Importation and analysis of data from a multi-center randomized controlled clinical research on total knee arthroplasty based on REDCap system
10.3969/j.issn.1672-8467.2025.01.016
- VernacularTitle:基于REDCap系统导入及分析全膝关节置换术多中心随机对照临床研究数据
- Author:
Yu LIU
1
;
Pei-hua CAO
1
;
Chang-hai DING
1
Author Information
1. 南方医科大学珠江医院临床研究中心 广州 510280
- Publication Type:Journal Article
- Keywords:
REDCap;
clinical research;
database;
electronic data capture;
total knee arthroplasty
- From:
Fudan University Journal of Medical Sciences
2025;52(1):119-127
- CountryChina
- Language:Chinese
-
Abstract:
Objective To introduce how to import and analyze data using the Research Electronic Data Capture(REDCap)system,taking a multi-center randomized controlled clinical research of total knee arthroplasty as an example.Methods Various tools within the REDCap system,including data import tools,data export functions,reports and statistics,project dashboards,and coding manuals,were used to systematically process and analyze the multi-center randomized controlled clinical trial data for total knee arthroplasty.Initially,electronically collected clinical data were adjusted and standardized,then uploaded in bulk to the system using the REDCap data import tool.Subsequently,the data were organized through REDCap's data export feature,and basic descriptive statistical analysis was performed using its reporting and statistical functions to ensure data quality and completeness.Results An electronic data collection and management platform for clinical research on knee osteoarthritis wase successfully created by the REDCap system.The platform enabled real-time data collection from multiple centers,and ensured data accuracy and consistency through built-in data management and quality control mechanisms.With the statistical analysis features of REDCap,the research team could monitor the progress of data in real time,conduct effective quality assessments,and perform dynamic analysis for further in-depth statistical evaluations.Conclusion The REDCap system can be used not only to build a new clinical research project,but also to import and analyze data that has been previously digitized of ongoing clinical researches into the system,which improved the scientificity of data management and research efficiency.
