The Learning-Adapting-Leveling model: from theory to hypothesis of steps for implementation of basic genome-based evidence in personalized medicine. (September 2013)

• Record Type: Journal Article
• Authors: Lal, Jonathan A; Vaidya, Anil; Gutiérrez-Ibarluzea, Iñaki; Dauben, Hans-Peter; Brand, Angela
• Is Part Of: Personalized medicine. Volume 10:Number 7(Year 2013)
• Page Start: 683
• Page End: 701
• Publication Date: 2013-09
• Subjects: health impact assessment -- health needs assessment -- health technology assessment -- LAL model -- life cycle -- personalized healthcare -- personalized medicine -- public health genomics -- technology transfer -- translational research; Pharmacogenomics -- Periodicals; Pharmacogenetics -- Periodicals; 615.19
• DOI: 10.2217/pme.13.72
• Languages: English
• ISSNs: 1741-0541

Abstract

We see a backlog in the effective and efficient integration of personalized medicine applications such as genome-based information and technologies into healthcare systems. This article aims to expand on the steps of a published innovative model, which addresses the bottleneck of real-time integration into healthcare. We present a deconstruction of the Learning-Adapting-Leveling model to simplify the steps. We found out that throughout the technology transfer pipeline, contacts, assessments and adaptations/feedback loops are made with health needs assessment, health technology assessment and health impact assessment professionals in the same order by the academic–industrial complex, resulting in early-on involvement of all stakeholders. We conclude that the model steps can be used to resolve the bottleneck of implementation of personalized medicine application into healthcare systems.