Perrin Caroline, Bediang Georges, Randriambelonoro Mirana, Geissbuhler Antoine
HI5lab, Department of Radiology and Medical Informatics, Geneva University, Geneva, Switzerland.
Division of eHealth and Telemedicine, Geneva University Hospitals, Geneva, Switzerland.
Front Public Health. 2019 Jul 5;7:188. doi: 10.3389/fpubh.2019.00188. eCollection 2019.
The implementation of digital health technologies has increased globally, producing 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 the 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 initially 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 . The 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.
数字健康技术在全球范围内的应用日益广泛，产生了大量的信息和知识。虽然数字健康领域仍有一些方面研究不足，但与此同时，已发表的文章、指南、方法、项目和经验呈指数级增长，其中许多未能达到临界规模（试点项目病）。从语义上描述和记录这些实施知识以及这些工具的有效性，将有助于避免重复劳动，减少可预防的实施障碍，并确保投资针对最重要的技术创新。本文介绍的RAFT注释模型能够从语义上描述已开发、正在使用或属于RAFT网络一部分的各种产出和实施项目的所有要素。该模型最初是为注释RAFT网络的各种实施和产出而开发的，以促进知识记录和共享，并用作……的概念验证。……将是一个相互连接的知识系统，使用户能够通过元数据注释的项目、人员和信息在多个维度上进行导航，并可作为建立共识、最佳实践和指南的基础。RAFT注释模型可以进一步开发，以实现对数字健康领域一般的产出、实施、人员、倡议和项目的注释。
