RTI International, in partnership with the University of North Carolina at Chapel Hill (UNC-CH), and in collaboration with the North Carolina Division of Public Health (NC-DPH), is submitting this application to work with the Centers for Disease Control and Prevention (CDC) to improve early detection of disease outbreaks of public health significance. Rapid detection of disease outbreaks rests on a foundation of accurate classification of patient symptoms early in the course of their illness. The overarching objective of this research is to define, evaluate, and standardize a methodology for creating useful case definitions designed for the early detection of intentional and naturally occurring disease outbreaks.
The specific aim of this research proposal is to develop and test methods for increasing the sensitivity and specificity of syndrome definitions using timely emergency department data. Improved case definitions will enhance CDC's capacity to detect and investigate threats to the health of the population, which CDC undertakes as part of its mission. Emergency department data may serve as a rich source for early signals of health threats to the population, but case definitions have not been standardized, and new methods are needed to process and use the textual information found within the emergency record. To address these challenges, we propose an innovative and iterative research plan that leverages RTI's and UNC-CH's capabilities to best serve CDC and the public health community. We will use emergency department data captured through North Carolina's Bioterrorism and Emerging Infections Preventive Service, the operational syndromic surveillance system used by NC-DPH to monitor the state. After (1) developing a gold standard data set of ED visits for evaluating syndrome test characteristics, we will (2) evaluate natural language processing for preprocessing chief complaints; (3) explore use of semantic networking tools for developing definitions; (4) apply a reverse engineering process using ICD-9-CM code groupings; and (5) assess the applicability of early event detection for creating situational awareness following detection of an event. These methods will make use of information within the emergency record and create syndrome definitions with acceptable sensitivity, specificity, and positisve predictive value. Valid syndrome definitions will enable public health officials to operate a national monitoring system that can automatically detect signals that may represent disease outbreaks or other potential threats to health. Operation of this system will protect the public health and will strengthen the capacity of public health officials to investigate and respond to these threats rapidly.
| Travers, Debbie; Wu, Shiying; Scholer, Matthew et al. (2007) Evaluation of a chief complaint pre-processor for biosurveillance. AMIA Annu Symp Proc :736-40 |
| Scholer, Matthew J; Ghneim, George S; Wu, Shiying et al. (2007) Defining and applying a method for improving the sensitivity and specificity of an emergency department early event detection system. AMIA Annu Symp Proc :651-5 |
