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engagement driven by researchers to actively involve communities in both directing
questions for research, and providing results [ 18 ]. It has been especially applied to
populations where the levels of patient engagement in research is comparatively
low, leading to disparities in research applicability that may be related to disparities
in health and healthcare. To improve community engagement as a core compo-
nent of translational research, specifi c elements of community engagement have
been required for the national Clinical and Translational Science Awards (CTSAs)
[ 19 ]. A critical component of translational informatics is to facilitate CBPR in clini-
cal studies. An example is the WICER project mentioned in Chap. 4 . WICER is
an informatics infrastructure for comparative effectiveness research, focused on a
mostly-immigrant, Hispanic population in New York City. A core component of
WICER is the population survey, where data are collected directly from community
members. Focus groups within the community were used to refi ne the questions.
Studies using subjects from the WICER cohort have shown an increased level of
engagement that other sources, and it has substantially improved the engagement of
the community in research studies [ 20 ].
A current innovation of WICER is to provide research data back to subjects in a
way that helps them understand the information, as a health promotion tool.
Focusing on improved health understanding and cognition, researchers are investi-
gating how to represent data in a simplifi ed and non-ambiguous way, so that sub-
jects can see their health relative to other subjects in the study. This innovation may
be able to translate research engagement into tools supporting overall health
engagement, creating an innovative method of health promotion.
9.3
Implications for Stakeholders
As was introduced in Chap. 2 , a variety of stakeholders can and will benefi t from the
engagement of patients and their communities in the broad TI paradigm. Critical
examples of these benefi ts stratifi ed by stakeholder type include the following:
Evidence and Policy Generators
￿ Traditional approaches to research often focus solely upon data collected by
practitioners and/or researchers in clinical care or other closely controlled set-
tings. In contrast, signifi cant amounts of data and activity that pertain to health
and wellness occur or are generated outside of those settings. By embracing the
role of patients and their communities as part of the evidence generation
team , the benefi ts of systems - level approaches to complex healthcare prob-
lems can be achieved .
￿ In a similar manner, policies that infl uence healthcare research and delivery
are often generated based on data and evidence that does not incorporate
patient or community input and related information resources . As such,
these policies can frequently fail due to unanticipated barriers to adoption or
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