Basic↦Data Management↦Data Management in Studies↦Aim
What is it? Why is it important?
In studies, the aim of Data Management (DM) is to support researchers in the collection and management of their study data.
DM ensures that study data is handled in compliance with the law (e.g. Swiss law, Data Protection Act), ICH GCP, Ethical (EC), and applicable regulatory requirements (e.g. Swissmedic, international).
By selecting an appropriate Clinical Data Management System (CDMS) to manage study data, DM contributes to the generation of high-quality data needed for the statistical analyses, publications and data sharing.
High quality data provide confidence in study results, which are an important basis for further research and the ongoing advancement in science (e.g. development of medicinal products, treatment procedures algorithms).
In many ways, DM sets the framework to ensure these aims are met. In this context, the implementation of defined quality procedures are especially important (e.g. quality assurance, quality control).
What do I need to do?
As a SP-INV familiarize yourself with DM tasks involved in the planning and set-up of a study database.
Typical tasks include:
- To add a section in the study budget for DM tasks
- To select a Clinical Data management System (e.g. CDMS) that complies with the law (e.g. Swiss law) and ICH GCP (e.g. infrastructure, database validation, audit-trail, access protected)
- To perform and validate the installation of a CDMS, or use a CDMS already installed and maintained by your institution
- To perform and validate software updates as they become available
- To write applicable SOPs and WIs for the set-up, data collection, export, and closure of a study database
- To define (as applicable) a Data Management Plan (DMP) for the study (e.g. outlines the life cycle of study data and describes how data is generated, collected, documented, shared and preserved)
- To collaborate with the Site-INV on the configuration of a study electronic Case Report Form (eCRF) (e.g. study variables, visit plan, data quality checks, functions to enable/disable randomisation)
- To close and archive the study database at study completion
- To export data for statistical analysis
Where can I get help?
Your local CTU↧ can support you with experienced staff regarding this topic
Basel, Departement Klinische Forschung, CTU, dkf.unibas.ch
Lugano, Clinical Trials Unit, CTU-EOC, www.ctueoc.ch
Bern, Clinical Trials Unit, CTU, www.ctu.unibe.ch
Geneva, Clinical Research Center, CRC, crc.hug.ch
Lausanne, Clinical Research Center, CRC, www.chuv.ch
St. Gallen, Clinical Trials Unit, CTU, www.kssg.ch
Zürich, Clinical Trials Center, CTC, www.usz.ch
References
ICH GCP E6(R2) – see in particular guideline
- 5.5 Trial management, data handling, and record-keeping