Evaluation of Syndromic Surveillance

NSSP, a Centers for Disease Control and Prevention (CDC) surveillance system, allows timely detection of emergency department (ED) trends by matching chief complaint (CC) text or diagnosis (DX) codes to established syndrome criteria [1, 2]. No CDC syndrome definition currently exists for marijuana-related visits. Accidental child ingestions and over-consumption of edible products are an emerging concern [3, 4]. A validated marijuana syndrome will allow health departments with access to ED data to measure relative trends and disparities in marijuana-related ED visits.

Objective

To evaluate methods of measuring marijuana-related emergency department visits at Denver metropolitan area hospitals participating in the National Syndromic Surveillance Program (NSSP).

Arguably the two most significant public health issues over the past two years have been the outbreak of ebola in West Africa and the rising epidemic of heroin use and overdoses. In the case of Ebola, the CDC issued guidance for inpatient facilities to screen for potential cases, however, there was little guidance for screening patients that presented to EMS workers. The West African pateint aht presented to the Emergency Department in Dallas was transported, unknowingly, by EMS, potentially exposing them and others to this deadly disease. Likewise, heroin has become an exploding epidemic in the United States with deaths from overdoses skyrocketing across the country. There are few data sources for overdoses that can alert and track real time instances of heroin overdose which are arguably the highest risk patients in the community. This will make it difficult for interventions in the community as expressed recently by the White House.

Objective

The objective of this oral presentation is to describe the use of near real time 911 Emergency Medical Services data in looking for suspected cases of Ebola and heroin cases in the community.

Monitoring heat-related illness (HRI) is a public health priority in Maricopa County, Arizona. Since 2006, Maricopa County Department of Public Health has utilized data from hospital discharges, medical examiner preliminary reports, and death certificates to quantify heat-related morbidity and mortality, but these surveillance methods take time. Identifying HRI more quickly would improve situational awareness and allow public health officials to launch a more immediate response to extreme heat events. Arizona began using BioSense 2.0 in July 2014 to collect chief complaint and diagnosis data for syndromic surveillance. The BioSense Front End Application uses a standard query definition for HRI (i.e., “Heat, excessive”), but this definition may perform differently for each jurisdiction.

Objective

To evaluate the pre-defined “Heat, excessive” query in BioSense 2.0 using recent Maricopa County, Arizona data; quantify the number of cases retrieved by the query due to chief complaint terms rather than clinical diagnosis; and provide a list of terms to be considered for exclusion criteria while developing a custom query

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.

Community health assessments are a foundation of public health practice and a prerequisite to achieving public health accreditation. Best practice dictates that CHAs must incorporate qualitative and quantitative data and utilize a number of indicators to create a detailed picture of a community’s health. Metrics may describe demographics, social and economic factors, health behaviors, health outcomes, and healthcare access and utilization. Commonly used indicators facilitate cross-jurisdiction comparisons and simplify decisionmaking. However, while many readily available indicators exist on a county level, few have been made available on the sub-county level. Syndromic surveillance messages, typically emergency room visit records, contain sub-county level data on patient residence, such as zip code or municipality. As hospitals progress towards meeting Stage 2 Meaningful Use requirements, transmission of syndromic surveillance data to public health entities will become standard. Analysis of emergency room visit data, either in aggregate or by specific syndromes, may be a valuable sub-county level indicator of community health status and access to care that can be standardized across jurisdictions.

Objective

To identify geographic clustering of elevated emergency room (ER) usage rates for incorporation into community health assessments (CHA) in suburban Cook County and to validate this metric as a potential sub-county level community health indicator.

Syndromic surveillance has been used by state agencies to collect real-time information on disease outbreaks but has not been used to collect data in the occupational setting. Therefore, OHS staff has begun evaluating a real-time surveillance tool to track a variety of occupationally-related emergency room visits throughout the state via EpiCenter, the NJDOH’s existing real-time surveillance system. This proposal applies established epidemiologic techniques to a different set of circumstances than they have been applied to in the past. Incorporating Syndromic Surveillance data with hospital discharge data will enhance the ability to classify and capture work-related nonfatal injuries and improve efforts of prevention. By employing a realtime, independent data source such as EpiCenter, the classification of work-related injuries and illnesses could be greatly enhanced, leading to a better understanding of the burden of non-fatal work-related injuries and illnesses, and allowing for quicker intervention.

Objective

The New Jersey Department of Health (NJDOH), Occupational Health Surveillance (OHS) Unit staff proposes to evaluate a realtime surveillance tool to track a variety of occupationally-related emergency room visits throughout the state via EpiCenter, the NJDOH’s existing real-time surveillance system.

Illnesses related to synthetic marijuana use have been reported in many states, including Florida. Because these visits can present with a variety of symptoms, as well as be attributed to numerous diagnosis codes, it can be difficult to identify and quantify these visits. The Electronic Surveillance System for the Early Notification of Community-based Epidemics in Florida (ESSENCE-FL) receives chief complaint (CC) and discharge diagnosis (DD) data as free text allowing uncommon or new terms to be searched for within each patient visit. The main source of data for ESSENCE-FL is emergency department (ED) and urgent care center (UCC) data. There are currently 210 EDs and 33 UCCs throughout Florida that send their data to the ESSENCE-FL server. Using ESSENCE-FL, a free text query of patient CCs and DDs was used to identify visits related to synthetic marijuana use. This study is designed to analyze these identified visits for trends over time, geographical distribution and descriptive statistics and demographics.

Objective

One of the numerous functions of syndromic data has been the identification of visits of public health interest using customized free text queries. A specific query of syndromic data was created to search for and identify emergency department (ED) and urgent care center (UCC) visits possibly related to the use of synthetic marijuana to describe and quantify this public health issue in Florida.

Underage drinking is a significant public health problem in the United States as well as in Nebraska1-2. Alcohol consumption among underage youth accounts for approximately 5,000 deaths each year in the United States, including motor vehicle crash related deaths, homicides and suicides1. In Nebraska, 23% of 12-20 year olds have reported alcohol use during the past 30 days3. In 2010, the estimated total costs of underage drinking in Nebraska were $423 million. These costs included medical care, work loss along with pain and suffering2. The health consequences of underage drinking include alcohol-related motor vehicle crashes and other unintentional injuries, physical and sexual assault, suicide, self-inflicted injury, death from alcohol poisoning, and abuse of other drugs1, 4. The monitoring of near-real–time ED data could help underage drinking prevention efforts by providing timelier actionable public health information.

Objective

The objective of this pilot study was to develop and evaluate syndromic definitions for the monitoring of alcohol-related emergency department (ED) visits in near-real–time syndromic surveillance (SyS) data. This study also evaluates the utility of SyS ED data for the monitoring of underage drinking.