Scientific Concept of the National Cohort (status ... - Nationale Kohorte

A.4 integrated data management
A.4.1 Aims and requirements
143
A.4 Integrated Data Management
The general aim of the common data management infrastructure is to support the National
Cohort in all phases and parts by using professional IT. This includes the following:
� IT support of recruitment and management of participants and schedule management
at the local study centers
� Efficient, standardized data collection both with manual input and using diagnostic
devices; support of collecting, processing, storing, and managing biological samples
� Secure storage and archival of data according to data privacy protection rules and
such that availability, integrity, and confidentiality of all data are guaranteed at any time
� Quality control of decentrally and centrally collected data (standardization, reliability,
validity, completeness, and plausibility) by means of automatic quality control procedures
as well as support of manual quality checks
� Integration of data collected at the study centers into a common data set, ensuring a
high quality standard and on-demand availability and which supports efficient analysis
� Providing and controlling access to study data for use in internal and external research
projects, and reintegrating data resulting from internal and external research
projects in the central data base of the National Cohort.
Two different types of data must be distinguished: One is the personal identifying data of
the study subjects; the other is the actual study data, i.e., all medical information collected
from the subjects after they have given their consent to participate in the study. Personal
identifying data are needed only for contacting study subjects during recruitment and followup,
possibly for submitting incidental findings according to the regulations described in the
ethics concept, and for requesting secondary data from external sources. Study data are
needed for scientific analysis only.
The data for the National Cohort with its large number of recruiting study centers and other
involved institutions can only be efficiently managed by standardizing data collection and
processing. The implementation of a centralized data management infrastructure represents
an important resource for all institutions that take part in this large, long-term cohort
study. The central organization supports standardization of instruments and processes and
optimization of data quality, guarantees high availability of all data, and enables study-wide
common handling of data privacy protection regulations. The effort for data management of
individual institutions is at the same time minimized through the use of common IT solutions.
Requirements for integrated data management comprise both general requirements for
cohort studies and large-scale distributed systems and specific requirements resulting from
the large number of institutions involved in the National Cohort:
� Data quality and standardization: Data quality is essential in order for the results
obtained from scientific analysis of study data to be valid. Data quality management
can be considered with regard to content (see Sect. A.5) and from a technical perspective.
Technical components of data quality management, which must be provided
by the data management infrastructure, are:
– Consistent reference to the data collection instruments and their respective parts,
structure, presentation, and resulting values throughout all data structures and
applications
– Automatic checks for completeness, plausibility, and consistency wherever possible
A.4