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DOI: 10.1055/s-0039-1677916
Personalized Medicine Implementation with Non-traditional Data Sources: A Conceptual Framework and Survey of the Literature
Publikationsverlauf
Publikationsdatum:
16. August 2019 (online)
![](https://www.thieme-connect.de/media/10.1055-s-00034612/201901/lookinside/thumbnails/10-1055-s-0039-1677916_taylor-1.jpg)
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.
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