的住院检查检验费用较未DIP改革B市下降19.0%（P<0.05）。门诊住院结构上，A市住院费用较B市下降14.1%（P<0.05）、出院人次数下降15.8%（P<0.05）、门诊人次数上升8.3%（P<0.05）。

结论

DIP支付方式促进住院检查检验费用降低和医疗服务结构优化；DIP支付方式对“冲点”行为进行有效遏制，有助于推动轻症患者分流至门诊，但仍需防范不合理的支付方式向门诊转移。

, authors=黄明芳, 林坤河*, *, 项莉*, *, authorsList=黄明芳, 林坤河, 项莉, authorCompany=null, correspAuthors=林坤河, 项莉, authorNote=

黄明芳（1966—），助理研究员，硕士，研究方向：卫生政策、高等教育管理

, correspAuthorsNote=
林坤河，E-mail：
项莉，E-mail：
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黄明芳（1966—），助理研究员，硕士，研究方向：卫生政策、高等教育管理

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Comparison of institutions in the experimental group and control group before and after reform

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变量2019—2020年（改革前）2021—2022年（改革后）
实验组（254家）对照组（307家）χ2值P值实验组（255家）对照组（304家）χ2值P值
数量 构成比/%数量构成比/%数量构成比/%数量 构成比/%
机构等级1.6240.4441.6880.430
　一级20078.7425482.7419777.2524881.58
　二级4216.544314.014116.084113.49
　三级124.72103.26176.67154.93
机构类别5.1530.1611.8140.612
　综合5019.695317.265220.395417.76
　专科103.9441.3083.1461.97
　基层19476.3825081.43　　19576.4724480.26　　
), ArticleFig(id=1321169570182840572, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169558573007014, language=CN, label=表1, caption=

改革前后实验组与对照组机构比较

, figureFileSmall=null, figureFileBig=null, tableContent=
变量2019—2020年（改革前）2021—2022年（改革后）
实验组（254家）对照组（307家）χ2值P值实验组（255家）对照组（304家）χ2值P值
数量 构成比/%数量构成比/%数量构成比/%数量 构成比/%
机构等级1.6240.4441.6880.430
　一级20078.7425482.7419777.2524881.58
　二级4216.544314.014116.084113.49
　三级124.72103.26176.67154.93
机构类别5.1530.1611.8140.612
　综合5019.695317.265220.395417.76
　专科103.9441.3083.1461.97
　基层19476.3825081.43　　19576.4724480.26　　
), ArticleFig(id=1321169570279309565, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169558573007014, language=EN, label=Tab.2, caption=

Comparison of medical service structure and outpatient-inpatient structure in the two groups from 2019 to 2022

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指标2019—2020年（改革前）2021—2022年（改革后）
实验组对照组t值P值实验组对照组t值P值
医疗服务结构
　Ln（住院医疗服务性总费用）14.4914.291.2360.21714.4814.360.7070.480
　Ln（住院药品总费用）14.2014.031.1300.25913.9319.890.2780.781
　Ln（住院材料总费用）11.5010.672.5210.01211.0110.601.2220.221
　Ln（住院检查化验总费用）14.3414.290.3300.74214.1114.260.9160.360
门诊住院结构
　Ln（门诊医疗总费用）15.2515.001.8980.05815.4515.152.2900.022
　Ln（住院医疗总费用）15.5415.430.7040.48215.3715.41−0.2490.804
　Ln（门诊人次数）10.7210.620.9420.34110.7910.621.5270.127
　Ln（出院人次数）7.687.76−0.7020.4837.457.31−2.1910.029
), ArticleFig(id=1321169570384167166, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169558573007014, language=CN, label=表2, caption=

