Research data management
Research data should be organized according the FAIR principles, making data Findable, Accessible, Interoperable and Reusable and, where applicable, additional requirements (e.g. for WMO, GCP and GDPR). It should be well documented, transparent and traceable. Legislation and growing emphasis on issues such as reproducibility, integrity of research and the requirement of subsidy providers for sharing data require specific working procedures, facilities and support.
All Amsterdam UMC (clinical and non-clinical) researchers can get support on their study preparation, including writing a data management plan, their data collection (including appropriate tooling), preparing data for statistical analysis, and sharing and publication of research data.
The Research data management department’s expertise is translated into policies, education, consultation and executive support, and we are the entrance point for requests for Epic data and setting up an additional data collection for research in Epic.
The Standard Operating Procedure (SOP) for Research Data Management describes the requirements for handling research data at Amsterdam UMC. The way you organize this must be described in a data management plan and reviewed by an RDM consultant. The SOP provides general requirements, explanation and links to supporting documents, templates, tooling, support and websites. The SOP and DMP template have been approved by various grant providers
The following courses are offered:
RDM for PhD students
- At location AMC via the Graduate School, three times a year
- At location VUmc in collaboration with the UBVU, six times a year
RDM (with the focus on Clinical Data Management) within the center specific BROK eCRF design in OpenClinica (Amstrdam UMC location AMC)
Castor EDC courses on eCRF design (both for beginners and advanced)
- RDM course Doctoral School
- Courses by RDM(internal link)
- RDM courses VUmc (internal link)
Consultation and support
The RDM helpdesk can help researchers with questions regarding choosing the right software applications and tools for data collection and data storage, the design of / within software applications for data collection, testing study databases in Castor EDC, handling data (sets), data processing, data extraction, data documentation, data archiving and publishing, and support in writing a data management plan.
In some cases, activities such as building a study database or creating a custom made solution can be outsourced to the RDM Department.
Epic and research
The Electronic Health Record (EPD) Epic contains a considerable amount of data that may be relevant for scientific research. Epic data are made available for research
s (RDP) of Amsterdam UMC.
Tools such as CTcue Patientfinder and SlicerDicer are available for selecting patients from Epic based on inclusion and exclusion criteria for both retrospective and prospective research.
With the patientfinder module of C
tTcue it is also possible to search both structured and unstructured data and present them in a pseudonimized manner.
Epic also offers
- Epic and research (internal link)
Extraction of care data using RDP
The RDP is a platform that pulls in clusters of data from Epic and several other sources (laboratory, biobank, imaging etc.) and can deliver integrated data sets to researchers. These data clusters are defined
The RDP is secure, auditable and compliant with rules and (privacy) regulations. The RDP is continuously being expanded by linking additional data and data sources. Using the links below, researchers can browse the RDP catalogues of both Amsterdam UMC locations to identify relevant datasets and find procedures for data collection using the RDP.
- RDB DCM catalogus (internal link)
- RDP intranet pages of the department of Business Intelligence (internal link)
- Request care data for research (internal link)