Institute of Bone and Joint Research, The Australian Arthritis and Autoimmune Biobank Collaborative, Kolling Institute, University of Sydney, Sydney, Australia.
Public Health and Preventive Medicine, Monash University, Clayton, Australia.
Biopreserv Biobank. 2022 Jun;20(3):244-259. doi: 10.1089/bio.2021.0098. Epub 2021 Nov 22.
A key element in the big data revolution is large-scale biobanking and the associated development of high-quality data collections and supporting informatics solutions. As such, in establishing the Australian Arthritis and Autoimmune Biobank Collaborative (A3BC), we sought to establish a low-cost, nation-scale data management system capable of managing a multisite biobank registry with complex longitudinal sample and data requirements. We assessed several international commercial and nonprofit software platforms using standardized system requirement criteria and follow-up interviews. Vendor compliance scoring was prioritized to meet our project-critical requirements. Consumer/end-user codesign was integral to refining our system requirements for optimized adoption. Customization of the selected software solution was performed to optimize field auto-population between participant timepoints and forms, using modules that are transferable and that do not impact core code. Institutional and independent testing was used to ensure data security. We selected the widely used research web application Research Electronic Data Capture (REDCap), which is "free" (under nonprofit license agreement terms), highly configurable, and customizable to a variety of biobank and registry needs and can be developed/maintained by biobank users with modest IT skill, time, and cost. We created a secure, comprehensive participant-centric biobank-registry database that includes: (1) best practice data security measures (incl. multisite access login using institutional user credentials), (2) permission-to-contact and dynamic itemized electronic consent, (3) a complete chain of custody from consent to longitudinal biospecimen data collection to publication, (4) complex longitudinal patient-reported surveys, (5) integration of record-level extracted/linked participant data, (6) significant form auto-population for streamlined data capture, and (7) native dashboards for operational visualizations. We recommend the versatile, reusable, and sustainable informatics model we have developed in REDCap for prospective chronic disease biobanks or registry biobanks (of local to national complexity) supporting holistic research into disease prediction, precision medicine, and prevention strategies.
大数据革命的一个关键要素是大规模生物银行,以及相关的高质量数据集的开发和支持信息学解决方案。因此,在建立澳大利亚关节炎和自身免疫性生物银行协作组织(A3BC)时,我们旨在建立一个低成本的、全国规模的数据管理系统,能够管理具有复杂纵向样本和数据要求的多站点生物银行登记处。我们使用标准化的系统需求标准和后续访谈评估了几个国际商业和非营利软件平台。供应商合规评分被优先考虑,以满足我们项目的关键要求。消费者/最终用户共同设计是优化我们的系统需求以实现优化采用的重要组成部分。选择的软件解决方案进行了定制,以优化参与者时间点和表单之间的字段自动填充,使用可转移且不影响核心代码的模块。机构和独立测试用于确保数据安全。我们选择了广泛使用的研究网络应用程序 Research Electronic Data Capture(REDCap),它是“免费的”(根据非营利许可证协议条款),高度可配置,并且可以根据各种生物银行和登记处的需求进行定制,并且可以由具有适度 IT 技能、时间和成本的生物银行用户进行开发/维护。我们创建了一个安全、全面的以参与者为中心的生物银行登记处数据库,其中包括:(1)最佳实践的数据安全措施(包括使用机构用户凭据的多站点访问登录),(2)许可联系和动态逐项电子同意,(3)从同意到纵向生物样本数据收集到发布的完整监管链,(4)复杂的纵向患者报告调查,(5)记录级提取/链接参与者数据的集成,(6)简化数据捕获的重要表单自动填充,以及(7)用于操作可视化的本机仪表板。我们推荐在 REDCap 中开发的灵活、可重复使用且可持续的信息学模型,用于支持疾病预测、精准医学和预防策略的整体研究的前瞻性慢性疾病生物银行或登记处生物银行(具有本地到全国的复杂性)。