The overarching framework of translation and integration into healthcare: A case for the LAL model

Background: Recently, there has been a substantial increase in relevant genome-based technologies into market. Compared with its utilization in healthcare systems, we notice a huge gap. In order to address this bottleneck, we previously developed the Learning-Adapting-Leveling (LAL) model. Aim: In this article, we aim to demonstrate the overarching reach of the model for translation to market and implementation into healthcare systems moving towards personalized healthcare. Methods: We use qualitative logical reasoning with the LAL model as a reference. Results: We found that technology transfer, health needs assessment, health technology assessment and health impact assessment are justified for their inclusion. In addition, the public health wheel is justified as a good reference frame along with value of information. Conclusion: We conclude that as the LAL model covers all dimensions and tools for translation and implementation in a defined method; it can therefore be considered as the overarching framework for translation and implementation into healthcare.