通过条码集成和REDCap增强临床数据管理:可扩展性和适应性的创新
Rendong Zhang1, Sophie Chiron2, Regina Tyree3
1Department of Electrical and Computer Engineering, School of Engineering, Vanderbilt University, Nashville, US.
JMIR formative research
|July 28, 2025
概括
这项研究通过提高条形码准确性和系统速度来增强临床数据管理. 优化的信息系统确保在研究研究中可靠的样本跟踪和分析.
科学领域:
- 临床信息学是一种临床信息学.
- 研究中的数据管理.
背景情况:
- 传统的临床数据管理面临着条形码错误和系统性能方面的挑战.
- 不有效的数据管理阻碍了临床研究中精确的样本跟踪和分析.
研究的目的:
- 为了提高条形码的稳定性,数据的细分性和临床信息学中的系统吞吐量.
- 在胃肠道 (GI) 研究中验证增强的数据管理策略,并确保工作流集成.
主要方法:
- 在模糊条件下评估条形码技术;实施了一个动态的特定器官REDCap档案.
- 利用Docker进行信息学软件容器化,并提出了一个用于REDCap交互的本地缓存系统.
- 评估条形码准确性,数据跟踪,软件部署和系统性能与/或没有缓存.
主要成果:
- 数据矩阵条形码在模糊下显示出高精度; REDCap档案改善了样本来源跟踪.
- 对大型数据集而言,Docker容器化简化了部署;本地缓存将REDCap交互时间减少了八倍.
结论:
- 提议的改进显著提高了条形码的稳定性,数据细节性和系统吞吐量.
- 优化的信息系统为各种临床研究需求提供了高效的数据管理.
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