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encounters
, wherein patient- or cohort-level features are instrumented, codifi ed,
and represented in ways that support and enable their reuse
[
1
-
4
];
In a similar manner and as part of the “Translational Science” paradigm,
basic
science research is conducted in a manner that emphasizes the analysis of the
data generated in the lab as contextualized by driving clinical problems
and
related data sets derived from the preceding facets of the model as are concerned
with instrumenting the healthcare delivery environment to support research
endeavors
[
5
-
11
];
Spanning the two preceding areas is the combined use of information technology
(IT) and Informatics theories and methods, such that
data, information, and
knowledge generation are enabled in an effi cient and harmonized manner
[
2
,
4
,
6
];
and
Finally, employing such an integrative view of basic science, clinical, and
population-level data, information, and knowledge resources,
investigative
teams are able to both discover and test high-impact hypotheses that can con-
tribute to the overall biomedical and healthcare delivery knowledge base, and
quickly deliver such knowledge in terms of standard-of-care practice guide-
lines and interventions
[
2
,
4
,
6
]
.
While the “Translational Science” approach we have described is indeed diffi cult
to achieve given current technical, cultural, and policy-based constraints, the ability
to overcome such barriers opens a pathway towards a number of promising benefi ts,
including both:
The ability to
break-down conventional barriers
between critical components of
the research process, such that the “hand-off” of data, information, and knowl-
edge between such activities becomes timely and effi cient, and perhaps more
importantly, an expected and valued aspect of such efforts
;
and
The facilitation of
rapid cycling and recycling of data, information, and knowl-
edge
between complementary scientifi c disciplines, thus creating a systematic
whole that is greater than the sum of its constituent parts
;
Ideally, the combination of these benefi ts can lead to the timelier, resource- effi -
cient, and impactful delivery of scientifi c evidence at the point-of-care, thus improv-
ing the health of patients and populations in any number of critical areas from
disease prevention and control to the diagnosis and treatment of complex and here-
tofore unaddressed pathophysiological states.
1.2.2
Systems Thinking in Biomedicine
In a manner analogous to the shift towards a translational science paradigm as previ-
ously introduced, there is also a shift occurring relative to the fundamental thought
processes used to conceptualize and execute both research and care in the biomedi-
cal and health sciences domains. Traditional models of thinking, tracing their origins
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