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Evaluation of Syndromic Surveillance

Description

In 2003, the need for a system to track and manage patient status and location was identified by Boston Emergency Medical Services (Boston EMS) and the Conference of Boston Teaching Hospitals. After consultation with EMS (municipal, fire based, and private), hospital, local and state public health and emergency management stakeholders, a core group from Boston EMS and Boston Public Health Commission (BPHC) developed guidelines for a Metro Boston Patient Tracking System. The goal was to provide a system to reunite family members and serve as a tool for managing short term/high impact mass casualty incidents and protracted disease outbreaks.

Since 2004, BPHC Communicable Disease Control Division (CDC) has effectively managed several mass prophylaxis clinics in response to infectious disease outbreaks. However patient data was largely collected on paper based forms, limiting the availability of real-time clinic data to incident command. To address these challenges BPHC CDC began meeting with Boston EMS to define the business processes and information needs during public health emergencies.

 

Objective

To describe the electronic patient tracking system configured by Boston EMS and the BPHC CDC to address information needs during public health emergencies.

Submitted by elamb on
Description

The use of syndromic surveillance in Tulsa County began as an attempt to identify symptoms associated with Category A agents, namely Anthrax. The underlying premise for adopting the system was the hope that an astute clinician, upon observing clusters of cases exhibiting certain symptoms, would rapidly notify the local health department so that an epidemiological investigation could be initiated. The system is also designed to send spatial and temporal alerts when cases of pre-defined syndromes are observed. Since 2002, when the system was first implemented, Tulsa Health Department has looked for other ways to integrate syndromic surveillance into its daily operations, and to expand its focus from an exclusive bioterrorism tool, to one that is broader in scope. One such way has been to  utilize the system to identify other syndromes and conditions. Collected emergency data has therefore, been used to identify occurrences of animal bites, mental conditions etc. This paper addresses the use of syndromic surveillance for the identification of heat-related illnesses during the hot Oklahoma summer months.

 

Objective

This paper describes the application of syndromic surveillance methodologies to identify nonbioterrorism syndromes particularly, the incidence of heat-related syndromes during the hot Oklahoma summer months.

Submitted by elamb on
Description

The threat of pandemic and seasonal influenza has drawn attention to syndromic surveillance systems for early detection of influenza-like illness. Since 2005, the Miami-Dade County Health Department has implemented ESSENCE (Electronic Surveillance System for the Early Notification of Community-based Epidemics) to monitor emergency department data for influenza-like Illness (ILI) using chief complaint information. This study evaluates the ability of the ESSENCE ILI chief complaint grouping for identifying true ICD-9 diagnosed influenza.

 

Objective

Previous studies have examined the utility of different methods of syndromic grouping. This study evaluates the utility of ESSENCE for ILI surveillance.

Submitted by elamb on
Description

ICD-9-CM codes have been proposed to be used as adjuncts to existing public health reporting systems and are commonly used for public health surveillance and research purposes. However these codes have been found to have variable accuracy for both healthcare billing as well as for disease classification due to both coding and physician errors, and these codes have never been comprehensively validated for their use for surveillance. Quantification of the positive predictive value for ICD-9 CM diagnosis codes is crucial for assessing their utility for public health disease surveillance and research.

 

Objective

To quantify the positive predictive values of ICD-9 CM diagnosis codes for public health surveillance of communicable diseases.

Submitted by elamb on
Description

Measures aimed at controlling epidemics of infectious diseases critically benefit from early outbreak recognition. Through a manual electronic medical record (EMR) review of 5,127 outpatient encounters at the Veterans Administration health system (VA), we previously developed single-case detection algorithms (CDAs) aimed at uncovering individuals with influenza-like illness (ILI). In this work, we evaluate the impact of using CDAs of varying statistical performance on the time and workload required to find a community-wide influenza outbreak through a VA-based syndromic surveillance system (SSS). The CDAs utilize various logical arrangements of EMR data, including ICD-9 codes, structured clinical parameters, and/or an automated analysis of the free-text of the full clinical note. The 18 ILI CDAs used here are limited to the most successful representatives of ICD-9-only and EMR-based case detectors.

