| 摘要: | 症候群偵測系統係指透過資訊科技，蒐集大量的臨床前期症狀(prodromal phase symptoms)，利用時間－空間聚集(spatial-temporal clustering analysis)分析處理後，結合視覺化資訊呈現和異常偵測理論，提供疫情調查人員即時掌握各項症候群/疾病的流行現況，並依此主動進行疫情調查工作，採取適當的防疫因應措施。由於症候群偵測系統是使用症狀資料而不是確診的病例數，因此可用來提早偵測可能的疫情發生，及早提出因應對策。近年來症候群偵測系統已成為各國防範新興傳染病與生物恐怖攻擊之不可或缺的工具。雖然台灣疾病管制局也相繼導入相關技術，然而，醫院結合症候群偵測系統參與防疫作業的經驗仍處於起步階段。本研究嘗試在台北市建置開發急診症候群偵測系統，整合醫院急診資料，利用主訴或國際疾病代碼(ICD-9-CM)，自動監視和偵測相關疾病群組，並提供適當的權限管理和彈性的操作介面，讓院內感染控制與公共衛生決策者監視動態定義疾病症候群的分析結果，以期望及早發現疾病的流行和提升防疫能力。
系統中將以台北市都會區5間綜合型區域醫院為對象，透過醫院資料庫中的預儲程序(stored procedure)合併急診系統的病患看診相關資料，並以資料轉換服務(Data Transformation Services，DTS)將其上傳重整後，提供症候群偵測系統運算與分析。在監視的過程中，系統根據已定義的症候群群組，自動將上傳的病例分類至不同症候群中，以做為病例數的計算。而在偵測的過程中，本系統的異常偵測 (aberration detection)方法採用歷史資料限制法(historical limit method)，其中包含不同的基準值(baseline)來做為歷年同期疾病發展之趨勢比較，並以電子郵件通報發佈發現疾病流行的異常警訊，最後將疾病監視分析結果以網頁呈現為主，也可結合地理資訊系統，查看病例在時間與空間演變、聚集與擴散走向。目前系統已收集三年的來院病患急診健康相關資料共約五十萬筆，並於2008年4月份開始配合醫院防疫作業，其中設置常規化監測的症候群共八種(呼吸道症候群、上腸胃道症候群、下腸胃道症候群、出血性症候群、神經性症候群、皮膚性症候群、類流感症候群和發燒)，彈性化監測的共五種(紅眼症、腸病毒類疾病、手口足症狀、肺炎相關、腹瀉相關) 。並實際應用於台灣2007年10月的紅眼症流行、2008年4月到6月間的第71型腸病毒流行與因應禽流感的採集檢體防疫行動。在系統的評估中，由於本系統是採取「每日」分析，並提供即時查詢和動態改變症候群組定義與偵測方法等，最後透過圖形視覺化的操作介面回饋，因此在時效性、簡易度、彈性化都較優於傳統疾病監視系統。而在資料的代表性、穩定度中，由於目前收取醫院數不多，並且尚未納入正式的防疫體系中，是目前本系統較欠缺之處。
本系統係以地方性疾病監視為主，涵蓋面僅限於部分台北市，未來將考慮分級訂定各種症候群的不同防疫警備階段與流程，互補地方與中央防疫策略，落實公共衛生防疫政策，以發揮系統有益於國民健康之最大功效。
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. |
