CEOsys – An ecosystem for COVID-19 evidence in Germany: challenges and lessons learned as a guide for future networks

Article type
Authors
Kunzler AM1, Iannizzi C2, Moerer O3, Nothacker M4, Rehfuess E5, Spies C6, Skoetz N2, Meerpohl JJ7, and the CEOsys Consortium -8
1Institute for Evidence in Medicine, Medical Center & Faculty of Medicine, University of Freiburg, Freiburg
2Evidence-based Medicine, Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Duesseldorf, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne
3Department of Anesthesiology, University Medical Center of the Georg August University Göttingen, Göttingen
4Institute for Medical Knowledge Management (AWMF-IMWi), AWMF office Berlin
5Chair of Public Health and Health Services Research, Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), LMU Munich, Munich, Germany AND Pettenkofer School of Public Health, Munich
6Department of Anesthesiology and Intensive Care Medicine (CCM, CVK), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt Universität zu Berlin and Berlin Institute of Health, Berlin
7Institute for Evidence in Medicine, Medical Center & Faculty of Medicine, University of Freiburg, Freiburg, Germany AND Cochrane Germany, Freiburg
8CEOsys Consortium (www.covid-evidenz.de)
Abstract
Background: The COVID-19 pandemic presented a major disruption worldwide. Given the extensive, rapidly evolving evidence, high-quality evidence syntheses that provide context-sensitive and up-to-date data were urgently needed as a basis for evidence-informed clinical and public health decision-making. CEOsys (‘COVID-19 evidence ecosystem’) was established as a national German network for living systematic reviews (LSRs) and living guidelines.

Objectives: To describe the infrastructure, processes and impact of CEOsys and to discuss challenges faced and lessons learned when organizing and maintaining the network, which may provide guidance for future networks in view of pandemics and health-related crises.

Methods: We present an experience report from representatives of the former CEOsys network (09/2020-12/2021; full list of collaborators: www.covid-evidenz.de), a project within the German Network of University Medicine (NUM). After describing its development, we outline CEOsys work processes and present our outputs before highlighting challenges encountered, adaptations made and lessons learned.

Results: CEOsys gathered 18 university hospitals and 8 (non-)university partners. Processes included i.a. prioritization, conducting LSRs, supporting evidence-based guidelines and knowledge translation, backed by setting up a technical infrastructure and capacity-building. We published 12 COVID-19-related Cochrane reviews, supported three living guidelines (inpatient/outpatient treatment, school-based infection prevention) and developed 10 methodological approaches and 10 dissemination formats. Challenges included CEOsys’ late initiation, prioritization, the continuously evolving knowledge on COVID-19 and revision of outcomes for LSRs or establishing a ‘living’ technical infrastructure. Based on lessons learned, the cooperation between clinicians and methodologists within CEOsys and the network’s international collaborative partners (e.g., Cochrane International) represented major advantages. Mediated by the Institute for Medical Knowledge Management, CEOsys greatly benefitted from collaborations with guideline groups. Future networks should, for example, involve key stakeholders early on, aim for (inter-)national collaborations, balance traditional publishing of results and living documents and evaluate their impact on decision-makers and the public.

Conclusions: CEOsys achieved rapid, high-quality and up-to-date evidence syntheses, collaboratively produced across multiple sites and on a broad range of issues. Our experiences are now taken up by the follow-up project PREPARED (‘PREparedness and PAndemic REsponse in Germany’), which uses the infrastructure and processes established to design a blueprint for a more sustainable evidence ecosystem.