Discovering the New Frontier of Syndromic Surveillance (Pt 3): A Meaningful Use Dialogue on the BioSense Implementation

This webinar is part of the Meaningful Use Webinar Series entitled "Discovering the New Frontier of Syndromic Surveillance: A Meaningful Use Dialogue"


Taha Kass-Hout, MD, MS, Centers for Disease Control and Prevention

Date and Time

Monday, March 19, 2012

September 30, 2017

Survey of Syndromic Surveillance Uses

Syndromic surveillance is the surveillance of healthrelated data that precedes diagnosis to detect a disease outbreak or other health related event that warrants a public health response. Though syndromic surveillance is typically utilized to detect infectious disease outbreaks, its utility to detect bioterrorism events is increasingly being explored by public health agencies.

July 30, 2018

Performance of Sub-Syndrome Chief Complaint Classifiers for the GI Syndrome

The Centers for Disease Control and Prevention BioSense project has developed chief complaint (CC) and ICD9 sub-syndrome classifiers for the major syndromes for early event detection and situational awareness. This has the potential to expand the usefulness of syndromic surveillance, but little data exists evaluating this approach. The overall performance of classifiers can differ significantly among syndromes, and presumably among subsyndromes as well.

July 30, 2018

Automated Monitoring of Exposures Using the BioSense System

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.

July 30, 2018

Identifying Clusters of Falls During the 2007-08 Winter Season in the BioSense System

The purposes of this study are to identify and characterize increases in emergency department (ED) visits for falls during the 2007-08 winter season.

July 30, 2018

BioSense 2.0 Definitions

Definitions for BioSense 2.0 common syndromes.

June 13, 2017

The Performance of Sub-Syndrome Chief Complaint Classifiers for the GI and RESP Syndromes

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 performance of these CC classifiers have been little studied. Chart reviews have been used in the past to study this type of question but because of the large number of cases to review, the labor involved would be prohibitive.

July 30, 2018

The Use of BioSense Data for Surveillance of Gastrointestinal Illness

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 (indicators). One of the 11 syndromes is gastrointestinal (GI) illness and 6 of the subsyndromes (abdominal pain; anorexia, diarrhea, food poisoning, intestinal infections, ill-defined; and nausea and vomiting) represent gastrointestinal concepts.



July 30, 2018

Performance Characteristics of Control Chart Detection Methods

To recognize outbreaks so that early interventions can be applied, BioSense uses a modification of the EARS C2 method, stratifying days used to calculate the expected value by weekend vs weekday, and including a rate-based method that accounts for total visits. These modifications produce lower residuals (observed minus expected counts), but their effect on sensitivity has not been studied.



To evaluate several variations of a commonlyused control chart method for detecting injected signals in 2 BioSense System datasets.

July 30, 2018

Identifying Fractures in BioSense Radiology Reports

The purposes of this study are to validate a keyword-based text parsing algorithm for identifying fractures and compare radiology results with chief complaint and ICD-9 final diagnoses.

July 30, 2018


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