ESSENCE

By mid-May 2008, the State of Florida had 102 active wildfires affecting approximately 40,000 acres. In addition, the Mustang Corners Fire in Everglades National Park started on May 14 and burned throughout the month affecting another 40,000 acres of federal land. Smoke from several wildfires cast a haze over parts of south Florida, prompting the National Weather Service to issue a dense smoke advisory. The Governor declared a State of Emergency, the EOC was activated and ESF-8 requested that the Agency for Health Care Administration open a wildfire event in the Emergency Status System to track census and bed availability in the local hospitals.

Objective

We used the syndromic surveillance system ESSENCE (Electronic Surveillance System for the Early Notification of Community-based Epidemics) to evaluate emergency room visits with respiratory related chief complaints in an area with decreased air quality associated with wildfires affecting South Florida, 2008.

The use of R is increasing in the public health disease surveillance community. The ISDS pre-conference workshops and newly formed R Group for Surveillance have been well attended and continue to grow in popularity. The use of R in the National Syndromic Surveillance Program (NSSP) has also been of value to many users who wish to analyze and visualize public health data using custom R scripts. This interest in R, combined with a desire from many ESSENCE users to create custom analytics and visualizations, led to a summer internship project to look into the feasibility and ways R could be integrated into ESSENCE.

Objective

The objective of this project is to give users the ability to run custom R scripts from within the ESSENCE system. This capability would allow for custom analytics and visualizations to be baked into the system for daily use. It would also provide a sandbox area for new ideas and features to be tested before being developed more fully into the ESSENCE codebase for a more seamless use in the future. The project must do this while maintaining a secure environment for public health data to reside.

VA began using ESSENCE as a public health surveillance tool in 2005. The system offered alerting capability for pre-defined syndromes and querying capability for outpatient ICD-9 diagnosis codes. Herein, we highlight examples of how we have invested in upgrades to analytic capabilities and expanded data sources available to ESSENCE in order to augment the overall utility of this system within VA.

Objective

To describe VA’s experience developing innovative and alternative uses of a surveillance system and improve the overall value proposition of this tool for the agency.

ILINet is used nationwide by sentinel healthcare providers for reporting weekly outpatient visit numbers for influenza-like illness to CDC. The Florida Department of Health receives urgent care center (UCC) data through ESSENCE from participating facilities. Seminole County is unique in that its four sentinel providers located in separate UCCs report into both systems, and all their discharge diagnoses are available through ESSENCE. However, the reported number of patients being discharged from those providers with diagnoses of influenza is not equivalent to the number of cases reported into ILINet. Data from the two systems were therefore compared both among and between the individual sentinel providers in order to determine the extent of the variation over four influenza seasons.

Objective

To compare influenza-like illness (ILI) data reported to the Centers for Disease Control and Prevention (CDC) U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet) with discharge diagnosis data for influenza from the same reporting source obtained through the Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE) in Seminole County, Florida.

Since the largest epidemic of Zaire ebolavirus (EBOV) in recorded history began in Guinea in December 2013, the epidemic has spread to neighboring countries of Liberia and Sierra Leone resulting in an estimation of over 27,000 total cases and over 11,000 deaths to date. In response to the widespread social disruption caused by this epidemic in West Africa, President Obama committed approximately 2,000 US service members to deploy to the region and provide humanitarian aid. US military physicians were called upon to evaluate service members returning from West Africa (WA) to rule out EVD. The US military also has a considerable number of beneficiaries who travel to WA to visit friends and relatives placing them at risk for exposure to EBOV and the development of illness upon returning to the US.

We are conducting an expanded surveillance program that employs a standard questionnaire that all providers can use when evaluating a patient at-risk for EVD that will also capture information from historical encounters. The data collected from the questionnaire will be used to assess the frequency with which clinicians are called to evaluate patients for EVD and the resources required. However, we realize that many encounters may not be captured with this method, especially those that are not high enough risk to require consultation with infectious disease (ID) specialists, and are developing ways to screen the Electronic Health Record (EHR) to find additional patients.

