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Evidence
Generation
Advances
in Human
Health
Improved
Translation
Systems
Thinking
Learning
Healthcare
System(s)
Enabled By Biomedical Informatics Theories and Methods
Fig. 1.1
Foundational argument for the vision of TI, wherein improved translational capabilities,
combined with systems thinking, and enabled by Biomedical Informatics theories and methods,
can facilitate critical advances in human health as provided by knowledge-driven paradigms such
as rapid-cycle evidence-generation predicated on the existence of learning healthcare system(s)
will be used throughout the remainder of topic to contextualize major areas of
innovation that contribute to attainment of a TI model and the vision for
knowledge- driven healthcare.
When taken as a whole, we believe that the foundational argument for the vision
of TI is that improved translation and systems thinking, enabled by Biomedical
Informatics theories and methods, will yield a platform and “way forward” towards
critical advances in human health made possible by fully knowledge-driven work-
fl ows and practices (Fig.
1.1
).
1.2
Motivation for a Translational Informatics Vision
In the sections that follow, we will review three critical and motivating factors
underlying our vision for Translational Informatics (TI), namely: (1) the promise of
new models for clinical and translational research (collectively referred to as trans-
lational science and described in more detail in Sect.
2.1
), particularly as applied to
biomedicine; (2) an emergent trend away from reductionism and towards systems
thinking; and (3) the formalization of a central dogma for the broad domain of
Biomedical Informatics.
1.2.1
The Promise of Translational Science
As was introduced at the outset of this chapter, increasingly, the biomedical and
healthcare communities have experienced a shift away from narrowly focused and
individualized research programs towards a model that emphasizes team-based
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