The IeDEA harmonist data toolkit: A data quality and data sharing solution for a global HIV research consortium

Area of Science:

• Health Informatics
• Data Science
• Epidemiology

Background:

• International observational HIV research networks generate vast amounts of complex data.
• Ensuring data quality and consistency across diverse datasets is crucial for reliable research findings.
• Existing data management tools may not adequately address the specific needs of global research collaborations.

Purpose of the Study:

• To design, implement, and evaluate a novel data toolkit for harmonizing and improving data quality in an international HIV research network.
• To develop a user-friendly, web-based application that streamlines data quality checking and report generation.
• To assess the impact of the toolkit on data accuracy and research efficiency.

Main Methods:

• Developed the IeDEA Harmonist Data Toolkit, a web-based application using R, R/Shiny, and RMarkdown.
• Integrated the toolkit with the REDCap platform for data model definition and user authentication.
• Implemented automated data quality checks, conformance checks against a common data model, and dynamic report generation.
• Incorporated stakeholder feedback throughout the design and implementation process.

Main Results:

• The toolkit successfully harmonizes data, performs quality checks, and generates dynamic reports.
• User surveys and usage metrics indicate significant time savings for data managers.
• A mean reduction of 61% in data error records was observed after toolkit implementation.
• The application demonstrated ease of adoption and positive impact on data quality.

Conclusions:

• The IeDEA Harmonist Data Toolkit enhances data quality and research efficiency in international HIV studies.
• Stakeholder involvement is critical for the successful adoption of data management tools.
• The generalized design of the toolkit allows for its adaptation to other research networks, promoting broader data quality improvements.