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The use of syndromic surveillance systems has evolved over the last decade, and increasingly includes both infectious and non- infectious topic areas. Public health agencies at the national, state, and local levels often need to rapidly develop new syndromic categories, or improve upon existing categories, to enhance their public health surveillance efforts. Documenting this development process can help support increased understanding and user acceptance of syndromic surveillance. This presentation will highlight the visualization process being used by CDC’s National Syndromic Surveillance Program (NSSP) program to develop and refine definitions for syndromes of interest to public health programs.

Objective: To describe the use of uni-grams, bi-grams, and tri-grams relationships in the development of syndromic categories.

Submitted by elamb on

Syndromic surveillance systems, although initially developed in response to bioterrorist threats, are increasingly being used at the local, state, and national level to support early identification of infectious disease and other emerging threats to public health. To facilitate detection, one of the goals of CDC's National Syndromic Surveillance Program (NSSP) is to develop and share new sets of syndrome codes with the syndromic surveillance Community of Practice. Before analysts, epidemiologists, and other practitioners begin customizing queries to meet local needs, especially monitoring ED visits in near-real time during public health emergencies, they need to understand how syndromes are developed. More than 4,000 hospital routinely send data to NSSP's BioSense Platform, representing about 55 percent of ED visits in the United States (2). The platform's surveillance component, ESSENCE,* is a web-based application for analyzing and visualizing prediagnostic hospital ED data. ESSENCE's Chief Complaint Query Validation (CCQV) data source, which is a national-level data source with access to chief complaint (CC) and discharge diagnoses (DD) from reporting sites, was designed for testing new queries.

Objective: Emergency department (ED) visits related to mental health (MH) disorders have increased since 2006 (1), indicating a potential burden on the healthcare delivery system. Surveillance systems has been developed to identify and understand these changing trends in how EDs are used and to characterize populations seeking care. Many state and local health departments are using syndromic surveillance to monitor MH-related ED visits in near real-time. This presentation describes how queries can be created and customized to identify select MH sub-indicators (for adults) by using chief complaint text terms and diagnoses codes. The MH sub-indicators examined are mood and depressive disorders, schizophrenic disorders, and anxiety disorders. Wider adoption of syndromic surveillance for characterizing MH disorders can support long-term planning for healthcare resources and service delivery.

Submitted by elamb on

The CDC's BioSense Program receives near real-time health care utilization data from a number of sources, including Department of Defense (DoD) healthcare facilities from around the globe and non-federal hospital emergency departments (EDs) in the US, to support all-hazards surveillance and situation awareness. Following the tsunami in Japan on March 11, 2011, the BioSense Program modified its surveillance protocols to monitor: 1) injuries and possible radiation-associated health effects in Japan-based DoD facilities and 2) potential adverse health effects associated with the consumption of potassium iodide (KI), a salt used to prevent injury to the thyroid gland in the event of radiation exposure, among persons attending participating EDs in the US. We present the findings from that enhanced surveillance.

Objective

To demonstrate the utility of the BioSense Program for post-disaster response surveillance.

Referenced File
Submitted by elamb on

Understanding the relationship between mental illness and medical comorbidity is an important aspect of public health surveillance. In 2004, an estimated one fourth of the US adults reported having a mental illness in the previous year (1). Studies showed that mental illness exacerbates multiple chronic diseases like cardiovascular diseases, diabetes and asthma (2). BioSense is a national electronic public health surveillance system developed by the Centers for Disease Control and Prevention (CDC) that receives, analyzes and visualizes electronic health data from civilian hospital emergency departments (EDs), outpatient and inpatient facilities, Veteran Administration (VA) and Department of Defense (DoD) healthcare facilities. Although the system is designed for early detection and rapid assessment of all-hazards health events, BioSense can also be used to examine patterns of healthcare utilization.



Objective:

The purpose of this paper was to analyze the associated burden of mental illness and medical comorbidity using BioSense data 20082011.

