文章基本信息

标题：A CONCEPTUAL OF KNOWLEDGE MANAGEMENT SYSTEM MODEL WITH EARLY WARNING SYSTEM IN CLINICAL DIAGNOSTIC ENVIRONMENT OF DENGUE FEVER
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作者：NORZALIHA MOHAMAD NOOR ; RUSLI ABDULLAH
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2017
卷号：95
期号：24
页码：6974
出版社：Journal of Theoretical and Applied
摘要：Knowledge management system (KMS) support the activities of knowledge management (KM) in early warning system (EWS) to provide early warning and aid in decision facilitation. Both KMS with EWS are also applicable in the clinical diagnostic (CD) environment during the CD activities to provide early warning and aid in decision facilitation of disease outbreak such as dengue. However, lack of proper data or information management and limited knowledge sharing and dissemination within the organization is a main challenge for mitigation of risk. In which the problem that may relate to this challenge is the timeliness for timely reporting and decision facilitation during CD activities. Therefore, a conceptual of KMS model with EWS in CD environment of dengue fever is formulated based on the existing components of KM, KMS with EWS. Then, the components of CD activities and dengue fever are also identified and studied for the model implementation. A pre survey and the analysis of five existing previous models were carried out to determine the significant components of KMS and EWS. The pre survey results analysis and gaps drawn from the analysis of these five models are used as a basis to the initial proposed of KMS model with EWS in CD environment of dengue fever. Next, the KMS model with EWS was then validated via prototype to verify the model reliability and is evaluated via a post survey. The model which is the integration between KMS with EWS is known as KMS with EWS is to enable the capturing, storing, reusing and managing of knowledge in order to provide early warning and aid in decision facilitation of dengue fever.
关键词：Knowledge Management; Knowledge Management System; Early Warning System; Clinical Diagnostic; Dengue Fever