淡江大學機構典藏:Item 987654321/108183
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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/108183


    Title: Intelligent Infection Surveillance System to assist the Control of Healthcare-Associated Infections
    Authors: Nan-Chen Hsieh, Jui-Fa Chen and Hsin-Che Tsai
    Keywords: Healthcare-Associated Infections;Healthcare Information Technology;Automatic Surveillance
    Date: 2016-07-01
    Issue Date: 2016-11-05 02:11:02 (UTC+8)
    Publisher: 中華民國電腦學會
    Abstract: Healthcare-Associated Infections (HAI) are important quality indicators of healthcare, a leading cause of mortality and morbidity worldwide, and contributors to lower medical quality and increases in medical costs. Based on the definition and determining criteria of healthcare-related infections stipulated by Taiwan’s Centers for Disease Control, Department of Health, we created a program for an HAI determining
    rule, as well as an HAI monitoring system environment. With a data warehouse and data mining techniques as the core, we integrated all HAI-related data as analytical information for the purpose of decision-making.

    Key decision information was presented visually in a dashboard. In this way, infection control professionals
    are able to peruse abundant HAI information through a visual interface at anytime, anywhere. Traditionally,
    operation is done manually through continuous monitoring and automatic surveillance management. Decision makers can assess measuring indicators in real-time, which is critical to the management of HAI. This also allows HAI control professionals to cross-analyze and understand potential infection trends, and assist hospitals in developing a suitable HAI monitoring mechanism. By using the developed system, we can discover healthcare-related infection abnormalities earlier and provide infection control professionals with the ability to check on and conduct pre-decision analyses .
    Relation: Journal of Computers 27(2), pp.36-49
    Appears in Collections:[Graduate Institute & Department of Computer Science and Information Engineering] Journal Article

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