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

Casey Overby Taylor, Peter Tarczy-Hornoch

Research output: Contribution to journalReview articlepeer-review

Abstract

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.

Original languageEnglish (US)
Pages (from-to)181-189
Number of pages9
JournalYearbook of medical informatics
Volume28
Issue number1
DOIs
StatePublished - Aug 1 2019

ASJC Scopus subject areas

  • Medicine(all)

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