324 An umbrella protocol that establishes an enterprise-wide framework for the operation of a Clinical Data Warehouse

IF 2.1 Q3 MEDICINE, RESEARCH & EXPERIMENTAL Journal of Clinical and Translational Science Pub Date : 2024-04-03 DOI:10.1017/cts.2024.294
Daniella Garofalo, Allison Orechwa, Neil Bahroos
{"title":"324 An umbrella protocol that establishes an enterprise-wide framework for the operation of a Clinical Data Warehouse","authors":"Daniella Garofalo, Allison Orechwa, Neil Bahroos","doi":"10.1017/cts.2024.294","DOIUrl":null,"url":null,"abstract":"OBJECTIVES/GOALS: To streamline the standards and procedures for operating a research-specific, clinical data warehouse, acheived by defining roles, introducing a common language, and categorizing dataset types to provide transparency regarding data security risks inherent in the use of patient data. METHODS/STUDY POPULATION: We established a Bioethics committee responsible for ensuring clinical data is securely procured, maintained, and extracted in a manner that adheres to all federal, state, and local laws. We created an operational framework in the form of an umbrella IRB protocol and shared it with the bioethics committee for feedback and approval. The protocol was approved first by the bioethics committee and subsequently by the IRB. It was then disseminated across the institution and published online for continuous reference and use by committee members, researchers, and the data warehouse service team. RESULTS/ANTICIPATED RESULTS: The resulting framework defined the roles of researchers, data warehouse service team members, and honest brokers; explains the procedures for accessing and securely delivering data; and lists six categories of datasets according to type and implicit risks: datasets that are preparatory for research/aggregate counts, anonymized datasets, coded datasets, limited datasets, identified datasets for recruitment purposes, and defined identified cohort datasets. The protocol is approved and in use enterprise-wide, has reduced the number of questions from stakeholders, and has given researchers, IRB members, and informatics staff confidence in the use of the clinical research data warehouse. DISCUSSION/SIGNIFICANCE: We offer our framework to CTSAs interested in streamlining their data warehouse operations. We believe the adoption of this framework will establish strong procedures for ensuring compliance with IRB requirements, data privacy, and data security while reducing barriers to clinical research.","PeriodicalId":15529,"journal":{"name":"Journal of Clinical and Translational Science","volume":"32 1","pages":""},"PeriodicalIF":2.1000,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Clinical and Translational Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1017/cts.2024.294","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
引用次数: 0

Abstract

OBJECTIVES/GOALS: To streamline the standards and procedures for operating a research-specific, clinical data warehouse, acheived by defining roles, introducing a common language, and categorizing dataset types to provide transparency regarding data security risks inherent in the use of patient data. METHODS/STUDY POPULATION: We established a Bioethics committee responsible for ensuring clinical data is securely procured, maintained, and extracted in a manner that adheres to all federal, state, and local laws. We created an operational framework in the form of an umbrella IRB protocol and shared it with the bioethics committee for feedback and approval. The protocol was approved first by the bioethics committee and subsequently by the IRB. It was then disseminated across the institution and published online for continuous reference and use by committee members, researchers, and the data warehouse service team. RESULTS/ANTICIPATED RESULTS: The resulting framework defined the roles of researchers, data warehouse service team members, and honest brokers; explains the procedures for accessing and securely delivering data; and lists six categories of datasets according to type and implicit risks: datasets that are preparatory for research/aggregate counts, anonymized datasets, coded datasets, limited datasets, identified datasets for recruitment purposes, and defined identified cohort datasets. The protocol is approved and in use enterprise-wide, has reduced the number of questions from stakeholders, and has given researchers, IRB members, and informatics staff confidence in the use of the clinical research data warehouse. DISCUSSION/SIGNIFICANCE: We offer our framework to CTSAs interested in streamlining their data warehouse operations. We believe the adoption of this framework will establish strong procedures for ensuring compliance with IRB requirements, data privacy, and data security while reducing barriers to clinical research.
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
324 为临床数据仓库的运行建立全企业框架的总协议
目的/目标:通过定义角色、引入通用语言以及对数据集类型进行分类,简化针对特定研究的临床数据仓库的操作标准和程序,从而使患者数据使用过程中固有的数据安全风险透明化。方法/研究对象:我们成立了一个生物伦理委员会,负责确保临床数据的安全采购、维护和提取符合所有联邦、州和地方法律。我们以总体 IRB 协议的形式创建了一个操作框架,并与生物伦理委员会共享,以获得反馈和批准。该协议首先获得了生物伦理委员会的批准,随后又获得了 IRB 的批准。随后,该协议在整个机构内传播,并在网上发布,供委员会成员、研究人员和数据仓库服务团队持续参考和使用。结果/预期结果:由此产生的框架界定了研究人员、数据仓库服务团队成员和诚信经纪人的角色;解释了访问和安全交付数据的程序;并根据类型和隐含风险列出了六类数据集:准备研究的数据集/汇总计数、匿名数据集、编码数据集、有限数据集、用于招募目的的已识别数据集和已定义的已识别队列数据集。该协议已获批准并在整个企业范围内使用,减少了利益相关者提出的问题数量,并使研究人员、IRB 成员和信息学人员对临床研究数据仓库的使用充满信心。讨论/意义:我们向有意简化数据仓库操作的临床研究机构提供了我们的框架。我们相信,采用该框架将建立强有力的程序,确保符合 IRB 要求、数据隐私和数据安全,同时减少临床研究的障碍。
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
Journal of Clinical and Translational Science
Journal of Clinical and Translational Science MEDICINE, RESEARCH & EXPERIMENTAL-
CiteScore
2.80
自引率
26.90%
发文量
437
审稿时长
18 weeks
期刊最新文献
Overview of ACTIV trial-specific lessons learned. Preparing better: Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) therapeutics trials lessons learned: A call to the future. The future is now: Using the lessons learned from the ACTIV COVID-19 therapeutics trials to create an inclusive and efficient clinical trials enterprise. ACTIV trials: Lessons learned in trial design in the setting of an emergent pandemic. Lessons learned from COVID-19 to overcome challenges in conducting outpatient clinical trials to find safe and effective therapeutics for the next infectious pandemic.
×
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