2019—2022年2组医疗服务结构和门诊住院结构变化比较

, figureFileSmall=null, figureFileBig=null, tableContent=
指标2019—2020年（改革前）2021—2022年（改革后）
实验组对照组t值P值实验组对照组t值P值
医疗服务结构
　Ln（住院医疗服务性总费用）14.4914.291.2360.21714.4814.360.7070.480
　Ln（住院药品总费用）14.2014.031.1300.25913.9319.890.2780.781
　Ln（住院材料总费用）11.5010.672.5210.01211.0110.601.2220.221
　Ln（住院检查化验总费用）14.3414.290.3300.74214.1114.260.9160.360
门诊住院结构
　Ln（门诊医疗总费用）15.2515.001.8980.05815.4515.152.2900.022
　Ln（住院医疗总费用）15.5415.430.7040.48215.3715.41−0.2490.804
　Ln（门诊人次数）10.7210.620.9420.34110.7910.621.5270.127
　Ln（出院人次数）7.687.76−0.7020.4837.457.31−2.1910.029
), ArticleFig(id=1321169570463858943, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169558573007014, language=EN, label=Tab.3, caption=

Estimation results of PSM-DID model

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变量 $ {\beta }_{3} $SER-squared
住院检查化验总费用−0.191 a0.0760.940
住院医疗总费用−0.141 a0.0680.967
门诊人次数0.092 b0.0340.973
出院人次数−0.158 b0.0660.949
), ArticleFig(id=1321169570598076672, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169558573007014, language=CN, label=表3, caption=

PSM-DID模型估计结果

, figureFileSmall=null, figureFileBig=null, tableContent=
变量 $ {\beta }_{3} $SER-squared
住院检查化验总费用−0.191 a0.0760.940
住院医疗总费用−0.141 a0.0680.967
门诊人次数0.092 b0.0340.973
出院人次数−0.158 b0.0660.949
), ArticleFig(id=1321169570698739969, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169558573007014, language=EN, label=Tab.4, caption=

Estimation results of DID model with 5% double tail truncation processing

, figureFileSmall=null, figureFileBig=null, tableContent=
变量 $ {\mathit{\beta }}_{3} $SER-squared
住院检查化验总费用−0.110 a0.0470.962
住院医疗总费用−0.094 b0.0320.960
门诊人次数0.058 a0.0300.981
出院人次数−0.084 a0.0350.974
), ArticleFig(id=1321169570803597570, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321169558573007014, language=CN, label=表4, caption=

5%的双尾截断处理的DID模型估计结果

, figureFileSmall=null, figureFileBig=null, tableContent=
变量 $ {\mathit{\beta }}_{3} $SER-squared
住院检查化验总费用−0.110 a0.0470.962
住院医疗总费用−0.094 b0.0320.960
门诊人次数0.058 a0.0300.981
出院人次数−0.084 a0.0350.974
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DIP支付方式对医疗服务供给结构的影响
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黄明芳 , 林坤河 *, * , 项莉 *, *
中国公共卫生 | 调查报告与分析 2025,41(11): 1373-1378
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中国公共卫生 |调查报告与分析 2025 , 41 (11) : 1373 -1378
DIP支付方式对医疗服务供给结构的影响
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黄明芳, 林坤河*, * , 项莉*, *
作者信息
  • 华中科技大学同济医学院医药卫生管理学院，武汉 430030
通讯作者:
林坤河，E-mail：
项莉，E-mail：
作者简介:

黄明芳（1966—），助理研究员，硕士，研究方向：卫生政策、高等教育管理

Impact of DIP payment method on the structure of medical service supply
Mingfang HUANG, Kunhe LIN , Li XIANG
Affiliations
  • School of Medicine and Health Management, Tongji Medical college of Huazhong University of Science and Technology, Wuhan 430030, China
    • Corresponding Author:
    LIN Kunhe, E-mail:
    XIANG Li, E-mail:
出版时间: 2025-11-10 doi: 10.11847/zgggws1147539
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摘要
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目的

分析区域点数法总额预算和按病种分值付费（DIP）支付方式对医疗服务结构和门诊住院结构的影响。

方法

以我国DIP试点A市和未DIP改革B市为例，收集两市2019—2022年公立医疗机构数据，分别从医疗服务结构（医疗服务性费用、药品费用、材料费用、检查检验费用）和门诊住院结构（门诊和住院费用、门诊和出院人次数）进行描述性和双重差分法分析。

