Surveillance Systems

The Louisiana Office of Public Health conducts ED syndromic surveillance using the Louisiana Early Event Detection System (LEEDS). Using outpatient data for syndromic surveillance is a relatively new concept, brought about due to the increasing use of EHRs and HIEs making such data readily available. Previously, there has been limited means of syndrome classification validation for the LEEDS data and the GNOHIE data has not been studied widely as a population sample, so this analysis and comparison is valuable on both fronts. Due to differences in the types of data (ADT messages from EDs and CCD from outpatient clinics), as well as different patient populations and site visit capability, the percentages of patients classified as ILI between data sets are unequal. The main focus of this analysis is determining whether the ILI classifiers applied to both data sets detect similar syndrome trends.

Each indicator used in the study represents the percentage of total patients seen that week who are classified as ILI cases. The study period covered the 13-14 influenza season, CDC week 1340 through 1420 (9/29/2013-5/17/2014). Two ILI classifiers were applied to both the GNOHIE and LEEDS data:the first classifier consisted of ICD-9 influenza codes and the second classifier consisted of keywords applied to encounter notes(GNOHIE data) and chief complaint, admit reason and diagnoses (LEEDS data). A graph of the data, below, shows the four data sets.

Objective

The goal of this analysis is to compare the results of influenza-like illness (ILI) text and International Classification of Diseases (ICD) code classifiers applied to the Louisiana Office of Public Health’s (OPH) syndromic surveillance data reported by New Orleans area emergency departments and the Greater New Orleans Health Information Exchange’s (GNOHIE) data reported by New Orleans area outpatient clinics.

UIs are among the leading causes of injury in children younger than 5 years in NYC. About 3000 calls are received each year by the NYC Poison Control Center (PCC) for this age group. Common UI exposures include medications, cosmetics, household cleaners, foreign bodies, and pesticides. We examined UIs in NYC from January 2010 to July 2014 for children <5 years to investigate the utility of syndromic surveillance in conjunction with the PCC in capturing real-time pediatric UIs over time.

Objective

To describe unintentional ingestions (UIs) in children <5 years using syndromic data from emergency departments in New York City (NYC) from 2010 to 2014.

Utilization and overcrowding of EDs has been a prominent component of the health care reform debate in the United States for the last several years. In Virginia, the ED utilization rate has increased 27.5% between 2000 and 2012 from 34.5 visits to 44.0 visits per 100 persons. Individuals with high frequency utilization of EDs account for a disproportionate number of visits, which can place burden on already strained health care resources. This study aims to use existing syndromic surveillance data received electronically by the Virginia Department of Health (VDH) to describe demographic and utilization characteristics among chronic high frequency ED users in order to better understand the health complaints affecting this population.

Objective

Leverage existing syndromic surveillance data to characterize the population of chronic high frequency emergency department (ED) users and to understand the health complaints for which this population utilizes emergent health care services.

Over several months in 2012, NYC DOHMH syndromic surveillance staff met with directors of all 49 participating EDs in our syndromic system to collect information on their health information systems coding practices. During these interviews, ED directors expressed interest in receiving summary reports of the data they send to the syndromic unit, such as number of ED visits, most common complaints, and temporal and spatial trends. This effort was done to increase communication and cooperation between the syndromic unit and the EDs that provide data to the syndromic system.

Objective

To share monthly summary reports of syndromic data to participating EDs in NYC.

Previous studies have demonstrated the benefit of laboratory surveillance and its capability to accurately detect influenza outbreaks earlier than syndromic surveillance. Current laboratory surveillance has an approximate 2-week lag due to laboratory test turn–around time and data collection. In order to provide real-time access to aggregated test results, we utilized direct cloud connectivity with a rapid PCR-based influenza test, Xpert Flu, to centrally consolidate test results along with GIS data. On-site, type-specific results were available to physicians and uploaded for public health awareness within 100 minutes of patient nasopharyngeal swab.

Objective

To demonstrate the feasibility and validity of a novel electronic surveillance system utilizing a cloud-based interface that consolidates laboratory test results and geographical information in real-time.

This work builds on a successful demonstration project and expands its data linkage capacity to new community partners. Presently, a national non-fatal injury reporting system does not exist for the Fire Service. In order to tell the story of all injuries within a fire department, state, or on a national scale, we must utilize data that are available from multiple sources that do not naturally talk to each other. In this panel, we will describe the purpose of the project, its goals, and the success of its model to public health surveillance.

