Article(id=1311349894909096054, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1311349802038821144, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202509126, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1757520000000, receivedDateStr=2025-09-11, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1790579778649, onlineDateStr=2026-09-28, pubDate=1783612800000, pubDateStr=2026-07-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1790579778649, onlineIssueDateStr=2026-09-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1790579778649, creator=13701087609, updateTime=1790579778649, updator=13701087609, issue=Issue{id=1311349802038821144, tenantId=1146029695717560320, journalId=1227665162245664772, year='2026', volume='53', issue='13', pageStart='2305', pageEnd='2496', issueExtLink='null', onlineDate='null', pubDate='1783612800000', pubDateStr='2026-07-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1790579756507, creator='13701087609', updateTime=1790588376143, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1311385955492258162, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1311349802038821144, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1311385955496452467, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1311349802038821144, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=2423, endPage=2430, ext={EN=ArticleExt(id=1311349896599400567, articleId=1311349894909096054, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Multilevel analysis of factors influencing cross-district/county inpatient mobility in Sichuan Province and its implications for medical resource allocation, columnId=1228016567846367388, journalTitle=Modern Preventive Medicine, columnName=Health Policy and Management, runingTitle=null, highlight=null, articleAbstract=
Objective To classify cross-district/county medical visits into upward flow (from low-GDP districts to high-GDP districts) and downward flow (from high-GDP districts to low-GDP districts), analyze their influencing factors and differences from overall cross-district/county visits, and provide theoretical support for optimal allocation of medical resources.
Methods Data were obtained from the front pages of medical records of inpatients in Sichuan Province in 2022. Taking inpatients as the study subjects, two types of cross-district/county medical visits were classified. Geographic information software was used for spatial visualization, and a two-level random intercept logistic regression model was applied to analyze influencing factors from patient, institutional and regional dimensions.
Results In 2022, the proportion of cross-district/county hospitalization in Sichuan was 29.20%, including 23.37% upward flow and 5.83% downward flow. Maintenance chemotherapy for malignant tumors accounted for the highest proportion in overall (4.97%) and upward flow (6.67%), while schizophrenia (2.69%) ranked first in downward flow. West China Hospital of Sichuan University in Wuhou District was the top choice for overall (5.69%) and upward flow (7.10%), and Chengdu Second People’s Hospital in Jinjiang District was preferred for downward flow (7.92%). The effects of occupation type, medical insurance and other individual factors became more significant after distinguishing the two flows.