Objective

To present methods of screening chief complaints and laboratory orders to find patients who presented for Ebola Virus Disease (EVD) screening, in order to determine the impact Ebola concern had on the Military Health System (MHS).

Near real-time emergency department chief complaint data is accessed through Florida’s syndromic surveillance system: Electronic Surveillance System for the Early Notification of Communitybased Epidemics-Florida (ESSENCE-FL). The Florida Department of Health relies heavily upon these data for timely surveillance of influenza and influenza-like illness (ILI). Hospital discharge data available from the Florida Agency for Health Care Administration (AHCA) captures information about influenza-associated ED visits and is considered complete. The delay in receiving the data (up to a year) hinders timely evidence-based decision making during the influenza season. Previous analyses (comparing the complete AHCA hospital discharge data to the ESSENCE-FL ILI syndrome and Influenza sub-syndrome) have shown ESSENCE-FL is a timely, effective tool to monitor influenza activity in the state and that the Influenza sub-syndrome most closely approximates influenza season activity in Florida. Adults > 65, pregnant women and children < 5 are at increased risk for morbidity and mortality from influenza infection. This investigation aims to determine if syndromic surveillance can be used to characterize in near real-time influenza infection in adults > 65, pregnant women, and children < 5 by comparing ED visits for influenza and ILI in ESSENCE-FL to historical AHCA records of people who incurred ED charges at a Florida hospital with diagnosed influenza.

Objective

To determine if emergency department (ED) based syndromic surveillance can be utilized to characterize in near real-time influenza infection in three high-risk populations: a) adults > 65, b) pregnant women, and c) children < 5.

Syndromic surveillance refers to the monitoring of disease related events, sets of clinical features (i.e. syndromes), or other indicators in a population. Tennessee obtains emergency department data for syndromic surveillance in standardized HL7 format following the field and value set standards published by the Public Health Information Network. Messages contain information previously unavailable to syndromic surveillance systems, including quantitative values such as recorded temperature. Data are received daily and processed by a Tennessee ESSENCE application and the national BioSense platform.

These systems use chief complaint keywords, ICD9 codes, and other algorithms to assign syndromes for each record. The differences between the BioSense and ESSENCE syndrome assignments have not been well defined. Detailed comparisons of syndrome assignment across tools are difficult to perform due to the intensity of the manual review required. However, definitions of fever can be easily confirmed in HL7 messages when the recorded temperature is provided. Currently, both the BioSense and ESSENCE syndrome definitions exclude recorded temperature from consideration when assigning syndromes.

To compare the performance of the fever syndromes used by BioSense and ESSENCE, recorded temperature data was used as the gold standard.

Objective

To objectively compare the BioSense and ESSENCE fever syndromes using recorded temperature as a gold standard.

There are currently over 25 installations of ESSENCE across the US. Among these, there are 3 instances of multi-jurisdictional implementations. These include a centralized regional system in the National Capital Region for MD, DC, and VA, a Missouri system that includes hospitals and users from the St. Louis area in Illinois, and soon the National Syndrome Surveillance Program (NSSP) version of ESSENCE which will centralize data from many jurisdictions. While each of these systems provides valid ways to share data across jurisdictions, they require data to be sent to another jurisdiction. There are some jurisdictions which have legal or philosophical or technical issues with these types of data sharing arrangements. Programs like Distribute attempted to solve this by only sharing pre-aggregated data. This caused issues though for surveillance of new and emerging issues that requires a more ad-hoc query capability. This gap can be filled with a locally-ran system that has the ability to perform queries into remote systems and perform a federated query across other jurisdictions.

Objective

The objective of this presentation is to describe the new federated query capability in ESSENCE and describe how this could affect public health practice in the future. Specifically, this presentation will describe how a federated set of disease surveillance systems across the country could help improve national disease surveillance situational awareness along with its potential to connect non-ESSENCE systems in the future for even more complete coverage. It will also describe how this capability is different than other data sharing projects that attempt to centralize data, but how there is room for both to benefit from each other.