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Talbot James

Description

In November of 2011, the local Public Health unit responsible for the Edmonton area (population 1.2mil) was alerted to an individual meeting the case definition for measles in the ED. A key part of the management strategy was to identify contacts to the index case, perform a risk assessment and, if applicable, inform them of the risk. Given the transmission characteristics, the risk for this group was defined as those present within the geographic area/environment of the index case within a specified time period. Public Health utilized the established manual lookup of hospital records and piloted an automated data query through the syndromic surveillance system, ARTSSN. This served as opportunity to validate the ability to generate a contact list, based on risk geography and time, of the ARTSSN system, and to compare the timeliness of each result.

Objective

Following a clinical case of measles presenting to an urban emergency department (ED), the local health authority sought to identify all patients that might be at risk for disease. This list of contacts was generated through a manual search of hospital records and through a piloted automated data query of the health authority's syndromic surveillance system, Alberta Real Time Syndromic Surveillance Net (ARTSSN). The purpose of this pilot study was to: 1) compare the completeness of the two lookup methods and, 2) describe the time requirements needed for each method.

Submitted by elamb on
Description

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.

Submitted by elamb on
Description

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.

Submitted by elamb on
Description

Screening for Influenza Like Illness (ILI) is an important infection control activity within emergency departments (ED). When ILI screening is routinely completed in the ED it becomes clinically useful in isolating potentially infectious persons and protecting others from exposure to disease. When routinely collected, ILI screening in an electronic clinical application, with real time reporting, can be useful in Public Health surveillance activities and can support resource allocation decisions e.g. increasing decontamination cleaning. However, the reliability of documentation is unproven. Efforts to support the adoption of ILI screening documentation in a computer application, without mandatory field support, can lead to long term success and increased adherence.

 

Submitted by uysz on
Description

Standardized electronic pre-diagnostic information is routinely collected in Alberta, Canada. ARTSSN is an automated real-time surveillance data repository able to rapidly refresh data that include school absenteeism information, calls about health concerns from Health Link Alberta; a provincial telephone service for health advice and information, and emergency department visits categorized by standardized chief complaint. Until recently, real-time ARTSSN data for public health surveillance and decision making has been underutilized.

Objective

We developed early warning algorithms using data from ARTSSN and used them to detect signatures of potential pandemics and provide regular weekly forecasts on influenza trends in Alberta during 2012-2014.

Submitted by rmathes on