Sharing of Data from Clinical Research Projects

Abstract

Objectives: Data sharing has become a requirement of many funding bodies and is becoming a scientific standard in many disciplines. In clinical research, however, data sharing can conflict with the obligation to protect privacy of study participants and especially of patients. General recommendations on data sharing exist also for clinical research, but so far they lack practical and Swiss-specific aspects. The objective of this document is to provide practical recommendations for all relevant aspects of data sharing in agreement with legislation in Switzerland. Methods: This document was written by members of the SCTO’s CTU Network, a network of academic clinical trial units. The process did not follow a formalized Delphi process. After an internal consensus round, this report was published as pre-print for external review. This is the second version with feedback from these external reviews incorporated. We publish this document as a text in progress, as we expect relevant changes in related fields such as the development of further dedicated medical repositories or methodological advances in de-identification techniques or changes to the legal situation. Results: We developed principles and practical recommendations with respect to informed consent, data management plan, de-identification, data structure and format, coding of variables, metadata and documentation, version control, selection of repository, requesting and use of data. We also provide a summary of legal aspects relevant for the Swiss context. Conclusions: The intention to share data has an impact not only after a clinical trial or an observational study is completed, but also during the planning period, the conduct and the analysis phase. Clinical researchers need to be aware at the beginning of a study on how to inform patients and at least the amount of work related to preparing data, metadata, and any further documentation for being shared. This report provides aspects to be considered, suggests decision criteria, and provides examples and checklists, in order to support data sharing in practice.