结果

医疗服务结构上，DIP试点A市的住院检查检验费用较未DIP改革B市下降19.0%（P<0.05）。门诊住院结构上，A市住院费用较B市下降14.1%（P<0.05）、出院人次数下降15.8%（P<0.05）、门诊人次数上升8.3%（P<0.05）。

结论

DIP支付方式促进住院检查检验费用降低和医疗服务结构优化；DIP支付方式对“冲点”行为进行有效遏制，有助于推动轻症患者分流至门诊，但仍需防范不合理的支付方式向门诊转移。

区域点数法总额预算和按病种分值付费(DIP)  /  医保支付方式  /  医疗服务供给  /  结构性
Objective

To analyze the impact of diagnosis-intervention packet (DIP) payment method on the medical service structure and outpatient-inpatient structure.

Methods

Data were collected from public medical institutions in DIP pilot city A and non-DIP reform city B in China from 2019 to 2022. Descriptive and difference-in differences-analyses were conducted on the medical service structure (medical service costs, drug costs, material costs, and examination and testing costs) and outpatient-inpatient structure (outpatient and inpatient costs, outpatient visits, and number of inpatient discharges).

Results

In terms of medical service structure, the examination and testing costs in city A decreased by 19.0% compared with those in city B (P < 0.05). In terms of the outpatient-inpatient structure, compared with city B, city A saw a 14.1% decrease in inpatient costs (P < 0.05), a 15.8% decrease in the number of inpatient discharges (P < 0.05), and an 8.3% increase in outpatient visits (P < 0.05).

Conclusions

The DIP payment method promotes optimization of the medical service structure. It effectively suppresses the behavior of "rushing points" and helps to promote the diversion of mild patients to outpatient clinics, while it is still necessary to prevent unreasonable outpatient transfer.

