Rudy Scholte received an MSc degree in Health Sciences from the Radboud University Nijmegen, The Netherlands. He is trained in major data management applications, in using Epic EHR for research and is GCP certified. He has worked for a commercial and an academic CRO, and became Senior Clinical Data Manager at the Clinical Research Unit of the Academic Medical Centre, Amsterdam in 2002. Since 2006 he is the Head data management of this unit.
After managing a data management group of 15 employees for 10 years, Mr Scholte’s current work focuses on setting up organization wide data management policies, education in research data management and organizing consultation services. He is strongly involved in research IT initiatives in the nowadays called Amsterdam UMC and is the product owner of the Research Data Platform. He actively participates in several national initiatives (Data4LifeSciences, LCRDM and NFU).
Title of Session: The changing role of academic data management units
Description of Session:
Traditionally, University Medical Centres (UMCs) supported their clinical researchers data management services through centralized Clinical Trial Units (CTUs). These were production oriented units with technically skilled personnel that programmed randomization procedures, eCRFs including queries and web based questionnaires. However, with the emergence of eCRF systems such as Castor, OpenClinica and REDCap, investigators nowadays can set up their data management tooling themselves. This has led to a shift of data management activities by CTU-professionals to clinical investigators with little or no experience in data management.
This shift triggered the need to safeguard the quality of decentral developed data management tooling. Nationwide, CTUs are more and more being transformed into Research Data Management (RDM) units that provide consultation and education services. The traditional, technical database developer becomes a data management consultant. Also in our UMC this transformation is going on: we developed organization-wide SOPs, an RDM-training program and an RDM helpdesk for hands-on advice, support and auditing services. Privacy related issues can also be organized via this desk.
Another relevant trend in this context is the emergence of Electronic Health Records (EHRs). Classically, we enter all data in the eCRF; nowadays the relevant EHR data (e.g. lab results) can be extracted and combined with eCRF content, which is less error-prone and more efficient. At our RDM helpdesk, we verify the EHR-data requests on privacy and technical aspects, we obtain the data from the IT department and provide consultation on how to link the extract to the other data. Pharma can profit of this development: once the EHR is validated as an acceptable data source, care data that fall within the patients consent can efficiently be added to the research-specific data collection.
Understand the traditional and the current role of clinical data management units in academia.
Recognize the value of EHR data for clinical research.
Understand the implications of this development, both for academic initiated and for pharma research.