Electronic data capture in resource-limited settings using the lightweight clinical data acquisition and recording...

Area of Science:

• Clinical Research Informatics
• Health Data Management
• Software Engineering in Medicine

Background:

• Existing electronic data capture (EDC) software for clinical research is often expensive or feature-limited.
• There is a need for accessible, adaptable, and scalable EDC solutions to facilitate research.
• Current tools may not adequately support simple and lightweight data acquisition.

Purpose of the Study:

• To develop a novel, open-source EDC software system with a mobile client for clinical data acquisition.
• To create a user-friendly, modifiable, and scalable solution that simplifies clinical research data management.
• To provide an alternative to costly and feature-restricted EDC software.

Main Methods:

• Developed a modular EDC software and mobile client using the R programming language.
• Implemented established data standards, a metadata-driven interface, and database structure.
• Designed for local or cloud installation with minimal IT expertise, including a progressive web app.

Main Results:

• Successfully demonstrated the software's capability in four clinical studies involving over 1600 participants.
• The system managed data for up to 679 variables per participant.
• A straightforward server installation approach was detailed, highlighting further use-cases.

Conclusions:

• The developed open-source EDC software is versatile, easily deployable, highly modifiable, and scalable for clinical studies.
• Its R-based, open-source nature promotes accessibility and community-driven development.
• The system effectively addresses the need for a lightweight and adaptable clinical data capture solution.