Real-time Surveillance

Syndromic surveillance systems have long been an important part of the public health arena. The long standing goal of early detection of disease outbreak has gained new urgency and requires a broader spectrum in the era of potential bioterrorism. A number of programs have used syndromic surveillance to broadly monitor community health. Outpatient chief complaints as well as positive laboratory tests have been used to monitor the occurrence of natural diseases. 

Limitations of the systems currently attempted include overbroad syndromic categories, labor intensive syndrome recognition training and time intensive manual data entry. Optimal use of laboratory data has been impeded by some of the same issues as well as a too often narrow focus and significant limitations on real time reporting. Given the likelihood of blunt and/or penetrating trauma being a manifestation of terrorist activity, the continuous inclusion of common traumatic and medical emergency conditions is a valuable tool for surveillance.

Objective

This paper describes the use of a multiple collective community health care database to monitor the occurrence of natural and manmade illness and injuries.

The performance of even the most advanced syndromic surveillance systems can be undermined if the monitored data is delayed before it arrives into the system.  In such cases, an outbreak may be detected only after it is too late for appropriate public health response. Surveillance systems can experience delays in data availability for a number of reasons: The process of transmitting data from data sources to the surveillance system can involve delays, especially in large systems where data is first aggregated across a national network of data sources before being transmitted to the surveillance system. Delays can also arise in the course of care, where, for example, a diagnosis is not available for a few days after the healthcare encounter.  It is important to minimize delays in data availability in order to maintain timeliness of detection [1].  When this is not possible, it is desirable to compensate for these data delays to minimize their effects.

Objective

This paper describes an approach to improving the detection timeliness of real-time health surveillance systems by modeling and correcting for delays in data availability.

Heat surveillance in Houston is currently limited to mortality reports from the medical examiners office. A possible source of heat related morbidity is the Houston Real-time Outbreak Disease Surveillance (RODS) system. The RODS system was put into practice in the Houston Department of Health and Human services (HDHHS) in 2004 and now encompasses 37 hospitals. While initially designed for early detection of bioterrorism events, using syndromic data to detect other medical complaints, such as heat related morbidity, could prove to be beneficial and cost-effective for large cities, such as Houston.

Objective

The purpose of this investigation is to determine the value of using the RODS system to track heat-related morbidity in Houston, Texas.

Rhode Island implemented the Real-time Outbreak and Disease Surveillance (RODS) system, developed in 1999 by the University of Pittsburgh’s Center for Biomedical Informatics. This system is based on real-time information from hospital emergency departments that is transmitted and analyzed electronically for the purpose of early detection of and situational awareness for public health emergencies. Through this system, chief complaint is reported in real-time. Diagnoses, coded in the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM), are reported to the RI RODS system as they become available. Three hospitals are currently participating in a pilot implementation of the RI RODS system.

Preliminary work by a CDC Working Group (CDCWG) developed recommendations for syndrome definitions for use in syndromic surveillance programs. Ten syndromes, based on ICD-9-CM diagnosis codes, identified diseases associated with critical bioterrorism-associated agents or indicative of naturally occurring infectious disease outbreaks. As a component of the evaluation of the RI RODS system, we evaluated the RI RODS chief complaint classifier (CoCo) using ICD-9-CM codes and the CDCWG work as the gold standard.

Objective

This paper presents findings related to the evaluation of the CoCo used in the pilot implementation of a syndromic surveillance system in Rhode Island.

Efforts have been made to standardize and prioritize the description and evaluation of syndromic surveillance systems. Systematic information on the performance of existing systems can be used to assess and compare the value of these systems, and inform decisions regarding their use. 

The Michigan’s Emergency Department Syndromic Surveillance System (MSSS) is an implementation of an early version of the Real-time Outbreak and Disease Surveillance system developed by the University of Pittsburgh, which collects patient chief complaint data from emergent care facilities in real time. At the Michigan Department of Community Health the system has been in use since 2003. Alterations to the system and recruitment of data contributors have been ongoing. The primary stated purpose of the MSSS is earlier detection of outbreaks of severe illness, enabling a more rapid public health response and intervention to reduce the impact of public health threats.

