Future Medicine - Personalized Medicine - 8(2):191 - Summary

Special Report
March 2011, Vol. 8, No. 2, Pages 191-205 , DOI 10.2217/pme.11.5
(doi:10.2217/pme.11.5)

The Genome-based Knowledge Management in Cycles model: a complex adaptive systems framework for implementation of genomic applications

Nedal Arar​‌†, Sara J Knight​‌1, Stephen M Modell​‌2 & Amalia M Issa​‌3; for the GAPPNet™ Inaugural Knowledge Synthesis & Dissemination Working Group*


† Author for correspondence
*Members of the Inaugural GAPPNet™ Knowledge Synthesis & Dissemination Working Group are: Nedal Arar, Gregory J Downing, Karen Edwards, Amalia M Issa (Facilitator) Katrina AB Goddard, Marta Gwinn, Michael J Hall, Bill Knaus (Facilitator), Sara Knight, Ira Lubin, Stephen M Modell (Group Note taker), Kathryn Phillips, Caroline F Thorn, Thomas Trikalinos & Stephanie Van Bebber

The main mission of the Genomic Applications in Practice and Prevention Network™ is to advance collaborative efforts involving partners from across the public health sector to realize the promise of genomics in healthcare and disease prevention. We introduce a new framework that supports the Genomic Applications in Practice and Prevention Network mission and leverages the characteristics of the complex adaptive systems approach. We call this framework the Genome-based Knowledge Management in Cycles model (G-KNOMIC). G-KNOMIC proposes that the collaborative work of multidisciplinary teams utilizing genome-based applications will enhance translating evidence-based genomic findings by creating ongoing knowledge management cycles. Each cycle consists of knowledge synthesis, knowledge evaluation, knowledge implementation and knowledge utilization. Our framework acknowledges that all the elements in the knowledge translation process are interconnected and continuously changing. It also recognizes the importance of feedback loops, and the ability of teams to self-organize within a dynamic system. We demonstrate how this framework can be used to improve the adoption of genomic technologies into practice using two case studies of genomic uptake.

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Future Medicine - Personalized Medicine - 8(2):191 - Summary