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To determine the feasibility of using BioSense laboratory data to do surveillance on Clostridium difficile infection (CDI) and calculate overall and facility rates of disease.

Content type: Abstract

BioSense is a national system that receives, analyzes, and visualizes electronic health data and makes it available for public health use. In December 2007 CDC added the Influenza Module to the main BioSense application.

 

Objective

This presentation describes the new... Read more

Content type: Abstract

To compare regression models with the modified C2 algorithm for analysis of time series data and real time outbreak detection.

Content type: Abstract

In addition to monitoring Emergency Department chief complaint data and pharmacy sales as indicators of outbreaks, the New York State Department of Health (NYSDOH) Syndromic Surveillance System also monitors information from the CDC’s Early Event Detection and Situational Awareness System,... Read more

Content type: Abstract

Objective The objective of this study was to determine which chief complaints and ICD-9-CM coded diagnoses from real-time BioSense hospital data correlate well with data from conventional influenza surveillance systems.

Content type: Abstract

The Centers for Disease Control and Prevention BioSense has developed chief complaint (CC) and ICD9 sub syndrome classifiers for the major syndromes for early event detection and situational awareness. The prevalence of these sub-syndromes in the emergency department population and the ... Read more

Content type: Abstract

Objective

To describe a standard set of criteria for identifying potentially important anomalies and to compare the criteria with several recent public health events.

Content type: Abstract

Analysis of time series data requires accurate calculation of a predicted value. Non-regression methods such as the Early Aberration Reporting System CuSum are computationally simple, but most do not adjust for day of week or holiday. Alternately, regression methods require larger counts, more... Read more

Content type: Abstract

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.

Content type: Abstract

The BioSense system currently receives real-time data from more than 370 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 (... Read more

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