An Introduction to Translational Informatics and the Future of Knowledge-Driven Healthcare - Translational Informatics: Realizing the Promise of Knowledge-Driven Healthcare - page 14

…the study of methods to promote the integration of research fi ndings and evidence into
healthcare policy and practice… (Source: National Library of Medicine)

Given such a defi nition, it is clear that implementation science theory and
practice will be central to the ability to understand and optimize the pathways by
which knowledge fl ows among the myriad disciplines and settings involved in
the broader TI ecosystem. The use if implementation science theories and meth-
ods can and will ultimately assist in the analysis of key socio-cultural and envi-
ronmental factors that may serve to infl uence or predispose the way in which the
vision of TI, and ultimately knowledge-driven healthcare, is operationalized.
However, it is also important to note that implementation science, at least in the
biomedical and healthcare domains, is an emergent and relatively “young” disci-
pline, and thus an area defi ned by a broad spectrum of open research questions.
Despite such limitations, if the lessons learned from the intersection of imple-
mentation science and other disciplines (such as the social science and public
health domains) are taken as exemplars [ 19 ], the application of these principles
lead to a deeper and richer understanding of the complex “real world” issues that
ultimately decide the fate of knowledge translational from research to practice to
widespread adoption.

1.4.3 Workforce Development

Finally, and of equal importance to the preceding areas, given the paucity of indi-
viduals with training or expertise in both basic and applied Biomedical Informatics,
particularly with relevance to the pursuit of TI, it will remain imperative for the
biomedical and healthcare communities to pursue and sustain workforce develop-
ment activities in such domains. The types of stakeholders to be engaged, and the
acuity of knowledge relative to Biomedical Informatics competencies needed by
such trainees, should be used to appropriately inform such workforce development
programs. At a high level, such stakeholders and training acuity levels can be strati-
fi ed into three major categories:

￿ Acculturation : At this level of training, individuals should become familiar with

high level defi nitions and methodological frameworks such that they are able to
prioritize and direct both basic and applied research, development, and systems
evaluation activities. Examples of stakeholders at this level of acuity include
C-level executives, project managers, and perhaps most importantly, clinicians
and other healthcare providers.

￿ Applied Knowledge : At this level of training, individuals should understand

how to select and apply theories and frameworks to satisfy use-case specifi c
information needs. Examples of stakeholders at this level of acuity include tech-
nical architects, software engineers, and technology deployment/support staff.

￿ Foundational Knowledge : At this level of training, individuals should have a

thorough theoretical and methodological grounding, as well as expertise in