Article(id=1292135513885012272, tenantId=1146029695717560320, journalId=1246415772164075586, issueId=1292135444850955150, articleNumber=null, orderNo=null, doi=10.13699/j.cnki.1001-6821.2026.09.022, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1740931200000, receivedDateStr=2025-03-03, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1785998713227, onlineDateStr=2026-08-06, pubDate=1778947200000, pubDateStr=2026-05-17, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1785998713227, onlineIssueDateStr=2026-08-06, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1785998713227, creator=13701087609, updateTime=1785998713227, updator=13701087609, issue=Issue{id=1292135444850955150, tenantId=1146029695717560320, journalId=1246415772164075586, year='2026', volume='42', issue='9', pageStart='1201', pageEnd='1350', issueExtLink='null', onlineDate='null', pubDate='1778947200000', pubDateStr='2026-05-17', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1785998696767, creator='13701087609', updateTime=1786014392260, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1292201276780081469, tenantId=1146029695717560320, journalId=1246415772164075586, issueId=1292135444850955150, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1292201276784275774, tenantId=1146029695717560320, journalId=1246415772164075586, issueId=1292135444850955150, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=1345, endPage=1350, ext={EN=ArticleExt(id=1292135515705340209, articleId=1292135513885012272, tenantId=1146029695717560320, journalId=1246415772164075586, language=EN, title=Analysis of the quality of intelligent management of drugs in clinical trials, columnId=1291704889697137247, journalTitle=Chinese Journal of Clinical Pharmacology, columnName=Special Column of Clinical Trials Administration, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze the application effect of the intelligent management system for clinical trial drugs.

Methods

Based on the overall architecture established for the intelligent module and the management of experimental drugs, we compared the error rates of monthly prescriptions and recovery forms from 2024 to 2025, as well as the error rates of annual prescriptions and recovery forms from 2024 to 2025.

Results

The prescription error rates for January 2024 and 2025 were 33.33% (4 prescriptions/12 prescriptions) and 0% (0 prescriptions/19 prescriptions), respectively; for May, they were 30.00% (6 prescriptions/20 prescriptions) and 5.56% (2 prescriptions/36 prescriptions), respectively; for June, they were 36.00% (9 prescriptions/25 prescriptions) and 3.21% (6 prescriptions/187 prescriptions), respectively; for July, they were 23.91% (11 prescriptions/46 prescriptions) and 5.14% (9 prescriptions/175 prescriptions), respectively; for August, they were 10.71% (6 prescriptions/56 prescriptions) and 1.82% (3 prescriptions/165 prescriptions), respectively; for September, they were 10.20% (10 prescriptions/98 prescriptions) and 2.84% (5 prescriptions/176 prescriptions), respectively; for October, they were 13.21% (7 prescriptions/53 prescriptions) and 2.70% (2 prescriptions/74 prescriptions), respectively; for December, they were 12.50% (6 prescriptions/48 prescriptions) and 3.02% (13 prescriptions/430 prescriptions), respectively. The above indicators were statistically significant differences between the two groups (P<0.05, P<0.01). The prescription error rates for the years 2024-2025 were 12.41% (82 prescriptions/661 prescriptions) and 3.38% (60 prescriptions/1 777 prescriptions), respectively, showing a downward trend, and there were statistically significant differences between the two groups(P<0.000 1). The overall error rate of the collected forms decreased, but differences were not statistically significant (P>0.05).

Conclusion

The intelligent management system can improve the efficiency and accuracy of drug management, and it is recommended to further optimize the recovery process.

, authors=Jü LIU1, Chang XU2, Xiao-yun LIU1, Xin-na ZHOU2, Xiao-qiang CHENG1, Xiao-hua HAO1, 2, authorsList=Jü LIU, Chang XU, Xiao-yun LIU, Xin-na ZHOU, Xiao-qiang CHENG, Xiao-hua HAO, authorCompany=null, correspAuthors=Xiao-hua HAO, 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=1292135515982164274, articleId=1292135513885012272, tenantId=1146029695717560320, journalId=1246415772164075586, language=CN, title=在临床试验中药品智能化管理质量的分析, columnId=1291704889869103713, journalTitle=中国临床药理学杂志, columnName=临床试验管理专栏, runingTitle=null, highlight=null, articleAbstract=
目的

