Yinsheng Zhang1, Haomin Li2, Huilong Duan3, Yinhong Zhao4. 1. 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. Electronic address: elevenjohns@163.com. 2. Children׳s Hospital, Institute of Translational Medicine, Zhejiang University, Hangzhou 310027, China. Electronic address: hmli@zju.edu.cn. 3. College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou 310027, China. Electronic address: duanhl@zju.edu.cn. 4. China National Center for Biotechnology Development, Beijing 100036, China. Electronic address: zhaoyh@cncbd.org.cn.
Abstract
BACKGROUND: 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. METHOD: 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. RESULTS: 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). DISCUSSION: Computer-aided knowledge translation via a CDS infrastructure can be effective in facilitating knowledge translation in clinical settings.
BACKGROUND: 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. METHOD: 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. RESULTS: 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). DISCUSSION: Computer-aided knowledge translation via a CDS infrastructure can be effective in facilitating knowledge translation in clinical settings.