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Barnett Clifton

NC DETECT is the Web-based early event detection and timely public health surveillance system in the North Carolina Public Health Information Network. The reporting system also provides broader public health surveillance reports for emergency department visits related to hurricanes, injuries, asthma,  vaccine-preventable diseases, environmental health and others. NC DETECT receives data on at least a daily basis from four data sources: emergency departments, the statewide poison center, the statewide EMS data collection system, a regional wildlife center and laboratory data from the NC State College of Veterinary Medicine. Data from select urgent care centers are in pilot testing.

 

Objective

Managers of the NC DETECT surveillance system wanted to augment standard tabular Web-based access with a Web-based spatial-temporal interface to allow users to see spatial and temporal characteristics of the surveillance data. Users need to see spatial and temporal patterns in the data to help make decisions about events that require further investigation. The innovative solution using Adobe Flash and Web services to integrate the mapping component with the backend database will be described in this paper.

Referenced File
Submitted by elamb on

States and localities are using biosurveillance for a variety purposes including event detection, situational awareness, and response. However, little is known about the impact of biosurveillance on the operational components and functioning of the public health system and the added value of biosurveillance to traditional surveillance methods. A deeper understanding of how state and local public health systems use biosurveillance data and the factors that facilitate and impede its utility are needed to inform efforts to improve public health surveillance.

 

Objectives

A goal of the case studies was to assess the impact of biosurveillance on public health system preparedness, detection and response for a range of public health threats.

Referenced File
Submitted by elamb on

While early event detection systems aim to detect disease outbreaks before traditional means, following up on the many alerts generated by these systems can be time-consuming and a drain on limited resources.

Authorized users at local, regional and state levels in North Carolina rely on the North Carolina Disease Event Tracking and Epidemiologic Collection Tool's (NC DETECT) Java-based Web application to monitor and follow-up on signals based on the CDC’s EARS CUSUM algorithms. The application provides users with access to aggregate syndrome-based reports as well as to patient-specific line listing reports for three data sources: emergency departments, ambulance runs and the statewide poison control center. All NC DETECT Web functionality is developed in a user-centered, iterative process with user feedback guiding enhancements and new development. This feedback, along with the need for improved situational awareness and the desire to improve communication among users drove the development of the Annotation Reports and the Custom Event Report.

 

Objective

We describe the addition of two reports to NC DETECT designed to improve NC public health situational awareness capability.

Referenced File
Submitted by elamb on

The North Carolina Disease Event Tracking and Epidemiologic Collection Tool (NC DETECT) is the early event detection system that serves public health users across North Carolina. One important data source for this system is North Carolina emergency department visits. ED data from hospitals across the state are downloaded, standardized, aggregated, and updated twice daily.

After hurricane Katrina devastated the Gulf Coast on August 29, 2005, federal officials evacuated two large groups of evacuees into Wake and Mecklenburg counties in North Carolina. In order to identify and monitor the hospital-based public health needs of these and other “unofficial” evacuees, NC state officials used both NC DETECT and hospital-based Public Health Epidemiologist reporting methods, along with other public health surveillance initiatives.

Objective

To compare two different methods of monitoring hurricane Katrina evacuees’ hospital visits in North Carolina.

Referenced File
Submitted by elamb on

The North Carolina Disease Event Tracking and Epidemiologic Collection Tool (NC DETECT) receives a designated set of data elements electronically available from 110 emergency departments (EDs) (98%) on at least a daily basis via a third party data aggregator. While automated processes monitor for data quality problems such as improper file formats or missing required elements, data corruption can occur at several stages before receipt, and if undetected, data can appear reliable. Hospitals might map to standard codes incorrectly, data aggregators might manipulate text improperly, or updates might be confused with original records. These inaccuracies cause delays and oversights in identifying events of public health importance.

 

Objective

This study evaluates the validity of a subset of ED data collected in NC DETECT, as well as measures the effectiveness of the data quality processes in place for this surveillance system.

Referenced File
Submitted by elamb on

Data quality for syndromic surveillance extends beyond validating and evaluating syndrome results. Data aggregators and data providers can take additional steps to monitor and ensure the accuracy of the data. In North Carolina, hospitals are mandated to transmit electronic emergency department data to the North Carolina Disease Event Tracking and Epidemiologic Tool (NC DETECT) system at least every 24 hours. Protocols have been established to ensure the highest level of data quality possible. These protocols involve multiple levels of data validity and reliability checks by NC DETECT staff as well as feedback from end-users concerning data quality. Hospitals also participate in the data quality processes by providing metadata including historical trends at each facility.

 

Objective

The purpose of this project is to describe the initiatives used by the NC DETECT to ensure the quality of ED data for surveillance.

Referenced File
Submitted by elamb on

Per a frequently asked questions document on the ISDS website, approximately two thirds of HL7 records received in BioSense do not provide a Visit ID. As a result, BioSense data processing rules use the patient ID, facility ID and earliest date in the record to identify a unique visit. If the earliest dates in records with the same patient ID and facility ID occur within the same 24-hour time frame, those two visits are combined into one visit and the earliest date will be stored. The ED data sent by hospitals to NC DETECT include unique visit IDs and these are used to identify unique visits in NC DETECT. These data are also sent twice daily to BioSense. In order to assess the potential differences between the NC DETECT ED data in NC DETECT and the NC DETECT ED data in BioSense, an initial analysis of the 24-hour rule was performed.

Objective

NC DETECT emergency department (ED) data were analyzed to assess the impact of applying the BioSense “24-hour rule” that combines ED visits into a single visit if the patient ID and facility ID are the same and the earliest recorded dates occur within the same 24-hour time frame.

Submitted by teresa.hamby@d… on

In 2012, an estimated 2.5 million people presented to the ED for a MVC injury in the U.S. National injury surveillance is commonly captured using E-codes. However, use of E-codes alone to capture MVC-related ED visits may result in a different picture of MVC injuries compared to using text searches of triage or chief compliant notes.

Objective

Identify and describe how the case definition used to identify MVC patients can impact results when conducting MVC surveillance using ED data. We compare MVC patients identified using external cause of injury codes (E-codes), text searches of triage notes and chief complaint, or both criteria together.

Submitted by teresa.hamby@d… on

Recreational drug use is a major problem in the United States and around the world. Specifically, drug abuse results in heavy use of emergency department (ED) services, and is a high financial burden to society and to the hospitals due to chronic ill health and multiple injection drug use complications. Intravenous drug users are at high risk of developing sepsis and endocarditis due to the use of a dirty or infected needle that is either shared with someone else or re-used. It can also occur when a drug user repeatedly injects into an inflamed and infected site or due to the poor overall health of an injection drug user. The average cost of hospitalization for aortic valve replacement in USA is about $165,000, and in order for the valve replacement to be successful, patients must abstain from using drugs.

Objective

To describe how the state syndromic surveillance system (NC DETECT) was used to initiate near real time surveillance for endocarditis, sepsis and skin infection among drug users.

Submitted by Magou on
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