Syndromes

Text-based syndrome case definitions published by the Center for Disease Control (CDC)1 form the basis for the syndrome queries used by the North Carolina Disease Event Tracking and Epidemiologic Collection Tool (NC DETECT). Keywords within these case definitions were identified by public health epidemiologists for use as search terms with the goal of capturing symptom complexes from free-text chief complaint and triage note data for the purpose of early event detection and situational awareness. Initial attempts at developing SQL queries incorporating these search terms resulted in the return of many unwanted records due to the inability to control for certain terms imbedded within unrelated free text strings. For example, a query containing the search term “h/a”, a common abbreviation for headache, also returns false positives such as “cough/asthma”, “skin rash/allergic reaction” or “psych/anxiety”.  Simple abbreviations without punctuation, such as “ha”, were even more problematic.  Global wildcards ('%') indicate that zero or more characters of any type may substitute for the wildcard.2 The term “ha” as a synonym for "headache" appears frequently in the data, but searching this term bracketed by global wildcards returns any instance where the two letters appear together (e.g. pharyngitis, hand, hallucinations, toothache). Using global wild cards to search for common symptoms such as headache using simple abbreviations, with or without specialized punctuation, results in the return of many unwanted false positive records. We describe here the advanced application of SQL character set wildcards to address this problem.

Objective

This paper describes a novel approach to the construction of syndrome queries written in Structured Query Language (SQL). Through the advanced application of character set wildcards, we are able to increase the number of valid records identified by our queries while simultaneously decreasing the number of false positives.

The inception of syndromic surveillance has spawned a great deal of research into emergency department chief complaint data. In addition to its use as an early warning system of a bioterror or outbreak event, many health departments are attempting to maximize the utility of the information to augment chronic and communicable disease surveillance. Hence, it can be used to enhance the traditional methods of surveillance. Using syndromic data to describe what could be the normal for a geographic area may be useful in monitoring a population for disease trends. Prevention efforts could be concentrated during a particular time of year. In addition, geospatial shifts in directional trends may indicate an unusual occurrence related to the utilization of emergency department services.

Objective

To describe the geographical mean as well as the directional trends of syndromes for the District of Columbia using temporal and geospatial analyses.

In North Carolina, select hospital emergency departments have been submitting data since 2003 for use in syndromic surveillance. These data are collected, stored, and parsed into syndrome categories by the North Carolina Emergency Department Database. The fever with rash illness syndrome is designed to capture smallpox cases. This syndrome was created as a combination of the separate fever and rash syndromes proposed by the consensus recommendations of the CDC’s Working Group on Syndrome Groups.

Objective 

This paper describes the construction of a syndromic surveillance case definition and a test for its ability to capture the appropriate syndromic cases.

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.