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Burkom Howard

Description

Data streams related to case severity have been added to the Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE), a disease-monitoring application used by the Department of Defense (DoD), as an additional analytic capability to alert the user when indications for events requiring expanded medical resources exist in clinical data streams. Commonly used indicators are admission and death, but fatalities are rare and many DoD clinics lack admitting capability, so we sought to derive additional severity indicators from outpatient records. This abstract describes the technical details and the thought process behind two novel derived indicators: Sick-in-Quarters (SIQ) and Escalating Care.

Objective

To evaluate new severity indicators that mimic a public health professional or clinician's judgment in determining the severity of a public health event when detected by a surveillance system.

Submitted by elamb on
Description

The International Society for Disease Surveillance (ISDS) community comprises a large pool of global expertise. Essential to the ISDS mission of advancing the science and practice of disease surveillance is understanding and setting priorities for research and best practices in public health monitoring. To this end, an ISDS workgroup developed an online survey to identify and prioritize the technical and policy issues of the ISDS community. Through analysis, the Survey will identify respondents' perceptions of opportunities in the area of analytical methodologies.

Objective

The objective of the '2013 Biosurveillance Technical Opportunity Prioritization Survey' (Survey) is to gather input from the ISDS community on the current landscape and prioritization of data sources and analytical issues in the field of biosurveillance.

Submitted by elamb on
Description

The Veterans Health Administration (VHA) uses the Electronic Surveillance System for the Early Notification of Community-based Epidemics to detect disease outbreaks and other health-related events earlier than other forms of surveillance. Although Veterans may use any VHA facility in the world, the strongest predictor of which health care facility is accessed is geographic proximity to the patient's residence. A number of outbreaks have occurred in the Veteran population when geographically separate groups convened in a single location for professional or social events. One classic example was the initial Legionnaire's disease outbreak, identified among participants at the Legionnaire's convention in Philadelphia in the late 1970s. Numerous events involving travel by large Veteran (and employee) populations are scheduled each year.

 

Objective

To develop an algorithm to identify disease outbreaks by detecting aberrantly large proportions of patient residential ZIP codes outside a health care facility catchment area.

Submitted by elamb on
Description

An expanded ambulatory health record, the Comprehensive Ambulatory Patient Encounter Record (CAPER) will provide multiple types of data for use in DoD ESSENCE. A new type of data not previously available is the Reason for Visit (ROV), a free-text field analogous to the Chief Complaint (CC). Intake personnel ask patients why they have come to the clinic and record their responses. Traditionally, the text should reflect the patient's actual statement. In reality the staff often "translates" the statement and adds jargon. Text parsing maps key words or phrases to specific syndromes. Challenges exist given the vagaries of the English language and local idiomatic usage. Still, CC analysis by text parsing has been successful in civilian settings [1]. However, it was necessary to modify the parsing to reflect the characteristics of CAPER data and of the covered population. For example, consider the Shock/Coma syndrome. Loss of consciousness is relatively common in military settings due to prolonged standing, exertion in hot weather with dehydration, etc., whereas the main concern is shock/coma due to infectious causes. To reduce false positive mappings the parser now excludes terms such as syncope, fainting, electric shock, road march, parade formation, immunization, blood draw, diabetes, hypoglycemic, etc.

Objective

Rather than rely on diagnostic codes as the core data source for alert detection, this project sought to develop a Chief Complaint (CC) text parser to use in the U.S. Department of Defense (DoD) version of the Electronic Surveillance System for Early Notification of Community-Based Epidemics (ESSENCE), thereby providing an alternate evidence source. A secondary objective was to compare the diagnostic and CC data sources for complementarity.

Submitted by elamb on
Description

In May of 2001, Boston released a strategic transportation plan to improve bicycle access and safety. [1] According to the Boston Transportation Department, ridership has increased 122% between 2007 and 2009. [2] A collaborative public health and public safety task force was initiated in 2010 to foster a safe and healthy bicycling environment.

