文章基本信息

标题：Real-Time Public Health Surveillance for Emergency Preparedness
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作者：Jean-Paul Chretien ; Nancy E. Tomich ; Joel C. Gaydos 等
期刊名称：American journal of public health
印刷版ISSN：0090-0036
出版年度：2009
卷号：99
期号：8
页码：1360-1363
DOI：10.2105/AJPH.2008.133926
语种：English
出版社：American Public Health Association
摘要：Public health agencies conduct surveillance to identify and prioritize health issues and evaluate interventions. Recently, natural and deliberate epidemics have motivated supplementary approaches to traditional surveillance methods based on physician and laboratory reporting. Fueled initially by post–September 11, 2001, bioterrorism-related funding, and more recently used for detecting natural outbreaks, these systems, many of which are called “syndromic” systems because they focus on syndromes recorded before the diagnosis, capture real-time health data and scan for anomalies suggesting an outbreak. Although these systems as typically implemented have often proven unreliable for detecting natural and simulated epidemics, real-time health-related data hold promise for public health. If redesigned to reliably perform beyond outbreak detection, syndromic systems could demonstrate unprecedented capabilities in responding to public health emergencies. Public health agencies conduct surveillance to identify and prioritize health issues and evaluate interventions. Marking a change from traditional surveillance approaches, in recent years, natural and deliberate epidemics have motivated supplementary approaches to traditional surveillance methods based on physician and laboratory reporting, which can be insensitive and slow. Systems that use automated procedures to capture near-real-time data on patient presentations or care-seeking behavior (“health indicators”) and scan for anomalies suggesting an outbreak have proliferated in the United States¹ (see the box on the following page). Many are called “syndromic” surveillance systems because they monitor clinical syndromes recorded before definitive diagnosis. Following the attacks of September 11, 2001, early syndromic surveillance efforts focused on detecting bioterrorism attacks in large populations; more recently, sponsors, users, and researchers have commonly cited their potential for detecting naturally occurring epidemics as well (e.g., Henning²). Data Sources for Health Indicator Surveillance Emergency department reason for visit Ambulatory care clinic reason for visit Hospital discharge diagnosis Medical call center data School nurse diagnosis Ambulance dispatch data School absenteeism Work absenteeism Pharmacy prescriptions Over-the-counter medicine and product sales Medical laboratory test orders and results Radiology results Open in a separate window Assessments of health indicator surveillance have noted frequent false alarms^{3 – 5} and the cost of a national system developed originally to detect bioterrorist attacks.³ Although health indicator surveillance systems have not proven highly useful for detecting naturally occurring or simulated outbreaks, proponents are right that real-time availability of health-related data holds enormous promise for public health. The potential benefit extends to a broad range of health protection activities; here we focus specifically on response to public health emergencies.