Objective

This work describes key characteristics of MSSS and reports on its evaluation.

Capital Health is a regional health care organization, which provides services for over one million inhabitants in the Edmonton area of Alberta, Canada. Traditionally, disease surveillance under its jurisdiction has been paper-based and records maintained by different departments in several locations. Before the Alberta Real Time Syndromic Surveillance Net (ARTSSN), there was no centralized database or unified approach to surveillance and automated reporting despite rich electronic health data in the region. The existing labor-intensive manual surveillance process is inefficient and inherently susceptible to human error. Its effectiveness is sub-optimal in detecting outbreaks of emerging infectious diseases, and clusters of injuries or toxic exposures. The ultimate objective of ARTSSN is to enhance public health surveillance through earlier and more sensitive detection of clusters and trends, with subsequent tracking and response through an integrated, automated surveillance and reporting system.

Objective

ARTSSN is a pilot public health surveillance project developed for the Capital Health region of Alberta, Canada and funded by Alberta Health and Wellness. This paper describes the advantages of using ARTSSN and comparing information derived from multiple electronic data sources simultaneously for real time syndromic surveillance.

In September 2004, Kingston, Frontenac and Lennox and Addington Public Health began a 2-year pilot project to develop and evaluate an Emergency Department Chief Complaint Syndromic Surveillance System in collaboration with the Ontario Ministry of Health and Long Term Care – Public Health Branch, Queen’s University, Public Health Agency of Canada, Kingston General Hospital and Hotel Dieu Hospital. At this time, the University of Pittsburgh’s Real-time Outbreak and Disease Surveillance (RODS, Version 3.0) was chosen as the surveillance tool best suited for the project and modifications were made to meet Canadian syndromic surveillance requirements.

Objective

This poster provides an overview of a RODS-based syndromic surveillance system as adapted for use at a Public Health unit in Kingston, Ontario Canada. The poster will provide a complete overview of the technical specifications, the capture, classification and management of the data streams, and the response protocols developed to respond to system alerts. It is hoped that the modifications described here, including the addition of unique data streams, will provide a benchmark for Canadian syndromic surveillance systems of the future.

The prompt detection of disease outbreaks is a major concern to public health as it has the potential to reduce morbidity and mortality (1). Real-time syndromic surveillance uses existing non-traditional data for timely analysis and feedback to those responsible for investigations and follow-up of potential outbreaks (2). Recent studies have suggested that integrating multiple data sources can significantly improve detection accuracy of syndromic surveillance systems, but more work is needed to explore the most effective means of said integration and what types of data streams give the greatest benefit (3;4).

Objective:

This paper will examine the temporal relationship between Ontarioís emergency department (ED) visits and telephone health line (Telehealth Ontario) call volume for respiratory illnesses, in an effort to test the feasibility of using Telehealth Ontarioís system for real-time surveillance.

The ability to provide real time syndromic surveillance throughout the Capital Health Region is currently undeveloped. There are limited mechanisms for routine real time surveillance of disease or conditions of public health interest, e.g. communicable diseases, toxic exposure or injury. Toxic exposure and injury while preventable are not notifiable in Alberta and as a consequence there is no real-time surveillance system to identify burden of disease or opportunities for intervention. The notifiable disease system is reliant on paper-based forms which are slow, prone to human error, and labor intensive to convert to electronic database format for flexible analysis and interpretation. Finally there is no system to link the data collected on the same individual in each database without compromising confidentiality. ARTSSN is designed to remedy these deficiencies.

Objective

In this presentation we describe the creation of an IT architecture and infrastructure to integrate data from four sources to support real-time syndromic surveillance for injuries, toxic exposures and notifiable diseases in Capital Health, Alberta, Canada.

This paper describes the synthesis of benefits and problems that French Armed Forces had to take into account for the implementation of syndromic surveillance within their epidemiological surveillance strategy.