分析临床试验用药品智能化管理系统的应用效果。

方法

基于智能化模块的建立和试验用药品管理的总体架构,对比2024和2025年每月处方和回收单错误率,对比2024和2025年度处方及回收单错误率。

结果

2024年和2025年1月的处方错误率分别为33.33%(4张/12张)和0%(0张/19张);5月的分别为30.00%(6张/20张)和5.56%(2张/36张);6月的分别为36.00%(9张/25张)和3.21%(6张/187张);7月的分别为23.91%(11张/46张)和5.14%(9张/175张);8月的分别为10.71%(6张/56张)和1.82%(3张/165张);9月的分别为10.20%(10张/98张)和2.84%(5张/176张);10月的分别为13.21%(7张/53张)和2.70%(2张/74张);12月的分别为12.50%(6张/48张)和3.02%(13张/430张);2组间比较在统计学上差异均有统计学意义(P<0.05,P<0.01);2024和2025年度处方错误率分别为12.41%(82张/661张)和3.38%(60张/1 777张)呈下降趋势,2组间比较,在统计学上差异有统计学意义(P<0.000 1);回收单错误率整体下降,但在统计学上差异无统计学意义(P>0.05)。

结论

智能化管理系统可提升药品管理效率与准确性,建议进一步优化回收流程。

, authors=刘菊1, 续畅2, 刘小云1, 周心娜2, 程小强1, 郝晓花1, 2, authorsList=刘菊, 续畅, 刘小云, 周心娜, 程小强, 郝晓花, authorCompany=null, correspAuthors=郝晓花, authorNote=

刘菊(1989-),女,药师,主要从事临床试验用药品中心化管理的研究和工作

, correspAuthorsNote=
郝晓花,研究员,副教授,硕士生导师 Tel: (010)63926883 E-mail:
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在临床试验中药品智能化管理质量的分析
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刘菊 1 , 续畅 2 , 刘小云 1 , 周心娜 2 , 程小强 1 , 郝晓花 1, 2
中国临床药理学杂志 | 临床试验管理专栏 2026,42(9): 1345-1350
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中国临床药理学杂志 |临床试验管理专栏 2026 , 42 (9) : 1345 -1350
在临床试验中药品智能化管理质量的分析
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刘菊1, 续畅2, 刘小云1, 周心娜2, 程小强1, 郝晓花1, 2
作者信息
  • 1.首都医科大学 附属北京世纪坛医院 药物Ⅰ期临床试验研究室,北京 100038
  • 2.首都医科大学 附属北京世纪坛医院 药物及医疗器械临床试验机构,北京 100038
通讯作者:
郝晓花,研究员,副教授,硕士生导师 Tel: (010)63926883 E-mail:
作者简介:

刘菊(1989-),女,药师,主要从事临床试验用药品中心化管理的研究和工作

Analysis of the quality of intelligent management of drugs in clinical trials
Jü LIU1, Chang XU2, Xiao-yun LIU1, Xin-na ZHOU2, Xiao-qiang CHENG1, Xiao-hua HAO1, 2
Affiliations
  • 1.Clinical Trial Institutions for Drugs and Medical Devices, Beijing Shijitan Hospital Afflicated to Capital Medical University, Beijing 100038, China
  • 2.Phase Ⅰ Clinical Trial Center, Beijing Shijitan Hospital Afflicated to Capital Medical University, Beijing 100038, China
出版时间: 2026-05-17 doi: 10.13699/j.cnki.1001-6821.2026.09.022
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目的

