Carolina Center for Health Informatics

The Carolina Center for Health Informatics (CCHI) is a practice-based and research unit within Emergency Medicine. CCHI staff are involved in several different grants and oversee the continuing development and maintenance of the North Carolina Disease Event Tracking and Epidemiologic Collection Tool (NC DETECT) in collaboration with the NC Division of Public Health.

NC DETECT

NC DETECT provides statewide early event detection, situational awareness and timely public health surveillance to local, regional and state public health practitioners as well as hospital-based users.  Anna Waller, ScD is the Principal Investigator of NC DETECT at CCHI.  CCHI oversees the following aspects of NC DETECT:

• Receipt and processing of all data sources
• NC DETECT database administration
• Design, development and maintenance of the NC DETECT Web Application.  End users drive the development of NC DETECT and CCHI staff works closely with users at all levels to solicit feedback and develop ideas for enhancements to the Web application.  Since the initial launch of the Java-based tool in August 2006, there have been approximately 40 additional releases.

PERRC Research Project #2: Public Health Surveillance Systems Research

Dr. Anna Waller is co-PI along with Dr. Pia MacDonald, Director of the NC Center for Public Health Preparedness, on a CDC-funded cooperative agreement.  The project will systematically assess the strengths, weaknesses and areas for improvement of NC DETECT and the North Carolina Electronic Disease Surveillance System (NC EDSS), including research on each system to examine system capacity, processes, outputs and outcomes. Emphasis will be on assessment of user needs for surveillance, the  characteristics of early and late adopters of electronic  to surveillance systems, and the connections of NC DETECT with NC EDSS and with other preparedness activities in NC. The results of these investigations will yield recommendations for interventions to ensure the utility, use and sustainability of these systems; these recommendations will be disseminated and implemented with the assistance of key partnering practitioners.  Finally, the research team will measure the effectiveness of the implemented interventions. 

Gillings Innovation Lab (GIL)

CCHI staff are participants in a new Gillings Innovation Lab focusing on the integration and use of existing healthcare data to provide a better understanding of the distribution of diseases and their causes.  David Richardson, PhD, Assistant Professor of Epidemiology in the UNC Gillings School of Global Public Health, is the PI for this study.

BioSense-funded Research Project on Syndrome Definitions

This study comprises a collaboration between the Research Triangle Institute and CCHI to conduct research in support of the CDC BioSense Initiative. 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, test, validate, and standardize methodology for optimizing syndrome definitions designed for the early detection of disease outbreaks of public health importance using emergency department data from the North Carolina Disease Event Tracking and Epidemiologic Collection Tool (NC DETECT). 

BioSense Evaluation Cooperative Agreement

This study comprises a collaboration between the Research Triangle Institute and CCHI to conduct biosurveillance evaluations in support of the CDC BioSense Initiative.  RTI is conducting case studies at several different sites around the US to describe the operational components and functioning of a public health system’s response to a public health threat, and to assess the impact of biosurveillance on the timeliness of detection and response and its role within the public health system.  CCHI's role in this cooperative agreement is to assess the quality of the data obtained through a biosurveillance system, by conducting data validity audits.  These audits compare data in source systems to the data found in biosurveillance systems.