Conclusion Upward and downward cross-district/county medical visits showed distinct demand differences: the former pursues high-quality medical services, while the latter mainly focuses on rehabilitation and other needs. Local governments should strengthen specialized or primary care services based on patient outflow and resource conditions, improve the rate of seeking care within the county, and promote the efficient, fair and sustainable development of the medical service system.
, authors=Jing-Hua WANG
1, 2, Lu AO
1, 2, Xian-Ge AN
1, 2, Chao SONG
1, 2, Xiu-Li WANG
1, 2, authorsList=Jing-Hua WANG, Lu AO, Xian-Ge AN, Chao SONG, Xiu-Li WANG, authorCompany=null, correspAuthors=Xiu-Li WANG, 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=1311349899074039950, articleId=1311349894909096054, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=四川省住院患者跨区县流动的多水平影响分析及对医疗资源配置的启发研究, columnId=1228016568014139551, journalTitle=现代预防医学, columnName=卫生政策与管理, runingTitle=null, highlight=null, articleAbstract=
目的 将跨区县就医细分为向上(GDP低区县流向高区县)和向下(GDP高区县流向低区县)两类,分析影响因素及与整体跨区县就医的差异,为医疗资源优化配置提供理论支撑。
方法 数据来源于2022年四川省住院患者病案首页,以住院患者为研究对象,划分两类跨区县就医类型,采用地理信息软件可视化就医情况,运用两水平随机截距logistic回归模型,从患者、机构、地区层面分析影响因素。
结果 2022年四川省跨区县住院占比29.20%,其中向上就医23.37%、向下就医5.83%;恶性肿瘤维持性化疗在整体(4.97%)及向上就医(6.67%)中占比最高,精神分裂症(2.69%)在向下就医中占比最高;武侯区四川大学华西医院是整体(5.69%)及向上就医(7.10%)首选,向下就医主要选择锦江区成都市第二人民医院(7.92%);区分两类就医后,个人层面工作类型、医保等因素的影响更显著。
结论 向上与向下跨区县就医需求差异明显,前者追求优质医疗服务,后者以康复等需求为主。各地应结合外流情况与资源条件,强化专科或基层服务,提升县域就诊率,推动医疗服务体系高效公平可持续发展。
, authors=王晶华
1, 2, 敖露
1, 2, 安宪革
1, 2, 宋超
1, 2, 王秀丽
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王晶华(2001—),女,硕士在读,研究方向:健康与社会行为学
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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=6iLS8wR6X3MZYqsBfDZ2Sw==, magXml=E2EUNYVpen4rW2tdO6ybzw==, pdfUrl=null, pdf=aX+WGt/hZTXntCkiDJi4gg==, pdfFileSize=1412424, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=Z59OWMuH0XXAgwXUL94lqA==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=pxPGarCnzHVHdyoVCqzA/Q==, mapNumber=null, fund=null)}, authors=[Author(id=1311349901032779925, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349894909096054, 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=1311349901120860312, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349894909096054, authorId=1311349901032779925, language=EN, stringName=Jing-Hua WANG, firstName=Jing-Hua, middleName=null, lastName=WANG, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=
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1.四川大学华西公共卫生学院/华西第四医院,四川 成都 610041
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Hospitalization rate and proportion of patients seeking cross-district/county medical care in Sichuan Province, figureFileSmall=6IMvJQ+whNWc0XKEtSIarg==, figureFileBig=Z59OWMuH0XXAgwXUL94lqA==, tableContent=null), ArticleFig(id=1311349903058628793, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349894909096054, language=CN, label=图1, caption=
四川省住院率及跨区县患者就医占比注:A为县域住院率;B为整体跨区县就医情况;C为向上跨区县就医情况;D为向下跨区县就医情况;审图号GS(2024)0650号。
, figureFileSmall=6IMvJQ+whNWc0XKEtSIarg==, figureFileBig=Z59OWMuH0XXAgwXUL94lqA==, tableContent=null), ArticleFig(id=1311349903238983866, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349894909096054, language=EN, label=Figure 2, caption=
