The tasks of collecting and managing data for clinical and translational research pose
significant challenges for researchers who lack access to data management expertise,
methods, and tools. These tasks, known collectively as clinical research informatics,1
include management of information acquired directly from clinical trials as well as
secondary use of data gathered in the context of patient care for research purposes. The
development of a robust research infrastructure that includes sophisticated approaches to data management and informatics is vital to modern, data-intensive clinical and translational research. But despite such infrastructure having been identified as a key priority,2 significant gaps remain and the conceptual frameworks and nomenclature of informatics and health information technology (HIT) are not agreed upon or well understood, either within or outside of academic health and science systems.3 One key effect of this lack of common models and terminology has been to make the articulation of informatics needs and
appropriate direction of resources for informatics support a continual challenge for clinical
and translational research.
Levels of informatics support for the diverse array of investigator-initiated research vary
significantly among institutions.4 Researchers working in well-funded departments are more
likely to have access to a clinical research infrastructure that includes statistical assistance,
data management support, and a secure, compliant, and robust application suite than are
investigators with limited funding or who rely upon internal departmental funds. In addition, lack of communication concerning available resources can also lead to under-utilization of those resources.5
In this article, we present a model for providing flexible, cost-efficient institutional support for clinical and translational research data management and informatics, the Research Management Team (RMT), and describe our initial experiences with this model.