Personalized Medicine Implementation with Non-traditional Data Sources: A Conceptual Framework and Survey of the Literature.

Personalized Medicine Implementation with Non-traditional Data Sources: A Conceptual Framework and Survey of the Literature.

Publication date: Aug 01, 2019

With the explosive growth in availability of health data captured using non-traditional sources, the goal for this work was to evaluate the current biomedical literature on theory- driven studies investigating approaches that leverage non- traditional data in personalized medicine applications.

We conducted a literature assessment guided by the personalized medicine unsolicited health information (pUHl) conceptual framework incorporating diffusion of innovations and task-technology fit theories.

The assessment provided an oveiview of the current literature and highlighted areas for future research. In particular, there is a need for: more research on the relationship between attributes of innovation and of societal structure on adoption; new study designs to enable flexible communication channels; more work to create and study approaches in healthcare settings; and more theory-driven studies with data-driven interventions.

This work introduces to an informatics audience an elaboration on personalized medicine implementation with non-traditional data sources by blending it with the pUHl conceptual framework to help explain adoption. We highlight areas to pursue future theory-driven research on personalized medicine applications that leverage non-traditional data sources.

Open Access PDF

Taylor, C.O. and Tarczy-Hornoch, P. Personalized Medicine Implementation with Non-traditional Data Sources: A Conceptual Framework and Survey of the Literature. 05205. 2019 Yearb Med Inform (28):1.

Concepts Keywords
Biomedical Conceptual
Diffusion Healthcare settings
Healthcare Communication
Informatics

Semantics

Type Source Name
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drug DRUGBANK Trestolone
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disease MESH tics
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disease MESH breast cancer
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