A Web-Based Questionnaire Builder to Facilitate form Management for the Electronic Data Capture with REDCap.

REDCap, a popular platform for building surveys for electronic data capture, offers two methods for creating questionnaires: an interactive web interface to modify single questions and an upload method to import entire questionnaires. Both methods present limitations in terms of usability and time needed for different tasks. We propose a browser-based web application to design and manage REDCap questionnaires using a What-You-See-Is-What-You-Get approach. The application provides a user-friendly interface for a comprehensive overview of all imported questionnaires, and three distinct views cater to different aspects of the questionnaire design process. The questionnaires can be imported and exported through the REDCap CSV format and thus integrate seamlessly into its environment. REDCapQB represents a significant advancement in questionnaire design and management, offering researchers a powerful and user-friendly tool for electronic data capture in translational research studies within the REDCap ecosystem.

Web-based Prototype for Graphical Exploration of FHIR® Questionnaire Responses.

The evaluation of clinical questionnaires is an important part of gaining knowledge in empirical research. The electronically captured responses are encoded in a standard format such as HL7 FHIR® that facilitates data exchange and systems interoperability. However, this also complicates access of the information to explore and interpret the results without appropriate tools. In this work, we present the design of a web-based graphical exploration tool for categorical questionnaire response data that can interact with FHIR-conformant HTTP endpoints. The web app enables non-technical users with simplified, direct visual access to highly structured FHIR questionnaire response data and preserves the applicability in arbitrary data exploration tasks. We describe the abstract feature design with the derived technical implementation to allow a universal, user-configurable data subselection mechanism to generate conditional one- and two-data-dimensional charts. The applicability of our developed prototype is demonstrated on synthetic FHIR data with the source code available at https://github.com/frankkramer-lab/FHIR-QR-Explorer.