diagnosis-intervention packet (DIP)  /  medical insurance payment method  /  medical service supply  /  structural perspective
黄明芳, 林坤河, 项莉. DIP支付方式对医疗服务供给结构的影响. 中国公共卫生, 2025 , 41 (11) : 1373 -1378 . DOI: 10.11847/zgggws1147539
Mingfang HUANG, Kunhe LIN, Li XIANG. Impact of DIP payment method on the structure of medical service supply[J]. Chinese Journal of Public Health, 2025 , 41 (11) : 1373 -1378 . DOI: 10.11847/zgggws1147539
正文
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区域点数法总额预算和按病种分值付费（diagnosis-intervention packet, DIP）支付方式是我国原创的医保支付工具[1]。随着国家医保局关于《DRG/DIP支付方式改革三年行动计划》出台，全国DIP支付方式改革进入深水区。但现有研究更多聚焦在费用控制、效率提升、质量转变等医疗服务供给方面的研究[2–5]。从医疗机构内部医疗服务供给出发，探究医疗服务构成和门诊住院构成的结构性变化仍有所不足。通过结构分析，可以更全面地了解DIP支付方式在医疗服务供给中引发的系统变化。为此，本研究基于结构性视域，聚焦医疗服务构成和门诊住院构成的结构性变化，选择改革时间较早的国家DIP试点城市A市与未开展DIP改革的B市，通过双重差分法（Differences-in-Differences, DID）进行实证比较分析。探究DIP支付方式对医疗服务构成和门诊住院构成等医疗服务供给结构的影响。为进一步推动DIP支付方式改革和医疗服务供给结构优化提供实证依据。
1　对象与方法
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1.1　对象
本研究综合考虑数据的可获得性、对照组的匹配性以及改革试点启动时间的代表性，选择我国中部省份的全国DIP支付方式改革首批试点地级市A市作为实验组，并选取同省份内未实施DIP支付方式改革且社会经济和医疗规模相当的地级市B市作为对照组。两市门诊服务均采用传统的按项目付费支付。2021年A市启动住院服务DIP支付方式改革，而B市住院服务自2023年才开展DIP支付方式。考虑到2023年我国医保门诊统筹的全面实施，对门诊结果会产生一定额外政策干扰，故选取2019—2022年为分析时间段。由于社会办医机构的外部特征较为复杂，DIP支付方式的影响效应易受混杂因素影响。故本研究选择两市公立医疗机构作为样本机构，2019—2022年共收集样本机构数1 500家，删除不受DIP改革影响即只开展门诊服务或开展精神类、康复类业务的380家公立医疗机构，最终A市和B市的样本数合计为1 120家医疗机构。其中，DIP支付方式改革前（2019—2020年），A市的样本机构数为254家，B市为307家；DIP支付方式改革后（2021—2022年），A市的样本机构数为255家，B市为304家。本研究设计已获得华中科技大学同济医学院医学伦理委员会伦理批准（伦审编号：2025–S058）。由于本文数据来源于回顾性数据，故而免除了本研究的知情同意。
1.2　资料收集
通过A、B市政府官网、医保局官网收集两市2019—2022年国民经济和社会发展统计公报、医保支付方式相关政策文件等定性资料；医疗服务结构（住院医疗服务性总费用、住院药品总费用、住院材料总费用、住院检查化验总费用）和门诊住院结构（门诊医疗总费用、住院医疗总费用、门诊人次数、出院人次数）等核心指标、机构级别、机构类别、职工人数、床位数、大型设备数等个体特征变量来源于两市卫生健康委卫生统计平台年报。
1.3　DID分析方法
采用Stata 18.0软件进行较为稳健的准自然实验DID分析[6]。DID应用面板数据，同时选择外部环境特征相似且DIP改革前变化趋势相近的城市作为实验组和对照组，尽可能减少内生性问题，通过固定效应估计缓解遗漏变量偏误问题。本研究以DIP支付方式作为准自然实验，DIP支付方式试点城市为实验组，未实施DIP支付方式的城市为对照组。以1和0分别对两市确定城市标识，分别以A、B两市DIP支付方式的启动时间为改革的边界，通过实验组与时间虚拟变量的交互项DID系数估计，捕捉政策干预对结局变量的效应。研究通过加入年份固定效应与医疗机构固定效应，年份固定效应吸收随时间变动的共同冲击，消除时间趋势对结局变量的系统性干扰；医疗机构固定效应则控制每个机构不随时间变化的个体异质性，避免遗漏非时间变量造成的估计偏误。两者的结合能更高效地解决潜在的选择性偏差和时不变混淆问题。纳入控制变量包括机构类型变量（机构等级、机构类别等）；服务能力变量（职工人数、床位数、大型设备数），用以捕捉医疗机构特征或外部环境中可能同时影响政策暴露与结局变量的时变因素，有助于缩小残差中的噪声，使DID系数的估计更接近真实政策效应。考虑到同一医疗机构不同时间点的观测可能存在相关性，研究使用聚类稳健标准误对医疗机构组内自相关进行校正，从而提高统计推断的可靠性。其中，本文DID模型如下：
