| Summary: | 碩士 === 臺北醫學大學 === 醫學資訊研究所 === 96 === Syndromic surveillance is the utillization of data that large amount of cases with prodromal phase symptoms and performs spatial-temporal clustering analysis through information technology for rapidly detecting disease outbreaks with visualization and aberration detection theory so that a further epidemiology investigation and disease control procedure could be taken in its very early time.In recent years, many countries have adopted syndromic surveillance systems as the frontline defense against emerging infectious diseases or bioterrorism attacks. Although Taiwan’s Centers for Disease Control, R.O.C.(Taiwan CDC) has established the system for several years, the disease control staff and investigators in local health agencies and hospitals are lack of experience in using syndromic surveillance systems for prevention of infectious disease outbreaks. Therefore, this study focuses on: (1) the establishment of an integrated syndromic surveillance system that can automatically collect data from hospital emergency departments (ED) in Taipei City in a timely and flexible fashion, (2) development of effective algorithms for early detection of disease outbreaks using data of routinely collected chief complaints or ICD-9 CM codes, and (3) provision of friendly interfaces for the presentation of surveillance data to provide information for healthcare workers and decision-makers at different levels of position in hospitals in order to enhance the capability in the detection and prevention of disease outbreaks.
The study selected five hospitals located in different geographical areas of Taipei City. The system has established and collected data of patient visiting ED (totally about 500,000 visits) during the period of January 1, 2005 and June 30, 2008. There are 8 syndrome groups for routine surveillance. In addition, the system can dynamically define new groups based on the trends of disease occurrence. Until now 5 dynamically defined syndrome groups have been performed in this system as an extra targeted surveillance. The historical limit method with the short-term and long-term baseline data is used for analysis in aberration detection, and the alerts are delivered over to persons concerned via email once it is detected. Meanwhile, the analyzed surveillance data, which is accessible through pages on website, can be used to compare the parallel trends of disease occurrence in different years. Furthermore, they can also be linked to a geographic information system to view the dynamic changes in temporal and spatial patterns of disease occurrence, the occurrence scale of clustering cases, and the development of trends for any interested syndromes.
Since our system is mainly used for surveillance of locally important disease and covered only Taipei area in geographic, in the future, we will make our effort to set our disease defense strategies by grading them into different stages in the processes of preparation and response, so that it can work as a whole with those conducted by the central government, to get better system performance.
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