Information Technology Reference
In-Depth Information
Clinical and/or
Population
Encounters
Data
Generation
Integration
IT + Biomedical
Informatics
Hypothesis
Discovery and
Testing
Research
Knowledge
Generation
Fig. 1.2 Overview of the “Translational Science” paradigm, in which an integrative and cyclical
approach to knowledge discovery, research, and evidence generation seeks to accelerate the trans-
lation of new scientifi c discoveries into clinical and/or population-based healthcare practice
approaches to complex problems that often span traditional organizational boundar-
ies. Such a change in thinking and research practice has been described in many
venues as “Translational Science”, and has been broadly defi ned (and redefi ned) in
a variety of reports and topics [ 1 - 3 ]. Another critical dimension of this shift in
thinking has been towards a model in which research and clinical care are tightly
and iteratively connected, whereby data generation and evidence generation span-
ning these two complementary areas are synergistic, integrated, and highly effi cient.
Ultimately, such an approach to knowledge discovery, research, and evidence-
generation are intended to overcome what has been described as a highly ineffi cient
or even dysfunctional paradigm in which new basic science discoveries can take up
to two decades to be translated into broadly utilized clinical care or population
health practices. An illustration of the integrative and cyclical nature of the
“Translational Science” paradigm is provide in Fig. 1.2 and described below:
￿
In the “Translational Science” paradigm, a variety of data, information, and
knowledge resources are generated via either clinical or population-level
 
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