Objective

The purpose of this panel is to describe the process of using data to develop firefighter nonfatal injury surveillance systems in the city of Philadelphia and the state of Florida through the linkage of data from workers’ compensation, inpatient and emergency department hospitalizations, human resources, and continuing education/training registries.

Disease surveillance particularly surveillance for communicable diseases is essential in identifying cases and preventing the occurrence of an outbreak. Surveillance can also contribute to reducing the size of an outbreak. In order to achieve these, surveillance activities must include all possible sites for case detection. The lack of established mechanisms to provide feedback to the surveillance system at all such points can cause a failure of the surveillance system. These are extremely relevant particularly in the current outbreak of Ebola in some parts of the West African Sub Region. Ghana, like many countries has established surveillance systems for specific diseases. Currently, 44 diseases/public health events including Ebola are under surveillance as part of an Integrated Disease Surveillance and Response (IDSR) system. Although the Ministry of Health (MOH) exercises authority over issues of health, the operation of policies and practices on disease surveillance is by the Ghana Health Service (GHS), an agency of the MOH despite the existence of other agencies such as the teaching hospitals.

Objective

To describe Ghana’s disease surveillance system operation and the potential challenges in the light of the Ebola outbreak in West Africa

Epidemiological surveillance is used to monitor time trends in diseases and the distribution of the diseases in the population. To streamline the process of identifying outbreaks, and notification of disease, syndromic surveillance has emerged as a method to report and analyze health data. Rather than report data by disease status (ie disease/no disease), clinical symptoms are used to detect outbreaks as early as possible. 

Currently, only data collected via active surveillance (notifiable disease investigations) are usable for identifying communities that require attention. Therefore, any interventions performed using said data is reactive in nature. Syndromic surveillance systems must be disaggregated to enable proactive health promotion, and responses.

Furthermore, a common method must be established to assess the overall impact of syndromes. Diseases are not equal; some have a greater impact on health, and life. To address this issue, the World Health Organization (WHO) has created disability weights to be used in calculating disability adjusted life years (DALY). DALYs are effective in calculating the overall impact of disease in a community. DALYs estimate the burden of disease, not syndromes; therefore, it is reactive tool. To create a more effective syndromic surveillance system, syndromes must be associated with an overall impact weight.

Objective

The justification for address based syndromic surveillance systems, and building syndrome weighting mechanisms.

The 2012 National Strategy for Biosurveillance1 calls for improved integration, synchronization, and coordination of national biosurveillance activities and acknowledges the benefits of collective knowledge through sharing and receiving of biosurveillance information via strengthened partnerships amongst international, federal, state, local, tribal, territorial, private sector, nongovernmental, academic and other participants. To assist in meeting these goals and goals specifically called out by United States (U.S.) Military and international partners, the Joint Program Executive Office for Chemical and Biological Defense began developing a software suite to support biosurveillance needs. In October 2014, the Biosurveillance Portal (BSP) will be deployed to support biosurveillance operations in the Korean Theater. In October 2016, the BSP will be available globally

Objective

This presentation aims to describe the development, initial use, and future directions of the Biosurveillance Portal.

Within the UK, previous syndromic surveillance studies have used statistical estimation to describe the activity of respiratory pathogens. The Emergency Department Syndromic Surveillance System (EDSSS) was initially developed in preparation of the London 2012 Olympic and Paralympic Games and has continued as a standard surveillance system, with expanding coverage across England and Northern Ireland. All reporting to this system is completely passive, with no extra work required within the ED. The data collection includes the diagnosis for each attendance, where available, using the coding system in use locally. The coding varies by ED with ICD- 10, Snomed-CT and the less detailed NHS Accident and Emergency Diagnosis Tables all in use. The use of diagnosis coding systems with differing levels of detail creates the need to have a variety of syndromic indicators to make best use of the data received.

We aim to describe the trends in respiratory attendances, and their comparison to the known circulating pathogens identified though laboratory surveillance to establish if any single syndromic indicator may be attributed to any one pathogen in particular. We also aim to describe the flexibility in the development of EDSSS syndromic indicators to best fit the data received.

Objective

Can syndromic surveillance using standard emergency department data collected using automated daily extraction be used to describe and alert the onset of the seasonal activity of named respiratory pathogens within the community?