Skip to main content

Emergency Department (ED)

Current methods for influenza surveillance include laboratory confirmed case reporting, sentinel physician reporting of Influenza-Like-Illness (ILI) and chief-complaint monitoring from emergency departments (EDs).

The current methods for monitoring influenza have drawbacks. Testing for the presence of the influenza virus is costly and delayed. Specific, sentinel physician reporting is subject to incomplete, delayed reporting. Chief complaint (CC) based surveillance is limited in that a patient’s chief complaint will not contain all signs and symptoms of a patient.

A possible solution to the cost, delays, incompleteness and low specificity (for CC) in current methods of influenza surveillance is automated surveillance of ILI using clinician-provided free-text ED reports.

 

Objective

This paper describes an automated ILI reporting system based on natural language processing of transcribed ED notes and its impact on public health practice at the Allegheny County Health Department.

Referenced File
Submitted by hparton on

In disease surveillance, an outbreak is often present in more than one data type. If each data type is analyzed separately rather than combined, the statistical power to detect an outbreak may suffer because no single data source captures all the individuals in the outbreak. Researchers, thus, started to take multivariate approaches to syndromic surveillance. The data sources often analyzed include emergency department data, categorized by chief complaint; over-thecounter pharmaceutical sales data collected by the National Retail Data Monitor (NRDM), and some other syndromic data.

 

Objective

This study proposes a simulation model to generate the daily counts of over-the-counter medication sales, such as thermometer sales from all ZIP code areas in a study region that include the areas without retail stores based on the daily sales collected from the ZIP codes with retail stores through the NRDM. This simulation allows us to apply NRDM data in addition to other data sources in a multivariate analysis in order to rapidly detect outbreaks.

Referenced File
Submitted by hparton on

The South Carolina Aberration Alerting Network (SCAAN) is a collaborative network of syndromic systems within South Carolina. Currently, SCAAN contains the following data sources: SC Hospital Emergency Department chief-complaint data, Poison Control Center call data, Over-the-Counter pharmaceutical sales surveillance, and CDC’s BioSense biosurveillance system. The Influenza-like Illness Network (ILINet) is a collaboration between the Centers for Disease Control, state health departments and health care providers. ILINet is one of several components of SC’s influenza surveillance.

 

Objective

This paper compares the SCAAN hospital-based fever–flu syndrome category with the South Carolina Outpatient ILINet provider surveillance system. This is the first comparison of South Carolina’s syndromic surveillance SCAAN data with ILINet data since SCAAN’s deployment.

Referenced File
Submitted by hparton on

The Public Health Surveillance (PHS) component (one of five monitoring and surveillance components deployed in the Cincinnati drinking water contamination warning system) functions to detect public health incidents resulting from exposure to toxic chemicals that produce a rapid onset of symptoms. Within the PHS component, four data streams were monitored: 911 calls, Emergency Medical Services (EMS) logs, Local Poison Control Center call data, as well as Emergency Department data (via EpiCenter). The focus of this paper centers on the 911 and EMS surveillance tools. The 911 data is dependent on information provided by the caller and the information entered by the dispatcher. EMS data, on the other hand, is recorded by a medical professional, and although not provided as rapidly as 911 data, provides more detailed information. The data included in 911 and EMS alerts, when utilized together, can provide timely and beneficial information during investigation of a possible drinking water contamination incident.

 

Objective

This paper describes the design, application and use of 911 and EMS data in a drinking water contamination warning system.

Referenced File
Submitted by hparton on

Effective and valid surveillance of syndromes can be extremely useful in the early detection of outbreaks and disease trends. However, medical chart checks without patient identifiers and lack of diagnoses in A08 data has made validation difficult. With the rising availability of electronic health records (EHRs) to local health departments, the ability to evaluate syndromic surveillance systems (SSS) has improved. In LAC, ED data are collected from hospitals and classified into categories based on chief complaints. The most reported syndrome in LAC is the respiratory classification, which is intended to broadly capture respiratory pathogen activity trends. To test the validity of the LAC Department of Public Health (DPH) respiratory syndrome classification, ED syndromic surveillance data were analyzed using corresponding EHRs from one hospital in LAC.

Objective

To compare and validate syndromic surveillance categorization against electronic health records at one hospital emergency department (ED) in Los Angeles County (LAC).