 

Objective

This work uses a mathematical model of a plausible influenza epidemic to begin to test the influence of CDAs on the performance of a SSS.

Submitted by elamb on
Description

The North Carolina Bioterrorism and Emerging Infection Prevention System (NC BEIPS) receives daily emergency department (ED) data from 33 (29%) of the 114 EDs in North Carolina. These data are available via a Web-based portal and the Early Aberration Reporting System to authorized NC public health users for the purpose of syndromic surveillance (SS). Users currently monitor several syndromes including: gastrointestinal severe, fever/rash illness and influenza-like illness. The syndrome definitions are based on the infection-related syndrome definitions of the CDC and search the chief complaint (CC) and, when available, triage note (TN) and initial temperature fields. Some EDs record a TN, which is a brief text passage that describes the CC in more detail. Most research on the utility of ED data for SS has focused on the use of CC. The goal of this study was to determine the sensitivity, specificity, and both positive and negative predictive value of including TN in the syndrome queries.

 

Objective

This study evaluates the addition of TN to syndrome queries used in the NC BEIPS.

Submitted by elamb on
Description

San Diego County Public Health has been conducting syndromic surveillance for the past few years. Currently, the system has become largely automated and processes and analyzes data from a variety of disparate sources including hospital emergency departments, 911 call centers, prehospital transports, and over-the-counter drug sales. What has remained constant since the system’s initial conceptualization is the local opinion that the data should be analyzed and interpreted in a variety of ways, in anticipation for the variety of contexts in which events that are of public health interest may unfold. Relatively small increases in volume that are sustained over time will likely be detected by methods designed to detect “small process shifts”, and include the CUSUM and EWMA methods. Larger increases in volume that are not sustained over time will likely be detected by other employed methods (P-Chart in the event of a non-proportional increase in volume, U-Chart in the event of a proportional increase in volume). A retrospective analysis was conducted on historical data from various data sources to determine the frequency of signals and detected events as well as the context within which the alert occurred (i.e., the “shape” of the data). Findings regarding several actual public health events will also be discussed.

 

Objective

This paper describes the frequency, various “shapes” and magnitudes of data anomalies, and varying ways actual public health events may present themselves in syndromic data.

Submitted by elamb on
Description

Overseas studies showed that increases in over-the-counter (OTC) drug sales might serve as an indicator of community disease outbreaks before they are detected by conventional surveillance systems. Using data collected retrospectively from commercial drug retailers, the Department of Health of Hong Kong conducted an exploratory study to examine the potential of monitoring OTC drug sales for early detection of community disease outbreaks.

 

Objective

This study evaluates whether OTC drug sales can serve as an earlier indicator for detecting community disease outbreaks in Hong Kong.

Submitted by elamb on
Description

States and localities are using biosurveillance for a variety purposes including event detection, situational awareness, and response. However, little is known about the impact of biosurveillance on the operational components and functioning of the public health system and the added value of biosurveillance to traditional surveillance methods. A deeper understanding of how state and local public health systems use biosurveillance data and the factors that facilitate and impede its utility are needed to inform efforts to improve public health surveillance.

 

Objectives

A goal of the case studies was to assess the impact of biosurveillance on public health system preparedness, detection and response for a range of public health threats.

Submitted by elamb on
Description

National surveillance is used to detect the emergence and spread of influenza virus variants and to monitor influenza-related morbidity and mortality. Nurse telephone triage (“call”) data may serve as a useful complement to traditional influenza surveillance, especially at times or in places traditional surveillance is not operating. It may also be useful to detect increased occurrence of non-influenza respiratory infection.

 

Objective

We compared state-level nurse call data to CDC national influenza surveillance data to determine how well call data performed relative to CDC sentinel provider and viral isolate data. This quantitative analysis extends an earlier semiquantitative regional analysis of the same data.

Submitted by elamb on