Submitted by Magou on

Medical claims and EHR data sources offer the potential to ascertain disease and health risk behavior prevalence and incidence, evaluate the use of clinical services, and monitor changes related to public health interventions. Passage of the HITECH Act of 2009 supports the availability of standardized EHR data for use by public health officials to obtain actionable information. While full adoption of EHRs is still years away, there are presently publicly- and commerciallyavailable EHR and medical claims data sets that could enhance public health surveillance at a national, regional and state level. The purposes of this evaluation were to i.) demonstrate the feasibility of gaining access to such data, ii.) evaluate their ability to augment current surveillance activities by developing measures for twenty separate healthcare indicators (e.g., HIV screening), iii.) evaluate each data source across a set of criteria needed for an effective surveillance system, and iv.) assess the ability of the data sources to evaluate changes in healthcare utilization and preventive services that may be a result of the 2009 Health Reform legislation.

Objective:

To assess the utility of inpatient and ambulatory clinical data compiled by public and commercial sources to enhance the Centers for Disease Control and Prevention’s surveillance activities.

 

Submitted by Magou on

Between 2006 and 2013, the rate of emergency department (ED) visits related to mental and substance use disorders increased substantially. This increase was higher for mental disorders visits (55 percent for depression, anxiety or stress reactions and 52 percent for psychoses or bipolar disorders) than for substance use disorders (37 percent) visits. This increasing number of ED visits by patients with mental disorders indicates a growing burden on the health-care delivery system. New methods of surveillance are needed to identify and understand these changing trends in ED utilization and affected underlying populations. Syndromic surveillance can be leveraged to monitor mental health-related ED visits in near real-time. ED syndromic surveillance systems primarily rely on patient chief complaints (CC) to monitor and detect health events. Some studies suggest that the use of ED discharge diagnoses data (Dx), in addition to or instead of CC, may improve sensitivity and specificity of case identification.

Objective: The objectives of this study are to

(1) create a mental health syndrome definition for syndromic surveillance to monitor mental health-related ED visits in near real time;

(2) examine whether CC data alone can accurately detect mental health related ED visits; and

(3) assess the added value of using Dx data to detect mental health-related ED visits.

Submitted by elamb on

The May arrival of two cases of Middle East Respiratory Syndrome (MERS) in the US offered CDC’s BioSense SyS Program an opportunity to give CDC’s Emergency Operations Center (EOC) and state-and-local jurisdictions an enhanced national picture of MERS surveillance. BioSense jurisdictions can directly query raw data stored in what is known as “the locker.” However, CDC cannot access these data and critical functions, like creating ad-hoc syndrome definitions within the application are currently not possible. These were obstacles to providing the EOC with MERS information. BioSense staff developed a plan to 1) rapidly generate query definitions regardless of the locally preferred SyS tool and, 2) generate aggregate reports to support the national MERS response.

Objective

Demonstrate that information from disparate syndromic surveillance (SyS) systems can be acquired and combined to contribute to national-level situational awareness of emergent threats.

Submitted by teresa.hamby@d… on

Centers for Disease Control and Prevention’s (CDC) BioSense system receives near real-time health care utilization data from number of sources, including DoD and VA outpatient facilities, and nonfederal hospital EDs in the US to support all-hazards surveillance and situational awareness. However, the BioSense system lacks some critical functions such as creating ad hoc definition of syndrome or ad hoc query tool development. This limits CDC Emergency Operations Center’s (EOC) ability to monitor new health events such as MERS - a viral respiratory illness first reported in Saudi Arabia in 2012. In May 2014, CDC confirmed two unlinked imported cases of MERS in the US - one in Indiana, the other in Florida. Upon report of a MERS case in Indiana, staff initiated joint efforts with EOC and several affected jurisdictions to enhance the surveillance of MERS irrespective of jurisdictions’ preferred surveillance system.

Objective

To identify and monitor Middle East Respiratory Syndrome (MERS) like syndromes cases in the syndromic surveillance system.

Submitted by teresa.hamby@d… on
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