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外文期刊>Frontiers in Public Health
>Learning From eHealth Implementations Through “Implementomics”: A Multidimensional Annotation Model Applied to eHealth Projects of the RAFT Network
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Learning From eHealth Implementations Through “Implementomics”: A Multidimensional Annotation Model Applied to eHealth Projects of the RAFT Network
The implementation of digital health technologies increased globally, which produces substantial amounts of information and knowledge. While there are still areas in digital health that are understudied, concurrently there is an exponential increase in published articles, guidelines, methods, projects and experiences, many of which fail to reach critical mass (pilotitis). Semantically describing and documenting this implementation knowledge and effectiveness of these tools will help to avoid the duplication of efforts, to reduce preventable implementation obstacles, and to assure that investments are targeted to the most important technological innovations. The RAFT annotation model, presented in this paper, enables to semantically describe all elements of various outputs and implementation projects that were developed, are used, or are part of the RAFT network. This model was developed to annotate various implementations and outputs of the RAFT network to facilitate knowledge documentation and sharing, and to be used as a proof of concept for the Implementome. The Implementome will be an interconnected knowledge system that enables the user to navigate on multiple dimensions through metadata annotated projects, people, and information, and can serve as base for consensus building, best practices and guidelines. The RAFT annotation model can be further developed to enable the annotation of outputs, implementations, people, initiatives and projects of the digital health domain in general.
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