Emergency Department (ED)

The Utah Department of Health documented a single epidemic of cryptosporidiosis in Utah during 2007. Seven hundred eleven laboratory-confirmed cases were reported in Salt Lake County, Utah from July 27 through December 18. Illness onset date was available for 86% (611 of 711) of patients and ranged from May 30 through November 11. Approximately 32% (224 of 691) of patients sought care in area emergency departments or urgent care facilities, and 8.5% (50 of 590 with data available) of patients required hospitalization. Sixty-one percent (432 of 711) of patients were less than 13 years of age. Of 381 patients with data available on symptoms, nearly all (99%, 378) reported diarrhea. Other commonly reported symptoms included vomiting (57%, 218), abdominal pain (51%, 196), and nausea (44%, 168).

Objective

The objective of this study was to evaluate the potential for improved detection of enteric disease epidemics using a classification category based on variations of diarrhea appearing in the chief complaints from emergency department and urgent care facility visits.

The Public Health Agency of Canada is currently utilizing a syndromic surveillance prototype called the Canadian Early Warning System (CEWS). This system monitors several live data feeds, including emergency room chief complaint records from all seven local hospitals, Telehealth (24/7 nurse hotline) calls, and over-the-counter drug sales from a number of the large chain drug stores. Data trends are analysed for aberrations as early indicators of outbreak events. Collaborators on this Winnipeg, Manitoba-based pilot include the Winnipeg Regional Health Authority and IBM Business Solutions. Algorithms currently in CEWS include the 3, 5 and 7-day moving averages, CUSUM and the CDC’s EARS. We seek to investigate the performance of these algorithms in view of the fact that their detection ability may be dependent upon data source and/or the type of outbreak event.

Objective

To determine the sensitivity, specificity and days to detection of several commonly used algorithms in syndromic surveillance systems.

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.

To compare the ability to detect disease outbreaks of separate and combined data streams from ambulatory care and emergency department from Harvard Pilgrim Health Care.

This research aims to determine the catchment area of Miami Children's Hospital Emergency Department (ED). The purpose is to identify pediatric populations and territories within Miami-Dade County that are insufficiently covered by this hospital's ED.

 Syndromic surveillance systems often classify patients into syndromic categories based on emergency department (ED) chief complaints. There exists no standard set of syndromes for syndromic surveillance, and the available syndromic case definitions demonstrate substantial heterogeneity of findings constituting the definition. The use of fever in the definition of syndromic categories is arbitrary and unsystematic. We determined whether chief complaints accurately represent whether a patient has any of five febrile syndromes: febrile respiratory, febrile gastrointestinal, febrile rash, febrile neurological, or febrile hemorrhagic.

Each year, more than two-thirds of all fireworksrelated injuries occur during June 16-July 16 [1]. During the 2006 July 4th holiday weekend, thousands of people were treated in emergency departments (EDs) for fireworks-related injuries [2]. Over 50% of these injuries were burns, most often occurring on the extremities and face. CDC’s BioSense System receives near real-time data from >11% of total U.S. ED visits. Most data is sent to BioSense by state or local systems. The system includes >540 hospital EDs; 522 facilities send patient chief complaints and 182 facilities also send physician diagnoses.  BioSense maps chief complaint and diagnosis data to 11 syndromes and 78 sub-syndromes; burns are one of 13 injury-related sub-syndromes.

Objective:

To describe burn injuries reported to the BioSense System during the 2008 Independence Day holiday.

Analysis of the BioSense data facilitates the identification, tracking, and management of emergent and routine health events, including potential bioterrorism events, injury related incidents and rapidly spreading naturally occurring events (1).  BioSense enhances coordination between all levels of public health and healthcare by providing access to the same data at the same time which can ultimately produce a faster and more coordinated response.  BioSense is a network of networks rather than a stand-alone program. Analysts at the BioIntelligence center (BIC) analyze and track BioSense data activity at a national level and support state and local public health system users (2).

Objective:

BioSense is a national human health surveillance system designed to improve the nationís capabilities for disease detection, monitoring, and real-time health situational awareness.

The Los Angeles County (LAC) Bioterrorism Preparedness and Response Unit has made significant progress in automating the syndromic surveillance system. The surveillance system receives electronic data on a daily basis from different hospital information systems, then standardizes and generates analytical results.

OBJECTIVE

This article describes architecture, analytical method, and software applications used in automating the LAC syndromic surveillance system.

In 2006, approximately 6.8 million children and 16.1 million adults were reported to have asthma in the US. The CDC BioSense System currently receives data from >540 hospital emergency departments (EDs; 522 send patient chief complaints and 182 send physician diagnoses), and captures about 11% of all U.S. ED visits.

OBJECTIVE

To describe the potential utility of BioSense data for surveillance of asthma.