Displaying results 9 - 16 of 32
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BioSense Real-Time Data Initiative: Improving Emergency Preparedness- Monitoring Injury Sub-Syndromes
Content Type: Abstract
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).… read more -
Burns Reported to the BioSense System During the Independence Day Holiday
Content Type: Abstract
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… read more -
Clostridium Difficile, Surveillance Using Laboratory Data from BioSense Hospitals
Content Type: Abstract
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. -
Comparison of Regression Models with Modified Time Series Methods for BioSurveillance
Content Type: Abstract
To compare regression models with the modified C2 algorithm for analysis of time series data and real time outbreak detection. -
Correlation between Real-Time BioSense Influenza Indicators and Data from the U.S. Influenza Sentinal Physicians Surveillance Network
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. -
Criteria for Prioritizing Statisitical Anomalies Identified in BioSense
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. read more -
Defining Clinical Condition Categories for Biosurveillance
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. -
Evaluation of Spatial Estimation Methods for Cluster Detection
Content Type: Abstract
CDC’s BioSense system provides near-real time situational awareness for public health monitoring through analysis of electronic health data. Determination of anomalous spatial and temporal disease clusters is a crucial part of… read more