Simplifying Multimodal Clinical Research Data Management: Introducing an Integrated and User-Friendly Database Concept

Background Clinical research, particularly in scientific data, grapples with the efficient management of multimodal and longitudinal clinical data. Especially in neuroscience, the volume of heterogeneous longitudinal data challenges researchers. While current research data management (RDM) systems offer rich functionality, they suffer from architectural complexity that makes them difficult to install and maintain and require extensive user training. Objectives The focus is the development and presentation of a data management approach specifically tailored for clinical researchers involved in active patient care, especially in the neuroscientific environment of German university hospitals. Our design considers the implementation of FAIR (Findable, Accessible, Interoperable, and Reusable) principles and the secure handling of sensitive data in compliance with the General Data Protection Regulation (GDPR). Methods We introduce a streamlined database concept, featuring an intuitive graphical interface built on HTML5/CSS technology. The system can be effortlessly deployed within local networks, i.e., in Microsoft Windows 10 environments. Our design incorporates FAIR principles for effective data management. Moreover, we've streamlined data interchange through established standards like HL7 CDA. To ensure data integrity, we've integrated real-time validation mechanisms that cover data type, plausibility, and Clinical Quality Language (CQL) logic during data import and entry. Results We have developed and evaluated our concept with clinicians using a sample dataset of subjects who visited our memory clinic over a three-year period and collected several multimodal clinical parameters. A notable advantage is the unified data matrix, which simplifies data aggregation, anonymization, and export. This streamlines data exchange and enhances database integration with platforms like KNIME. Conclusion Our approach offers a significant advancement for capturing and managing clinical research data, specifically tailored for small-scale initiatives operating within limited IT infrastructures. It's designed for immediate, hassle-free deployment by clinicians and researchers. The Database template and pre-compiled versions of the user interface are available at: https://github.com/stebro01/research_database_sqlite_i2b2.git.

Angaben zum Objekt

• Standort: Deutsche Nationalbibliothek Frankfurt am Main
• Umfang: Online-Ressource
• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Simplifying Multimodal Clinical Research Data Management: Introducing an Integrated and User-Friendly Database Concept ; day:01 ; month:02 ; year:2024 ; Applied clinical informatics ; (01.02.2024)

Beteiligte, Orts- und Zeitangaben

• Beteiligte Personen und Organisationen: Schweinar, Anna ; Wagner, Franziska ; Klingner, Carsten ; Festag, Sven ; Spreckelsen, Cord ; Brodoehl, Stefan

Weitere Informationen

• DOI: 10.1055/a-2259-0008
• URN: urn:nbn:de:101:1-2024032112361779401706
• Rechteinformation: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Letzte Aktualisierung: 30.01.2025, 13:53 MEZ