文章基本信息

标题：INTEGRATED KMS@EWS OF CONCEPTUAL IMPLEMENTATION MODEL FOR CLINICAL DENGUE FEVER ENVIRONMENT
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作者：Norzaliha Mohamad Noor ; Rusli Abdullah ; Mohd Hasan Selamat 等
期刊名称：International Journal of New Computer Architectures and their Applications
印刷版ISSN：2220-9085
出版年度：2011
卷号：1
期号：3
页码：743-756
出版社：Society of Digital Information and Wireless Communications
摘要：Early warning system (EWS) is a technology to mitigate risk is used to disseminate timely information. Then knowledge management system (KMS) is used to support for decision facilitation will integrate with EWS to disseminate timely information with proactive early warning. Issues on timeliness for timely reporting and decision facilitation are regarded as main challenge for mitigation of risk. Therefore in this paper, we suggest the model of integration between KMS and EWS known as KMS@EWS as a solution to support early warning for timely reporting and to guide on decision facilitation. The integration model is to combine the knowledge management (KM) processes, activities and technologies with the EWS functionalities. The proposed model is based on empirical study by using literatures on EWS and KMS. In which we synthesize the analysis and findings of both EWS and KMS for the integration. We propose the implementation model in clinical diagnostic (CD) environment of dengue fever (DF) manifestation. This model is intended to provide early warning when any abnormalities or peculiar pattern of DF and symptoms arise and detected during the interaction between physicians and patients in the CD environment. Thus, this paper attempts to integrate relevant enabling KM technologies and processes with EWS components and functionalities into an environment that would support activities for early warning thru organizational knowledge creation, use and management for timely reporting and detection by providing decision facilitation and initiate early warning of DF during CD processes.
关键词：Early warning system; Knowledge ; management; Knowledge management ; system; Dengue fever; Clinical diagnostic