Objective

To quantify the injury burden and identify possible risk factors using bicycle related injury (BRI) visits at Boston emergency departments (ED).

Submitted by elamb on
Description

Block 3 of the US Military Electronic Surveillance System for Early Notification of Community-Based Epidemics (ESSENCE) system affords routine access to multiple sources of data. These include administrative clinical encounter records in the Comprehensive Ambulatory Patient Encounter Record (CAPER), records of filled prescription orders in the Pharmacy Data Transaction Service, developed at the Department of Defense (DoD) Pharmacoeconomic Center, Laboratory test orders and results in HL7 format, and others. CAPER records include a free-text Reason for Visit field, analogous to chief complaint text in civilian records, and entered by screening personnel rather than the treating healthcare provider. Other CAPER data fields are related to case severity. DoD ESSENCE treats the multiple, recently available data sources separately, requiring users to integrate algorithm results from the various evidence types themselves. This project used a Bayes Network approach to create an ESSENCE module for analytic integration, combining medical expertise with analysis of 4 years of data using documented outbreaks.

 

Objective

The project objective was to develop and test a decision support module using the multiple data sources available in the U.S. DoD version of ESSENCE.

Submitted by elamb on
Description

In development for over fourteen years, ESSENCE is a disease surveillance system utilized by public health stakeholders at city, county, state, regional, national, and global levels. The system was developed by a team from the Johns Hopkins University Applied Physics Laboratory (JHU/APL) with substantial collaborations with the US Department of Defense Global Emerging Infections Surveillance and Response System (DoD GEIS), US Department of Veterans Affairs (VA), and numerous public health departments. This team encompassed a broad range of individuals with backgrounds in epidemiology, mathematics, computer science, statistics, engineering and medicine with significant and constant influence from many public health collaborators.

Objective

This talk will describe the history and events that influenced the design and architecture decisions of the Electronic Surveillance System for Community-based Epidemics (ESSENCE)(1). Additionally, it will discuss the current functionality and capabilities of ESSENCE and the future goals and planned enhancements of the system.

Referenced File
Submitted by elamb on
Description

Syndromic surveillance systems were designed for early outbreak and bioterrorism event detection. As practical experience shaped development and implementation, these systems became more broadly used for general surveillance and situational awareness, notably influenza-like illness (ILI) monitoring. Beginning in 2006, ISDS engaged partners from state and local health departments to build Distribute, a distributed surveillance network for sharing de-identified aggregate emergency department syndromic surveillance data through existing state and local public health systems. To provide more meaningful cross-jurisdictional comparisons and to allow valid aggregation of syndromic data at the national level, a pilot study was conducted to assess implementation of a common ILI syndrome definition across Distribute.

 

Objective

Assess the feasibility and utility of adopting a common ILI syndrome across participating jurisdictions in the ISDS Distribute project.

Submitted by elamb on
Description

Time-of-arrival (TOA) surveillance methodology consists of identifying clusters of patients arriving to a hospital emergency department (ED) with similar complaints within a short temporal interval. TOA monitoring of ED visit data is currently conducted by the Florida Department of Health at the county level for multiple subsyndromes [1]. In 2011, North Carolina's NC DETECT system and CDC's Biosense Program collaborated to enhance and adapt this capability for 10 hospital-based Public Health Epidemiologists (PHEs), an ED-based monitoring group established in 2003, for North Carolina's largest hospital systems. At the present time, PHE hospital systems include coverage for approximately 44% of the statewide general/acute care hospital beds and 32% of all emergency department visits statewide. We present findings from TOA monitoring in one hospital system.

Objective

To describe collaborations between North Carolina Division of Public Health and the Centers for Disease Control and Prevention (CDC) implementing time-of-arrival (TOA) surveillance to monitor for exposure-related visits to emergency departments (ED) in small groups of North Carolina hospitals.

Submitted by elamb on
Description

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.

Submitted by elamb on