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Lee Chris

The VA has employed ESSENCE for health monitoring since 2006 [1]. Epidemiologists at the Office of Public Health (OPH) monitor the VA population at the national level. The system is also intended for facility-level monitoring to cover 152 medical centers, nearly 800 community-based outpatient clinics (CBOC), and other facilities serving all fifty states, the District of Columbia, and U.S. territories. For the entire set of facilities and current syndrome groupings, investigation of the full set of algorithmic alerts is impractical for the group of monitors using ESSENCE. Signals of interest may be masked by the nationwide alert burden. Customized querying features have been added to ESSENCE, but standardization and IP training are required to assure appropriate use.

Objective

The objective was to adapt and tailor the alerting methodology employed in the Electronic Surveillance System for Early Notification of Community-Based Epidemics (ESSENCE) used by Veterans Affairs (VA) for routine, efficient health surveillance by a small, VA headquarter medical epidemiology staff in addition to a nationwide group of infection preventionists (IPs) monitoring single facilities or facility groups.

Referenced File
Submitted by elamb on

The National Strategy for Biosurveillance promotes a national effort to improve early detection and enable ongoing situational awareness of all-hazards threats. Implicit in the Strategy’s implementation plan is the need to upgrade capabilities and integrate multiple disparate data sources, including more complete electronic health record (EHR) data into future biosurveillance capabilities. Thus, new biosurveillance applications are clearly needed. Praedico™ is a next generation biosurveillance application that incorporates cloud computing technology, a Big Data platform utilizing MongoDB as a data management system, machine-learning algorithms, geospatial and advanced graphical tools, multiple EHR domains, and customizable social media streaming from public health-related sources, all within a user friendly interface.

Objective

The purpose of our study was to conduct an initial assessment of the biosurveillance capabilities of a new software application called Praedico™ and compare results obtained from previous queries with the Electronic Surveillance System for the Early Notification of Community-Based Epidemics (ESSENCE).

 

Submitted by Magou on

Many methods to detect outbreaks currently exist, although most are ineffective in the face of real data, resulting in high false positivity. More complicated methods have better precision, but can be difficult to interpret and justify. Praedico™ is a next generation biosurveillance application built on top of a Hadoop High Performance Cluster that incorporates multiple syndromic surveillance methods of alerting, and a machine-learning (ML) model using a decision tree classifier  evaluating over 100 different signals simultaneously, within a user friendly interface.

Objective

To compare syndromic surveillance alerting in VA using Praedico™ and ESSENCE.

Submitted by teresa.hamby@d… on
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