Summary
Introduction: In the context of an increasing number of multi-centric studies providing data from
different sites and sources the necessity for central data management (CDM) becomes
undeniable. This is exacerbated by a multiplicity of featured data types, formats
and interfaces. In relation to methodological medical research the definition of central
data management needs to be broadened beyond the simple storage and archiving of research
data.
Objectives: This paper highlights typical requirements of CDM for cohort studies and registries
and illustrates how orientation for CDM can be provided by addressing selected data
management challenges.
Methods: Therefore in the first part of this paper a short review summarises technical, organisational
and legal challenges for CDM in cohort studies and registries. A deduced set of typical
requirements of CDM in epidemiological research follows.
Results: In the second part the MOSAIC project is introduced (a modular systematic approach
to implement CDM). The modular nature of MOSAIC contributes to manage both technical
and organisational challenges efficiently by providing practical tools. A short presentation
of a first set of tools, aiming for selected CDM requirements in cohort studies and
registries, comprises a template for comprehensive documentation of data protection
measures, an interactive reference portal for gaining insights and sharing experiences,
supplemented by modular software tools for generation and management of generic pseudonyms,
for participant management and for sophisticated consent management.
Conclusions: Altogether, work within MOSAIC addresses existing challenges in epidemiological research
in the context of CDM and facilitates the standardized collection of data with pre-programmed
modules and provided document templates. The necessary effort for in-house programming
is reduced, which accelerates the start of data collection.
Keywords
Medical data management - data privacy protection - informed consent - pseudonyms
- record linkage