A Tool for Specifying Data Quality Checks for Clinical Data Management Systems - A Technical Case Report.

Q3 Health Professions Studies in Health Technology and Informatics Pub Date : 2023-09-12 DOI:10.3233/SHTI230705
Florian Ulbrich, Frank A Meineke, Florian Rissner, Alfred Winter, Matthias Löbe
{"title":"A Tool for Specifying Data Quality Checks for Clinical Data Management Systems - A Technical Case Report.","authors":"Florian Ulbrich,&nbsp;Frank A Meineke,&nbsp;Florian Rissner,&nbsp;Alfred Winter,&nbsp;Matthias Löbe","doi":"10.3233/SHTI230705","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Prospective data collection in clinical trials is considered the gold standard of clinical research. Validating data entered in input fields in case report forms is unavoidable to maintain good data quality. Data quality checks include both the conformance of individual inputs to the specification of the data element, the detection of missing values, and the plausibility of the values entered.</p><p><strong>State-of-the-art: </strong>Besides Libre-/OpenClinica there are many applications for capturing clinical data. While most of them have a commercial approach, free and open-source solutions lack intuitive operation.</p><p><strong>Concept: </strong>Our ocRuleTool is made for the specific use case to write validation rules for Open-/LibreClinica, a clinical study management software for designing case report forms and managing medical data in clinical trials. It addresses parts of all three categories of data quality checks mentioned above.</p><p><strong>Implementation: </strong>The required rules and error messages are entered in the normative Excel specification and then converted to an XML document which can be uploaded to Open-/LibreClinica. The advantage of this intermediate step is a better readability as the complex XML elements are broken down into easy to fill out columns in Excel. The tool then generates the ready to use XML file by itself.</p><p><strong>Lessons learned: </strong>This approach saves time, is less error-prone and allows collaboration with clinicians on improving data quality.</p><p><strong>Conclusion: </strong>Our ocRuleTool has proven useful in over a dozen studies. We hope to increase the user base by releasing it to open source on GitHub.</p>","PeriodicalId":39242,"journal":{"name":"Studies in Health Technology and Informatics","volume":"307 ","pages":"137-145"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Studies in Health Technology and Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/SHTI230705","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Health Professions","Score":null,"Total":0}
引用次数: 0

Abstract

Introduction: Prospective data collection in clinical trials is considered the gold standard of clinical research. Validating data entered in input fields in case report forms is unavoidable to maintain good data quality. Data quality checks include both the conformance of individual inputs to the specification of the data element, the detection of missing values, and the plausibility of the values entered.

State-of-the-art: Besides Libre-/OpenClinica there are many applications for capturing clinical data. While most of them have a commercial approach, free and open-source solutions lack intuitive operation.

Concept: Our ocRuleTool is made for the specific use case to write validation rules for Open-/LibreClinica, a clinical study management software for designing case report forms and managing medical data in clinical trials. It addresses parts of all three categories of data quality checks mentioned above.

Implementation: The required rules and error messages are entered in the normative Excel specification and then converted to an XML document which can be uploaded to Open-/LibreClinica. The advantage of this intermediate step is a better readability as the complex XML elements are broken down into easy to fill out columns in Excel. The tool then generates the ready to use XML file by itself.

Lessons learned: This approach saves time, is less error-prone and allows collaboration with clinicians on improving data quality.

Conclusion: Our ocRuleTool has proven useful in over a dozen studies. We hope to increase the user base by releasing it to open source on GitHub.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
临床数据管理系统中指定数据质量检查的工具-技术案例报告。
临床试验前瞻性数据收集被认为是临床研究的金标准。为了保持良好的数据质量,在报表的输入字段中验证输入的数据是不可避免的。数据质量检查包括单个输入与数据元素规范的一致性、缺失值的检测以及输入值的合理性。最先进的:除了Libre /OpenClinica之外,还有许多用于获取临床数据的应用程序。虽然它们中的大多数都有商业方法,但免费和开源的解决方案缺乏直观的操作。概念:我们的ocRuleTool是为Open-/LibreClinica的特定用例编写验证规则而制作的,Open-/LibreClinica是一款临床研究管理软件,用于设计病例报告表格和管理临床试验中的医疗数据。它解决了上面提到的所有三类数据质量检查的部分问题。实现:在规范的Excel规范中输入所需的规则和错误消息,然后转换为可上传到Open-/LibreClinica的XML文档。这个中间步骤的优点是可读性更好,因为复杂的XML元素在Excel中被分解成易于填写的列。然后,该工具自己生成可使用的XML文件。经验教训:这种方法节省了时间,不易出错,并允许与临床医生合作提高数据质量。结论:我们的ocRuleTool已经在十几项研究中被证明是有用的。我们希望通过在GitHub上发布开源版本来增加用户基数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Studies in Health Technology and Informatics
Studies in Health Technology and Informatics Health Professions-Health Information Management
CiteScore
1.20
自引率
0.00%
发文量
1463
期刊介绍: This book series was started in 1990 to promote research conducted under the auspices of the EC programmes’ Advanced Informatics in Medicine (AIM) and Biomedical and Health Research (BHR) bioengineering branch. A driving aspect of international health informatics is that telecommunication technology, rehabilitative technology, intelligent home technology and many other components are moving together and form one integrated world of information and communication media.
期刊最新文献
Virtual Reality Assessment Reveals Myopic Regression After ICL Implantation in High Myopia. Construction of Guideline-Based Decision Tree for Medication Recommendation. Systemic Risk Management Plan for Electronic Medical Records (EMR): Why and How? Mental Health Patient Portals Aimed at Depression: A Picture Close to Reality. Mettertron - Bridging Metadata Repositories and Terminology Servers.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1