Hotspot and coldspot analysis of patients seeking cross-district/county medical care in Sichuan Province, figureFileSmall=rd6vFZVUH98eiWiOxpPaqw==, figureFileBig=x6I9zefsZ5pHrol+LEvgaw==, tableContent=null), ArticleFig(id=1311349903310287035, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349894909096054, language=CN, label=图2, caption=
四川省跨区县就医患者现状冷热点分析注:A为整体跨区县就医聚集情况;B为向上跨区就医聚集情况;C为向下跨区县就医聚集情况;审图号GS(2024)0650号。
, figureFileSmall=rd6vFZVUH98eiWiOxpPaqw==, figureFileBig=x6I9zefsZ5pHrol+LEvgaw==, tableContent=null), ArticleFig(id=1311349903381590204, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349894909096054, language=EN, label=Figure 3, caption=
Flow map of patients seeking cross-district/county medical care in Sichuan Province, figureFileSmall=FEZ+HHCALageUUsx91UiXw==, figureFileBig=2MNpcw2CiDn7szt58Yi8yg==, tableContent=null), ArticleFig(id=1311349903461281981, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349894909096054, language=CN, label=图3, caption=
四川省跨区县就医患者流向图注:审图号GS(2024)0650号。
, figureFileSmall=FEZ+HHCALageUUsx91UiXw==, figureFileBig=2MNpcw2CiDn7szt58Yi8yg==, tableContent=null), ArticleFig(id=1311349903528390846, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349894909096054, language=EN, label=Figure 4, caption=
Results of two-level random-intercept logistic regression analysis of factors influencing overall cross-district/county medical visits among patients, figureFileSmall=5sCHnZGdux3Qn1NSUohD3Q==, figureFileBig=9DikCXpL6HjD21HOj6KqhQ==, tableContent=null), ArticleFig(id=1311349903599694015, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349894909096054, language=CN, label=图4, caption=
患者整体跨区县就医的影响因素两水平随机截距logistic回归分析结果, figureFileSmall=5sCHnZGdux3Qn1NSUohD3Q==, figureFileBig=9DikCXpL6HjD21HOj6KqhQ==, tableContent=null), ArticleFig(id=1311349903670997184, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349894909096054, language=EN, label=Figure 5, caption=
Results of two-level random-intercept logistic regression analysis of factors influencing upward cross-district/county medical visits among patients, figureFileSmall=geT/g94jaVMhPI++hucPig==, figureFileBig=l0FKypFQbNlOXv2Hgi/3Ow==, tableContent=null), ArticleFig(id=1311349903742300353, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349894909096054, language=CN, label=图5, caption=
患者向上跨区县就医的影响因素两水平随机截距logistic回归分析结果, figureFileSmall=geT/g94jaVMhPI++hucPig==, figureFileBig=l0FKypFQbNlOXv2Hgi/3Ow==, tableContent=null), ArticleFig(id=1311349905420021954, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349894909096054, language=EN, label=Figure 6, caption=
Results of two-level random-intercept logistic regression analysis of factors influencing downward cross-district/county medical visits among patients, figureFileSmall=3IVUf2UzXVACFaVSQ3VSKA==, figureFileBig=rZstCgg6igRQ+ZrbyLebDw==, tableContent=null), ArticleFig(id=1311349905512296643, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349894909096054, language=CN, label=图6, caption=
患者向下跨区县就医的影响因素两水平随机截距logistic回归分析结果, figureFileSmall=3IVUf2UzXVACFaVSQ3VSKA==, figureFileBig=rZstCgg6igRQ+ZrbyLebDw==, tableContent=null), ArticleFig(id=1311349905575211204, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349894909096054, language=EN, label=Table 1, caption=