Submitted by elamb on

In North Carolina there has been an escalation of poisoning deaths. In 2011, the number of fatal poisonings was 1,368 deaths, with 91% classified as drug overdoses with the majority of those due to opioid analgesics.[1] Far greater numbers of drug overdoses result in hospitalization, emergency department (ED) or outpatient clinic visits, or resolve without the individual seeking medical attention. Although public health authorities have long employed death data for drug overdose surveillance in NC, little attention has been paid to the use of ED data for this purpose. Through the North Carolina Disease Event Tracking and Epidemiologic Collection Tool (NC DETECT), NC collects information on 99.5% of all acute-care ED visits across the state, primarily for syndromic surveillance purposes. Despite the timeliness and completeness of this data system, drug overdose surveillance is a challenge due to lack of a standardized definition for the positive identification of opioid overdoses. In this study we used NC DETECT ED data to describe visits due to drug, and more specifically, opioid overdoses. Objective: To describe the epidemiologic characteristics for emergency department visits due to drug overdoses in North Carolina.

Submitted by elamb on

Reliable detection and accurate scoping of outbreaks of foodborne illness are the keys to effective mitigation of their impacts. However, relatively small number of persons affected and underreporting, challenge the reliability of surveillance models. In this work, we correlate a record of identified outbreaks and sporadic cases of Salmonellosis in humans retained in PulseNet1, and diagnosis codes in hospital claims collected in California from 2006 to 2010. We hypothesize that the data support and reliability of detection could be improved by including cases in which Salmonella infection may be confused2.

Objective

To investigate utility of using inpatient and emergency room diagnoses to detect outbreaks of Salmonellosis in humans. To quantify the impact of including in the analysis cases diagnosed with conditions that may have physiological appearance similar to Salmonellosis.

Submitted by elamb on

In Reunion Island, alcohol is the most experienced psychoactive substance [1]. Alcohol consumption is characterized by a massive ingestion of hard liquor and an early experimentation. Health consequences are significant: a high annual incidence of fetal alcohol syndromes [2] and a higher premature mortality than in France mainland [1]. Reunion island is one the French regions most affected by addictive behaviors related to alcohol. However, existing data are insufficient concerning the current health impact and associated factors.

Objective

Describe the emergency departments' visits for alcohol intoxication (AI) in Reunion Island and factors associated with their variations.

Submitted by elamb on

The 'Grand Raid de la Reunion' is one of the hardest ultra trails in the world (5,350 competitors in 2012). This one stage race takes place in Reunion Island, a French overseas department in the Indian Ocean. Ultra trails and ultra marathons are intense long-distance running races pushing back human physical abilities' limits. In general terms, studies about these races highlight different severity levels' injuries, from asymptomatic to critical condition [1-4]. No study has yet used syndromic surveillance to study the impact of such sporting events on ED visits. Using a syndromic surveillance approach to monitor sport-related visits could allow an early public health response.

Objective

To estimate the health impact of the 'Grand Raid de la Reunion' (GRR) ultra trail in 2012 on the emergency departments (ED) of Reunion Island.

Submitted by elamb on

Syndromic surveillance is usually presented as relevant for event detection. As the data collected automatically from data sources is detailed enough (e.g. ICD10 codes), it may contribute to assess and quantify the burden of health events and describe their main epidemiological features. In France, besides the national liver transplant data, no surveillance data are available for ALF. Since ALF is severe, threatens the vital prognosis in absence of intensive care, may require liver transplantation and is quite well characterized clinically, patients are very likely to be diagnosed with ALF in ED at the onset phase. ALF is caused by viral infections (hepatitis A, B, C, D or E viruses), drug or toxic exposures, autoimmune or metabolic disorders (Wilson's disease), some of which have public health implications (viral hepatitis, drug or toxicological adverse effects). We therefore hypothesized that surveillance of ALF through an ED syndromic surveillance system would be feasible. The aim of our work was to explore the relevance of ED data to describe the main features and assess the burden of ALF.

Objective

The objective of this study was to assess the interest and feasibility of using syndromic surveillance data from emergency departments (ED) for the description of clinical and epidemiological characteristics of patients with acute liver failure (ALF) during the 2010-2012 period in France.

Submitted by elamb on
Subscribe to Emergency Department (ED)