$ \begin{split}Y_{it}= & \beta_0+\beta_1\times post_t+\beta_2\times Treat_i+\beta_3\times \\ &(Post_t\times Treat_i)+\gamma X_{it}+\mathit{u_i+\lambda_t}\text{+ϵ}_{it}\end{split} $
其中，$ {Y}_{it} $为个体$ i $在时间$ t $的结果变量被解释变量，$ {Treat}_{i} $为是否为改革地区的虚拟变量，若个体$ i $属于改革地区取1，未改革地区取0。$ {Time}_{t} $为DIP支付方式改革时点虚拟变量，政策实施后取1，否则取0。$ {Post}_{t}\times {Treat}_{i} $是实验组与DIP实施的交互项。$ {\beta }_{0} $截距项，$ {\beta }_{1} $为个体效应，$ {\beta }_{2} $为时间效应，$ {\beta }_{3} $反映的是双重差分估计量，表示政策效应。此外，$ \gamma {X}_{it} $为本研究的控制变量，$ u_i $表示个体固定效应，$ \mathit{\lambda_t} $表示时间固定效应，$ \text{{ϵ} }_{it} $为随机误差项，包含未观测到的个体或时间特异性因素。结果以P<0.05差异有统计学意义。为了验证双重差分估计结果的可靠性，本研究系统性地进行4项稳健性检验。首先，通过平行趋势检验考察实验组与对照组在政策实施前的结局变量趋势是否一致，以确保DID识别的有效性；同时，采用倾向得分匹配–双重差分（Propensity Score Matching-Difference in Differences, PSM-DID）方法，基于协变量进行样本匹配后重新估计政策效应，以缓解选择性偏差问题；通过对5%极端值进行双尾截断处理，排除极端观测值对结果的影响，确保估计结果不受极端值驱动。此外，进行500次随机安慰剂检验，观察估计系数的分布是否集中在零附近，且大多结果均在显著性阈值以上，排除随机波动影响。
1.4　统计分析
使用SPSS 24.0软件进行描述性分析，计数资料通过χ2检验进行差异性分析，计量资料通过t检验分析。医疗费用和人次数变量存在偏态，经过自然对数变换使其分布正态化。
2　结　果
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2.1　改革前后两组机构基本信息比较（表1）
两组不同等级和不同类型医疗机构的分布结果在改革前后差异均无统计学意义（P>0.05），说明2组的医疗机构在机构分布和资源供给上具有相似性。故而，从总体上可以认为两组2019—2022年不存在异质性趋势。其中，实验组医疗机构的平均大型设备数在改革前（10.52个）和改革后（13.10个）均显著高于对照组改革前（8.27个）和改革后（9.83个），差异有统计学意义（t=4.462，P<0.001；t=5.433，P<0.001）。但显著性结果在改革前后始终存在，说明在2019—2022年未发生明显变化。
2.2　两组医疗服务结构和门诊住院结构变化（表2）
从医疗服务结构来看，实验组与对照组住院医疗服务性总费用、住院药品总费用、住院检查化验总费用改革后差异均无统计学意义（P>0.05）。实验组住院材料费用改革前显著高于对照组（P<0.05），而改革后差异无统计学意义（P>0.05）。门诊住院结构实验组与对照组的门诊医疗总费用由改革前差异无统计学意义（P>0.05），转变为改革后实验组显著高于对照组（P<0.05）。实验组与对照组的出院人次数由改革前差异无统计学意义（P>0.05），转变为改革后实验组显著低于对照组，差异有统计学意义（P<0.05）。
2.3　两组结果指标改革前后DID模型比较