分析临床试验用药品智能化管理系统的应用效果。

方法

基于智能化模块的建立和试验用药品管理的总体架构,对比2024和2025年每月处方和回收单错误率,对比2024和2025年度处方及回收单错误率。

结果

2024年和2025年1月的处方错误率分别为33.33%(4张/12张)和0%(0张/19张);5月的分别为30.00%(6张/20张)和5.56%(2张/36张);6月的分别为36.00%(9张/25张)和3.21%(6张/187张);7月的分别为23.91%(11张/46张)和5.14%(9张/175张);8月的分别为10.71%(6张/56张)和1.82%(3张/165张);9月的分别为10.20%(10张/98张)和2.84%(5张/176张);10月的分别为13.21%(7张/53张)和2.70%(2张/74张);12月的分别为12.50%(6张/48张)和3.02%(13张/430张);2组间比较在统计学上差异均有统计学意义(P<0.05,P<0.01);2024和2025年度处方错误率分别为12.41%(82张/661张)和3.38%(60张/1 777张)呈下降趋势,2组间比较,在统计学上差异有统计学意义(P<0.000 1);回收单错误率整体下降,但在统计学上差异无统计学意义(P>0.05)。

结论

智能化管理系统可提升药品管理效率与准确性,建议进一步优化回收流程。

临床试验  /  临床试验用药品管理  /  临床试验项目管理系统
Objective

To analyze the application effect of the intelligent management system for clinical trial drugs.

Methods

Based on the overall architecture established for the intelligent module and the management of experimental drugs, we compared the error rates of monthly prescriptions and recovery forms from 2024 to 2025, as well as the error rates of annual prescriptions and recovery forms from 2024 to 2025.

Results

The prescription error rates for January 2024 and 2025 were 33.33% (4 prescriptions/12 prescriptions) and 0% (0 prescriptions/19 prescriptions), respectively; for May, they were 30.00% (6 prescriptions/20 prescriptions) and 5.56% (2 prescriptions/36 prescriptions), respectively; for June, they were 36.00% (9 prescriptions/25 prescriptions) and 3.21% (6 prescriptions/187 prescriptions), respectively; for July, they were 23.91% (11 prescriptions/46 prescriptions) and 5.14% (9 prescriptions/175 prescriptions), respectively; for August, they were 10.71% (6 prescriptions/56 prescriptions) and 1.82% (3 prescriptions/165 prescriptions), respectively; for September, they were 10.20% (10 prescriptions/98 prescriptions) and 2.84% (5 prescriptions/176 prescriptions), respectively; for October, they were 13.21% (7 prescriptions/53 prescriptions) and 2.70% (2 prescriptions/74 prescriptions), respectively; for December, they were 12.50% (6 prescriptions/48 prescriptions) and 3.02% (13 prescriptions/430 prescriptions), respectively. The above indicators were statistically significant differences between the two groups (P<0.05, P<0.01). The prescription error rates for the years 2024-2025 were 12.41% (82 prescriptions/661 prescriptions) and 3.38% (60 prescriptions/1 777 prescriptions), respectively, showing a downward trend, and there were statistically significant differences between the two groups(P<0.000 1). The overall error rate of the collected forms decreased, but differences were not statistically significant (P>0.05).

Conclusion

The intelligent management system can improve the efficiency and accuracy of drug management, and it is recommended to further optimize the recovery process.

clinical trial  /  trial drug management  /  clinical trial project management system
刘菊, 续畅, 刘小云, 周心娜, 程小强, 郝晓花. 在临床试验中药品智能化管理质量的分析. 中国临床药理学杂志, 2026 , 42 (9) : 1345 -1350 . DOI: 10.13699/j.cnki.1001-6821.2026.09.022
Jü LIU, Chang XU, Xiao-yun LIU, Xin-na ZHOU, Xiao-qiang CHENG, Xiao-hua HAO. Analysis of the quality of intelligent management of drugs in clinical trials[J]. Chinese Journal of Clinical Pharmacology, 2026 , 42 (9) : 1345 -1350 . DOI: 10.13699/j.cnki.1001-6821.2026.09.022

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doi: 10.13699/j.cnki.1001-6821.2026.09.022
  • 接收时间:2025-03-03
  • 首发时间:2026-08-06
  • 出版时间:2026-05-17
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  • 收稿日期:2025-03-03
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    1.首都医科大学 附属北京世纪坛医院 药物Ⅰ期临床试验研究室,北京 100038
    2.首都医科大学 附属北京世纪坛医院 药物及医疗器械临床试验机构,北京 100038

通讯作者:

郝晓花,研究员,副教授,硕士生导师 Tel: (010)63926883 E-mail:
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Genus
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species
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Percentage of total
species (%)
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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