Tokars Jerome

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

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.

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.

BioSense is a national program designed to improve the nation’s capabilities for conducting disease detection, monitoring, and real-time situational awareness. Currently, BioSense receives near real-time data from non-federal hospitals, as well as national daily batched data from the Departments of Defense and Veteran’s Affairs facilities.  These data are analyzed, visualized, and made simultaneously available to public health at local, state, and federal levels through the BioSense application.

Objective:

In this paper we present summary information on the non-federal hospitals currently sending data to the BioSense system and describe this distribution by hospital type, method of data delivery as well as patient class and patient health indicator.

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. This project was spurred by the recent detection of several clusters with chief complaints containing the term “exposure” only some of which map to current BioSense sub-syndromes. BioSense currently does not have a generic “exposure” sub-syndrome.

OBJECTIVE

To identify hospital visits with chief complaints concerning exposures, characterize them, and develop methods for detecting exposure clusters.

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.

Influenza surveillance provides public health officials and healthcare providers with data on the onset, duration, geographic location, and level of influenza activity in order to guide the local use of interventions. The Influenza Sentinel Provider Surveillance Network tracks influenza-like illness (% ILI) across the U.S. population. Objective: This presentation describes the use of influenza antiviral data from retail pharmacies to supplement influenza surveillance.

Since July 2004 the BioSense program at the Centers for Disease Control and Prevention (CDC) has received data from DoD military and VA outpatient clinics (not in real time). In January 2006 real-time hospital data (e.g. chief complaints and diagnoses) was added. Various diagnoses from all sources are binned into one or more of 11 syndrome categories.

Objective

This paper'­s objective is to compare syndromic categorization of newly acquired real-time civilian hospital data with existing BioSense data sources.

The objective of this project was to develop an efficient method to map Logical Observation Identifier Names and Codes (LOINC) to notifiable conditions to accommodate future changes in standard laboratory test codes.