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education, research, and clinical care organizations fund, staff, and operate their
enterprises. Such factors are called into sharp relief by simultaneous pressures
exerted at the economic, governmental, and policy levels. When taken as a whole,
this environment and the changes it has experienced can be defi ned by a number of
critical challenges and opportunities, as enumerated below:
How can we transform the delivery of both clinical care and wellness promotion,
such that the quality, safety, and effi cacy of such efforts are improved, while
simultaneously decreasing the costs and complexity of doing so?
How do we accelerate the speed with which discoveries in the basic sciences are
translated into actionable and widely utilized diagnostic and/or therapeutic
strategies?
How can we drive the process of discovery as a natural outgrowth of patient care
by leveraging data that is collected through clinical interactions?
How will a biomedical workforce, with appropriate levels and types of training
and related career trajectories, both evolve and be sustained in a manner aligned
with such rapidly changing needs?
A shift in emphasis and thinking, relative to the ways in which the broad health-
care community addresses the collection, storage, management, analysis, and dis-
semination of data, information, and knowledge, will be required to address these
questions. Such a shift will be impossible to achieve without signifi cant cultural
change. It must de-emphasize application or domain-specifi c silos in favor of inte-
grative and systems-level translation between and among disciplines and driving
biological or clinical problems. For readers not familiar with the premise of such
systems-level approached, we will defi ne the concept more fully in Sect.
2.2
.
When taken as a whole, we have labeled this paradigm as “Translational
Informatics” or “TI”, and will argue that the defi nition and application of TI prin-
ciples is essential to the realization of a knowledge-driven healthcare enterprise
capable of addressing the aforementioned challenges and opportunities. Building
upon this overall motivation, and in order to contextualize the remainder of this
topic, in this chapter, we will:
Describe in greater detail the motivating factors for the formulation of the TI
vision, including the promise of translation, an emergent shift in scientifi c inves-
tigation away from reductionism and towards systems thinking, and the evolving
central dogma of the discipline of Biomedical Informatics
;
Introduce exemplary trends that serve to illustrate the importance of the preced-
ing factors, including an increasing emphasis on the creation of learning health-
care systems, the evolution of precision medicine, and the dawning era of “big
data”
;
Propose a set of next steps related to the advancement of critical strategic
research foci, implementation science best practice, and workforce development,
in response to such motivating trends
;
and
Introduce a hypothetical environment in which all of the preceding factors are
present, spanning a spectrum from patients to policy makers. This environment
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