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Quality of real-world data

As the new front of Digital Biomarkers quickly expands, Real-World Data (RWD) is the largest domain of application, be it for data collection, hypothesis testing and/or generation of RWE.

Several parallel efforts already define RWD/RWE, however an overall systematic view of the domain and data quality assessments for clinical use are missing. We use an indexing workflow to address the systematic organization of RWD by focusing on identifiers for describing the quality, standardization, regulation, and privacy of RWD datasets. These variables are Quality Identifiers (QI) and provide a first quality assessment and validation for the use of RWD in a clinical setting.

In collaboration with the School of Business, we developed the RWD Cockpit, a dashboard to view and assess the quality of RWD. The RWD Cockpit is a practical database which allows the management of QIs and their possible scores. By using this QI list of quality metrics, we index available RWD datasets and provide an overall Quality Score (QS) for the dataset. The system equips each RWD dataset with a unique ID and a deep-link allowing to share quick details as well as off-the-shelf database features such as advanced searching and filtering. The RWD Cockpit is a complete tool to assess quality of RWD for clinical use.

Institute for Medical Engineering and Medical Informatics

FHNW University of Applied Sciences and Arts Northwestern Switzerland School of Life Sciences, Institute for Medical Engineering and Medical Informatics Hofackerstrasse 30 CH - 4132 Muttenz
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