REDbox: a comprehensive semantic framework for data collection and management in tuberculosis research

Author(s)

Lima, Vinicius Costa ; Rijo, Rui Pedro Charters Lopes ; Bernardi, Filipe Andrade ; Colombo Filho, Marcio Eloi ; Barbosa-Junior, Francisco ; Pellison, Felipe Carvalho ; Galliez, Rafael Mello ; Kritski, Afranio Lineu ; Alves, Domingos

• Document type: Journal article
• Source: SCIENTIFIC REPORTS; v. 13, n. 1, p. 14-pg., 2023-05-11.

Abstract

Clinical research outcomes depend on the correct definition of the research protocol, the data collection strategy, and the data management plan. Furthermore, researchers often need to work within challenging contexts, as is the case in tuberculosis services, where human and technological resources for research may be scarce. Electronic Data Capture Systems mitigate such risks and enable a reliable environment to conduct health research and promote result dissemination and data reusability. The proposed solution is based on needs pinpointed by researchers, considering the need for an accommodating solution to conduct research in low-resource environments. The REDbox framework was developed to facilitate data collection, management, sharing, and availability in tuberculosis research and improve the user experience through user-friendly, web-based tools. REDbox combines elements of the REDCap and KoBoToolbox electronic data capture systems and semantics to deliver new valuable tools that meet the needs of tuberculosis researchers in Brazil. The framework was implemented in five cross-institutional, nationwide projects to evaluate the users' perceptions of the system's usefulness and the information and user experience. Seventeen responses (representing 40% of active users) to an anonymous survey distributed to active users indicated that REDbox was perceived to be helpful for the particular audience of researchers and health professionals. The relevance of this article lies in the innovative approach to supporting tuberculosis research by combining existing technologies and tailoring supporting features. (AU)

• FAPESP's process: 20/01975-9 - Digital health for the End TB strategy: from linked data integration to a better evidence-based decision making
• Grantee: Domingos Alves
• Support Opportunities: Research Grants - eScience and Data Science Program - Regular Program Grants