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Silva Julio

Description

Adoption of electronic medical records is on the rise, due to the Health Information Technology for Economic and Clinical Health Act and meaningful use incentives. Simultaneously, numerous HIE initiatives provide data sharing flexibility to streamline clinical care. Due to the consolidated data availability in centralized HIE models, conducting syndromic surveillance using locally developed systems, such as GUARDIAN, is becoming feasible. During the past year, Chicago has embarked on a city-wide HIE deployment campaign. Perhaps the most unique aspect of this endeavor is that the data warehouse for the HIE is intricately tied to the GUARDIAN syndromic surveillance system.

Objective

The objective is to describe the technical process, challenges, and lessons learned in scaling up from a local to regional syndromic surveillance system using the MetroChicago Health Information Exchange (HIE) and Geographic Utilization of Artificial Intelligence in Real-Time for Disease Identification and Alert Notification (GUARDIAN) collaborative initiative.

Submitted by elamb on
Description

The Centers for Disease Control and Prevention case definition of influenza-like illness (ILI) as fever with cough and/or sore throat casts a wide net resulting in lower sensitivity which can have major implications on public health surveillance and response.

 

Objective

This study investigates additional signs and symptoms to further enhance the ILI case definition for real-time surveillance of influenza.

Submitted by elamb on
Description

Detection of biological threat agents (BTAs) is critical to the rapid initiation of treatment, infection control measures, and public health emergency response plans. Due to the rarity of BTAs, standard methodology for developing syndrome definitions and measuring their validity is lacking.

 

Objective

The objective of this study is to outline and demonstrate the robust methodology used by Geographic Utilization of Artificial Intelligence in Real-Time for Disease Identification and Alert Notification surveillance system to generate and validate BTA profiles.

Submitted by elamb on
Description

Real-time disease surveillance is critical for early detection of the covert release of a biological threat agent (BTA). Numerous software applications have been developed to detect emerging disease clusters resulting from either naturally occurring phenomena or from occult acts of bioterrorism. However, these do not focus adequately on the diagnosis of BTA infection in proportion to the potential risk to public health.

GUARDIAN is a real-time, scalable, extensible, automated, knowledge-based BTA detection and diagnosis system. GUARDIAN conducts real-time analysis of multiple pre-diagnostic parameters from records already being collected within an emergency department. The goal of this system is to move from simple trend anomaly detection to an infectious disease specific expert system in order to assist clinicians in detecting potential BTAs as quickly and effectively as possible. GUARDIAN improves the diagnostic process for BTA infection through the capture and automated application of associated clinical expertise. The automated application of this knowledge provides the focus and accuracy necessary for effective BTA infection diagnosis. The continuity of this process improves the efficiency by which diagnoses of BTA infections can be made.

Submitted by elamb on
Description

Real-time disease surveillance is critical for early detection of the covert release of a biological threat agent (BTA). Numerous software applications have been developed to detect emerging disease clusters resulting from either naturally occurring phenomena or from occult acts of bioterrorism. However, these do not focus adequately on the diagnosis of BTA infection in proportion to the potential risk to public health.

GUARDIAN is a real-time, scalable, extensible, automated, knowledge-based BTA detection and diagnosis system.  GUARDIAN conducts real-time analysis of multiple pre-diagnostic parameters from records already being collected within an emergency department (ED).  The goal of this system is to assist clinicians in detecting potential BTAs as quickly and effectively as possible in order to better respond to and mitigate the effects of a large-scale outbreak.  

GUARDIAN improves the diagnostic process by moving away from simple trend anomaly detection and towards the development of a BTA-specific infectious disease expert system [1].  Through the capture and automated application of specific clinical expertise, GUARDIAN provides the focus and accuracy necessary for effective BTA infection diagnosis.  The continuity of this process improves the efficiency by which diagnoses of BTA infections can be made.

 

Submitted by elamb on
Description

Early detection of rarely occurring but potentially harmful diseases such as bio-threat agents (e.g., anthrax), chemical agents (e.g., sarin), and naturally occurring diseases (e.g., meningitis) is critical for rapid initiation of treatment, infection control measures, and emergency response plans. To facilitate clinicians’ ability to detect these diseases, various syndrome definitions have been developed. Due to the rarity of these diseases, standard statistical methodologies for validating syndrome definitions are not applicable.

 

Objective

To develop and test a novel syndrome definition validation approach for rarely occurring diseases.

Submitted by teresa.hamby@d… on
Description

Special event driven syndromic surveillance is often initiated by public health departments with limited time for development of an automated surveillance framework, which can result in heavy reliance on frontline care providers and potentially miss early signs of emerging trends. To address timelines and reliability issues, automated surveillance system are required.

Objective

To develop and implement a framework for special event surveillance using GUARDIAN, as well as document lessons learned postevent regarding design challenges and usability.



 

Submitted by Magou on