Description of the current status of different types of cross-district/county medical visits
, figureFileSmall=null, figureFileBig=null, tableContent=
| 类别 | 整体流出患者占比(%) | 向上流出患者占比(%) | 向下流出患者占比(%) |
|---|
| 主要流出区县 | 沿滩区(91.90) | 蓬溪县(78.44) | 金牛区(41.08) |
| 蓬溪县(79.77) | 新龙县(76.50) | 武侯区(31.76) |
| 石渠县(78.20) | 茂县(74.84) | 自流井区(30.04) |
| 主要流向区县 | 武侯区(14.34) | 武侯区(17.92) | 锦江区(12.92) |
| 青羊区(9.43) | 青羊区(8.60) | 青羊区(12.77) |
| 顺庆区(4.79) | 顺庆区(5.93) | 龙马潭区(6.36) |
| 主要流出疾病 | 恶性肿瘤维持性化学治疗(4.97) | 恶性肿瘤维持性化学治疗(6.67) | 精神分裂症(2.69) |
| 精神分裂症(1.18) | 慢性阻塞性肺疾病(1.13) | 恶性肿瘤维持性化学治疗(1.48) |
| 慢性阻塞性肺疾病(1.17) | 老年性白内障(0.86) | 腰椎间盘突出(1.35) |
| 主要流向机构 | 四川大学华西医院(5.69) | 四川大学华西医院(7.10) | 成都市第二人民医院(7.92) |
| 四川省人民医院(4.21) | 四川省人民医院(4.15) | 四川省人民医院(4.48) |
| 西南医科大学附属医院(3.10) | 西南医科大学附属医院(3.53) | 西南医科大学附属中医医院(3.95) |
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不同跨区县就医分类现状描述
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| 类别 | 整体流出患者占比(%) | 向上流出患者占比(%) | 向下流出患者占比(%) |
|---|
| 主要流出区县 | 沿滩区(91.90) | 蓬溪县(78.44) | 金牛区(41.08) |
| 蓬溪县(79.77) | 新龙县(76.50) | 武侯区(31.76) |
| 石渠县(78.20) | 茂县(74.84) | 自流井区(30.04) |
| 主要流向区县 | 武侯区(14.34) | 武侯区(17.92) | 锦江区(12.92) |
| 青羊区(9.43) | 青羊区(8.60) | 青羊区(12.77) |
| 顺庆区(4.79) | 顺庆区(5.93) | 龙马潭区(6.36) |
| 主要流出疾病 | 恶性肿瘤维持性化学治疗(4.97) | 恶性肿瘤维持性化学治疗(6.67) | 精神分裂症(2.69) |
| 精神分裂症(1.18) | 慢性阻塞性肺疾病(1.13) | 恶性肿瘤维持性化学治疗(1.48) |
| 慢性阻塞性肺疾病(1.17) | 老年性白内障(0.86) | 腰椎间盘突出(1.35) |
| 主要流向机构 | 四川大学华西医院(5.69) | 四川大学华西医院(7.10) | 成都市第二人民医院(7.92) |
| 四川省人民医院(4.21) | 四川省人民医院(4.15) | 四川省人民医院(4.48) |
| 西南医科大学附属医院(3.10) | 西南医科大学附属医院(3.53) | 西南医科大学附属中医医院(3.95) |
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Parameter estimates of the two-level null logistic regression model
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| 参数 | 估计值 | 标准误 | t值 | P值 |
|---|
| 固定效应(截距) | -0.69 | 0.01 | -69.000 | <0.001 |
| 随机效应(区县水平) | 2.29 | 1.17 | 1.960 | <0.001 |
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零模型参数估计结果
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| 参数 | 估计值 | 标准误 | t值 | P值 |
|---|
| 固定效应(截距) | -0.69 | 0.01 | -69.000 | <0.001 |
| 随机效应(区县水平) | 2.29 | 1.17 | 1.960 | <0.001 |
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Variables and coding
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| 变量 | | 赋值 |
|---|
| 跨区县就医 | 整体 | 否=0,是=1 |
| 向上 | 否=0,是=1 |
| 向下 | 否=0,是=1 |
| 性别 | | 男=0,女=1 |
| 婚姻状况 | | 无序多分类变量:未婚=0,已婚=1,丧偶=2,离异=3,其他=4 |
| 民族 | | 少数民族=0,汉族=1 |
| 医疗保险 | | 城镇职工医疗保险=0,城乡居民医疗保险=1,其他=2 |
| 职业 | | 公务员、技术人员、职工、管理人员=0,工人、农民、自由职业、无业人员=1,学生、现役军人、个体经营者=2,离退休人员=3,其他=4 |
| 医院等级 | | 一级乙等=0,一级甲等=1,二级乙等=2,二级甲等=3,三级乙等=4,三级甲等=5 |
| 医院类别 | | 综合医院=0,康复医院=1,其他医院=2 |
| 医保定点医疗机构 | | 非定点机构=0,基本医保定点机构=1 |
), ArticleFig(id=1311349905965281481, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349894909096054, language=CN, label=表3, caption=
变量与赋值
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| 变量 | | 赋值 |
|---|
| 跨区县就医 | 整体 | 否=0,是=1 |
| 向上 | 否=0,是=1 |
| 向下 | 否=0,是=1 |
| 性别 | | 男=0,女=1 |
| 婚姻状况 | | 无序多分类变量:未婚=0,已婚=1,丧偶=2,离异=3,其他=4 |
| 民族 | | 少数民族=0,汉族=1 |
| 医疗保险 | | 城镇职工医疗保险=0,城乡居民医疗保险=1,其他=2 |
| 职业 | | 公务员、技术人员、职工、管理人员=0,工人、农民、自由职业、无业人员=1,学生、现役军人、个体经营者=2,离退休人员=3,其他=4 |
| 医院等级 | | 一级乙等=0,一级甲等=1,二级乙等=2,二级甲等=3,三级乙等=4,三级甲等=5 |
| 医院类别 | | 综合医院=0,康复医院=1,其他医院=2 |
| 医保定点医疗机构 | | 非定点机构=0,基本医保定点机构=1 |
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