A conceptual knowledge management system model with early warning system in clinical diagnostic environment of dengue fever - Mohamad Noor, Norzaliha (2017)
Knowledge management system (KMS) is an information technology (IT) based system that supports four common activities of knowledge management (KM) processes namely i) knowledge acquisition; ii) knowledge codification; iii) knowledge application; and iv) knowledge dissemination. Meanwhile, disaster management is the activities concerning the mitigation, risk reduction, prevention, preparedness, response and recovery can be related to early warning system for risk mitigation. Early Warning System (EWS) can aid in the early warning to reduce any damage or loss by facilitating the timely communication and response. EWS is referring to the collection of information that leads to timely decision-making processes in order to mitigate risk encompassed with four main components, namely i) risk knowledge; ii) monitoring and warning services; iii) communication and dissemination and iv) response capability. 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 the main issue during the EWS. Other problem that may relate to this issue is the timeliness for timely reporting and decision facilitation during CD activities. Therefore, a conceptual of KMS model with EWS in the CD environment of dengue fever is formulated based on the existing components KMS with EWS. The CD activities and dengue fever components are also studied for the model implementation. A pre survey was carried out to determine significant components for both KMS with EWS. Then these components are further verified by experts. Based on the pre survey results and analysis, the initial KMS model with EWS in CD environment of dengue fever is proposed. The KMS model with EWS was then validated via prototype to verify the model reliability. Then, a post survey is used to evaluate the KMS prototype which is based on the KMS with EWS model in CD environment of dengue fever. The results of post surveys were divided into two categories of analysis. First analysis is the reliability of the proposed KMS with EWS model by comparatively analysed the overall surveys result against the existing previous models and secondly is the analysis on KMS prototype from the user's perspective based on the five main attributes address in this survey items. In which the analysis is based on reliability of the attributes in order to know the attributes ranking and significant to the proposed model. All the analysis of pre and post surveys was measure using Rasch Model. 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.