临床试验的代码集中监控,共享开放科学解决方案以获得高质量的数据
André Daher1, Júlio Castro-Alves2, Leandro Amparo1
1Vice-presidency of Research and Biological Collections, Oswaldo Cruz Foundation (Fiocruz), Rio de Janeiro, Brazil.
PloS one
|November 22, 2023
概括
这项研究引入了一种用于COVID-19临床试验的新型集中监测工具,提高数据质量和研究完整性. 该工具支持基于风险的监测 (RBM) 的采用,这对于保护人类受试者和确保可靠的试验结果至关重要.
科学领域:
- 临床研究 临床研究
- 医疗信息学 医疗信息学
背景情况:
- 临床试验监测对于人类受试者保护和研究质量至关重要.
- 基于风险的监测 (RBM) 的采用尽管有好处,但仍滞后.
- 随着COVID-19的流行,远程和集中监测策略的需求加快了.
研究的目的:
- 描述COVID-19临床试验集中监测工具的开发和功能.
- 评估该工具在确保数据质量的优势和局限性.
- 通过共享软件代码和案例报告表 (CRF) 来促进开放科学实践.
主要方法:
- 开发一个集中的监控工具,与案例报告表格 (CRF) 和自动化程序集成.
- 在巴西卫生部的Fiocruz临床研究平台上实施.
- 利用基于风险的监测 (RBM) 的原则,包括减少源数据验证 (SDV) 和源文档审查 (SDR).
主要成果:
- 开发的工具有助于集中监控,这是RBM的关键组成部分.
- 同步的自动化程序和集成的CRF提高了数据质量保证.
- 该工具在与流行病有关的中断期间管理临床试验的实用性得到了证明.
结论:
- 集中监测工具是改善临床试验数据质量的宝贵资产,特别是在资源有限的环境中.
- 采用此类工具支持临床研究中向基于风险的监测 (RBM) 过渡.
- 软件代码和CRF的共享符合开放科学原则,促进合作和可重复性.
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