College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou 310027, China; School of Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou 310018, China.
Children׳s Hospital, Institute of Translational Medicine, Zhejiang University, Hangzhou 310027, China.
Comput Biol Med. 2015 May;60:40-50. doi: 10.1016/j.compbiomed.2015.02.013. Epub 2015 Feb 21.
A wide gulf remains between knowledge and clinical practice. Clinical decision support has been demonstrated to be an effective knowledge tool that healthcare organizations can employ to deliver the "right knowledge to the right people in the right form at the right time". How to adopt various clinical decision support (CDS) systems efficiently to facilitate evidence-based practice is one challenge faced by knowledge translation research.
A computer-aided knowledge translation method that mobilizes evidence-based decision supports is proposed. The foundation of the method is a knowledge representation model that is able to cover, coordinate and synergize various types of medical knowledge to achieve centralized and effective knowledge management. Next, web-based knowledge-authoring and natural language processing based knowledge acquisition tools are designed to accelerate the transformation of the latest clinical evidence into computerized knowledge content. Finally, a batch of fundamental services, such as data acquisition and inference engine, are designed to actuate the acquired knowledge content. These services can be used as building blocks for various evidence-based decision support applications.
Based on the above method, a computer-aided knowledge translation platform was constructed as a CDS infrastructure. Based on this platform, typical CDS applications were developed. A case study of drug use check demonstrates that the CDS intervention delivered by the platform has produced observable behavior changes (89.7% of alerted medical orders were revised by physicians).
Computer-aided knowledge translation via a CDS infrastructure can be effective in facilitating knowledge translation in clinical settings.
知识与临床实践之间存在巨大差距。临床决策支持已被证明是一种有效的知识工具，医疗机构可以利用它来提供“正确的知识、正确的人、正确的形式、正确的时间”。如何有效地采用各种临床决策支持（CDS）系统来促进循证实践是知识转化研究面临的挑战之一。
提出了一种利用基于证据的决策支持的计算机辅助知识转化方法。该方法的基础是一个知识表示模型，该模型能够涵盖、协调和协同各种类型的医学知识，以实现集中有效的知识管理。接下来，设计了基于网络的知识创作和基于自然语言处理的知识获取工具，以加速将最新的临床证据转化为计算机化的知识内容。最后，设计了一批基本服务，如数据采集和推理引擎，以激活获取的知识内容。这些服务可以作为各种基于证据的决策支持应用程序的构建块。
基于上述方法，构建了一个计算机辅助知识转化平台作为 CDS 基础设施。在此平台上，开发了典型的 CDS 应用程序。药物使用检查的案例研究表明，该平台提供的 CDS 干预措施产生了可观察的行为变化（医生修改了 89.7%的提醒医嘱）。
通过 CDS 基础设施进行计算机辅助知识转化可以有效地促进临床环境中的知识转化。
