Summary
Objectives: 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.
Methods: 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.
Results: 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.
Conclusion: 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.
Keywords
Personalized medicine - implementation science - dissemination research - diffusion
of innovation - review literature as topic
