Syndromes

The purpose of syndromic surveillance is the early identification of disease outbreaks. Classification of chief complaints into syndromes and the type of statistics used for aberration detection can affect outbreak detection sensitivity and specificity. Few data are available on the relationship between chief complaints and demographics such as gender, age, or race. For example, myocardial infarction in women would be misclassified using definitions based solely on “male” symptoms such as chest pain because women more commonly report neck, jaw, and back pain.

Objective

We evaluated the sensitivity and specificity of a gastrointestinal syndrome group using the Boston Public Health Commission syndromic surveillance system.

The goal of this project is to create a set of clinical condition categories based on explicit criteria for use in biosurveillance programs. The categories will be defined and keywords and ICD-9-CM diagnosis codes for implementation will be proposed.

The goal of this paper is to describe a methodology used to create a gold standard set of emergency department (ED) data that can subsequently be used to evaluate the sensitivity and specificity of syndrome definitions.

We will convene a consultative meeting on chief complaint classifiers and standardized syndromic definitions in Pittsburgh, PA, from September 24-25,

The purpose of this study was to determine if existing chief complaint and ICD-9 codes for detecting gastrointestinal syndrome correctly identify similar patterns of illness when applied to the Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE IV).

We evaluated several classifications of emergency department (ED) syndromic data to ascertain best syndrome classifications for ILI.

Most research in syndromic surveillance has emphasized early detection, but clinical diagnosis of the index case will tend to occur before detection by syndromic surveillance for certain types of outbreaks [1]. Syndromic surveillance may, however, still play an important role in rapidly characterizing the outbreak size because there will be additional non-diagnosed symptomatic cases in the medical system when the index case is identified. Other authors have shown that the temporal pattern of symptomatic cases could be used to project the total outbreak size, but their approach requires a priori knowledge of the incubation curve for the specific anthrax strain and exposure level [2]. In this paper, we focus on estimating the number of non-diagnosed symptomatic cases at the time of detection without making assumptions about the exposure level or disease course.

Objective 

Upon detection of an inhalational anthrax attack, a critical priority for the public health response would be to characterize the size and extent of the outbreak. Our objective is to assess the potential role of syn-dromic surveillance in estimating the outbreak size.

BioSense is a national automated surveillance system designed to enhance the nation's capability to rapidly detect and quantify public health emergencies, by accessing and analyzing diagnostic and prediagnostic health data. The BioSense system currently receives near real-time data from more than 540 civilian hospitals, as well as national daily batched data from over 1100 Department of Defense and Veterans Affairs medical facilities. BioSense maps chief complaint and diagnosis data to 11 syndromes and 78 sub-syndromes. This project was spurred by the recent detection of several clusters with chief complaints containing the term “exposure” only some of which map to current BioSense sub-syndromes. BioSense currently does not have a generic “exposure” sub-syndrome.

OBJECTIVE

To identify hospital visits with chief complaints concerning exposures, characterize them, and develop methods for detecting exposure clusters.

We report on a retrospective analysis of gastrointestinal syndrome definitions based on chief complaints and ICD9 diagnosis for gastroenteritis during the 2006-07 season of increased norovirus activity.