Multidisciplinary Open COVID Dataset (MOVE-IT)
Post-COVID syndrome (PCS) is a complex clinical condition that requires collaboration across different disciplines between experts, researchers and those affected. To fully exploit the potential of PCS data collections, the integration and free availability of different datasets are essential. Through innovative methods of data analysis and data exchange, the full range of hidden information can be utilised for research.
Project objective
The project aims to process the extensive PCS databases from the DEFEAT-Corona project at Hannover Medical School and the University Medical Centre (UMG), comprising over 8,000 patients, into a compatible, comprehensive open-source dataset that is aligned with the GECCO and WHO Core Datasets. By weighting the data using health insurance records, the aim is to achieve approximate representativeness for PCS patients receiving outpatient care in northern Germany. In addition to PCS patients, the dataset also includes comparison cohorts and COVID-19 patients from all pandemic waves and will complement the existing NAPKON cohort.
Basic data
Duration: 24 months
Funding body: Federal Ministry of Education and Research (BMBF)
Project partners
Hannover Medical School (MHH), Department of Rheumatology and Immunology (Coordinator)
University Medical Centre Göttingen (UMG), Institute of General Practice
Peter L. Reichertz Institute for Medical Informatics (PLRI) at MHH
Ostfalia University of Applied Sciences, Department of Computer Science
Project team