从医疗服务结构来看，实验组与对照组住院医疗服务性总费用、住院药品总费用、住院材料总费用在DIP支付方式改革后差异均无统计学意义（P>0.1）。仅实验组住院检查化验总费用较对照组显著下降，降幅为19.0%（$ {\beta }_{3} $= −0.190，95%CI= −0.335～−0.045，P=0.010）。从门诊住院结构来看，实验组医疗机构的门诊医疗总费用与对照组之间在DIP支付方式改革后差异无统计学意义（P>0.05）实验组住院医疗总费用和出院人次数在DIP支付方式改革后较对照组显著下降，降幅为14.1%和15.8%（$ {\beta }_{3} $=−0.141，95%CI= −0.270～−0.012，P=0.032；$ {\beta }_{3} $=−0.158，95%CI=−0.282～−0.033，P=0.014）；而实验组门诊人次数在DIP支付方式改革后较对照组显著上升，增幅为8.3%（$ {\beta }_{3} $=0.083，95%CI=0.017～0.149，P=0.014）。
2.4　稳健性检验
2.4.1　平行趋势检验（图1）
本研究以2019年为基准组，对差异有统计学意义的核心指标进行平行趋势检验。A、B两组的住院检查化验总费用、住院医疗总费用、门诊人次数、出院人次数在DIP改革前系数的置信区间均包含0。因此，各核心指标在DIP改革前的变化趋势可以认为保持一致，故证明使用DID模型评估的合理性。
2.4.2　PSM-DID检验（表3）
本研究采用logit回归，运用控制变量作为反映机构个体初始差异，估计样本接受处理的概率，生成每个样本的倾向得分。使用半径匹配法进行得分匹配，运用共同支持区域限制，将超出倾向得分重叠范围的样本剔除，共剔除24个样本（实验组9个，对照组15个），保留1 096个样本。结果表明，住院检查化验总费用、住院医疗总费用、门诊人次数、出院人次数4个指标在DIP支付方式改革后差异均有统计学意义（P<0.05）。且系数的正负符号与主效应分析保持一致，说明分析结果较为稳健。
2.4.3　敏感性检验（表4）
对实验组和对照组1 120家医疗机构的原始数据集进行5%的双尾截断，得到1 003家医疗机构观测值，以进行敏感性分析。结果显示，各医疗机构住院检查化验总费用、住院医疗总费用、门诊人次数、出院人次数差异仍有统计学意义（均P<0.05）。且系数的正负符号与主效应分析保持一致，说明分析结果较为稳健。
2.4.4　安慰剂检验（图2）
在保持控制变量一致的情况下，进行500次安慰剂检验。采用分层随机化方法，重复进行500次随机分配，将所有样本随机分配至虚拟的实验组和对照组，并在每次随机化后使用DID模型估计“虚拟政策”效应。由于这500次分配均为随机生成，理论上不存在真实的政策效应。4个显著性指标在安慰剂检验中的估计结果大多差异无统计学意义，且系数远离实际值。表明统计结果的显著性并非受随机波动影响，体现了分析结果的稳健性。
3　讨　论
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本研究结果表明，实验组在DIP支付方式改革后住院检查化验费用较对照组出现明显抑制效应。在过往研究中指出，自国家医保局成立后，医疗服务价格调整与集中采购等政策出台，遏制医疗机构以药养医和以耗养医产生的药品耗材项目过度使用[7–9]。故而，两组间的住院医疗服务性总费用、住院药品总费用、住院材料总费用无显著差异。但是，同时也引发由于医疗信息的不对称[10–11]，医疗机构向检查化验费用转嫁的风险，导致非必要的检查化验项目增加[12]。实验组检查化验费用的降低主要得益于DIP支付方式通过病种支付标准建立了费用阈值，其将医保支付与患者自付设定为约束性分配比。由于医保支付与患者自付的负相关关系[13]，非必要的检查化验项目的增加会导致患者自付的提升，而患者自付增加则直接造成医保支付的减少。在此支付框架下，以往通过检查化验项目增加医疗费用的不合理医疗服务行为仅会带来医疗机构的成本提升，而并不能带来实际的利益回报[3]。同时，也会因为检查化验项目的增加而造成患者费用敏感度提升，降低患者对医疗机构的满意度。从而激励医疗机构在既定支付标准内加强精细化管理和医疗服务结构的合理调整，降低非必要检查化验项目的医疗成本，一定程度消解了医疗服务价格调整、药品耗材集中采购等政策可能诱发的结构性替代问题，真正实现成本效益。
DIP支付方式改革对实验组的住院人次数和住院医疗总费用起到了明显的抑制作用。该结论与以往研究不一致。以往研究指出，区域点数法总额预算下的DRG和DIP均存在“冲点”风险[14–16]，即由于DIP年终结算点值对所有医疗机构是一致的。各医疗机构作为独立的理性经济主体，为提升自身利益可以采取增加住院人次数来获取更高的分值，从而获得更多的医保份额。这种博弈行为可能导致住院量的激增和住院医疗总费用攀升，并对住院与门诊服务结构产生溢出性影响。德国、加拿大等部分开展区域点数法总额预算的国家也得出住院量激增的相似结论[17]。然而，实验组对出院人次数和住院医疗总费用的抑制效应，这一现象可能得益于实验组DIP改革中建立的严格监管考核机制和奖惩绩效付费制度，有效遏制了医疗机构的不合理“冲点”行为。国内外研究表明，基于监管机制和绩效付费的政策能够有效引导服务提供者根据绩效目标改善医疗服务行为[18]。这也与上海市、广州市等地通过智能监管和绩效考评成功控制医疗机构不合理医疗行为的实践相一致[19]。实验组充分利用医保大数据，对低于标准入院、二次入院等不合理“冲点”行为进行实时监控，并对违规医疗机构处以违规病例金额3倍的罚款。这种高额费用惩戒将“冲点”行为的低风险收益转变为高风险收益，从而引导医疗机构减少不合理住院收治。
DIP改革对门诊服务量具有明显的促进作用。随着“冲点”行为从优势策略转变为劣势策略，医疗机构难以通过增加住院量来提升分值。相反，通过减少非必要住院患者，一方面可以规避高额罚款风险；另一方面，区域内医疗机构共同减少住院患者控制不必要的分值增长，可以提升年终结算点值，增加每例住院患者的实际收益。因此，DIP支付方式基于点数法的病种支付机制，以经济杠杆推动医疗机构门诊与住院服务供给策略的重构。对于门诊住院结构而言，医院可以通过优化诊疗路径，将轻症患者分流至门诊，从而形成门诊服务集约化、住院服务重症化的医疗服务供给结构优化。
实验组的门诊医疗总费用在DIP支付方式改革后未产生明显影响。这与以往研究结论不一致[20–21]。以往文献结果显示，门诊住院的结构变化同样存在不合理转移的风险；医疗机构可能将住院患者的医疗服务在门诊进行二次拆解，以降低患者住院费用，获得更高的医保支付率的同时，在门诊进行二次收费，提升门诊和住院双重医疗收益的非预期行为风险[20–21]。2024年，国家医保基金飞行检查通报指出，部分医疗机构将住院治疗费用分解至门诊环节重复计费、虚增门诊就诊人次等费用转嫁行为。这一定程度反映了实验组门诊住院的结构调整主要是将不必要住院的轻症患者留在门诊进行治疗，为患者提供门诊医疗服务。实验组作为经济水平较高的城市，具有较为完善的医保队伍和信息系统建设，为门诊住院服务提供全流程的医保监管和智能监测。从而一定程度促进住院服务向合理的门诊服务分流，提升实验组门诊住院结构的优化和资源合理利用。但这与统筹地区的能力息息相关，由于地方医保监管机制存在差异和医保部门人员的执行能力不同，仍可能由于监管缺乏，造成住院服务向门诊服务的不合理转移，而为医疗机构的非预期行为提供空间。这也表明需构建结构性服务供给监管体系，以应对制度性套利行为的潜在风险。
本研究存在一些不足。为控制疫情对结果的干扰，研究选取同省份、地理位置相近的中部城市以增强样本可比性。然而，疫情具有非同步、间歇性爆发的特征，可能在月度尺度上造成异质冲击，难以被本研究的年度面板数据所充分识别和控制。建议后续研究可以采用月度或随改革时间延长剔除疫情干扰进一步验证。此外，本研究基于数据可获得性，仅对部分机构变量进行控制，而且受限于机构层面数据，难以对人口学特征进行控制。
综上所述，DIP支付方式在医疗服务结构上，一定程度阻断向检查化验等项目的费用转移路径。在门诊住院结构上，DIP支付方式显著降低住院人次数，同时促进门诊服务量上升，形成“门诊服务集约化、住院服务重症化”的分层服务格局。然而，门诊住院结构的调整仍需防范不合理转移的风险。因此，建议DIP支付方式既要对住院服务进行监管，又需要关注对门诊服务的正向或负向的溢出效应，加大门诊与住院服务行为的监管力度，利用医保智能审核系统实现全流程精准回溯。一方面防范住院服务由于“冲点”行为带来的患者激增问题；另一方面，需要对由于住院服务“冲点”行为的强力监管下向门诊服务流转的合理性管控，确保医疗服务供给结构优化的可持续性与公平性。

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2025年第41卷第11期
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doi: 10.11847/zgggws1147539
  • 接收时间：2025-03-31
  • 首发时间：2026-10-25
  • 出版时间：2025-11-10
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  • 收稿日期：2025-03-31
  • 修回日期：2025-06-03
  • 录用日期：2025-08-02
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    华中科技大学同济医学院医药卫生管理学院，武汉 430030

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2种不同金属材料的力学参数
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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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