Emergency Department (ED)

Emergency Departments (ED) supply critical infrastructure to provide medical care in the event of a disaster or disease outbreak, including seasonal and pandemic influenza [1]. Already over-crowded and stretched to near-capacity, influenza activity augments patient volumes and increases ED crowding [2,3]; high ED patient volumes expected during a true influenza pandemic represents a significant threat to the nation's healthcare infrastructure [4]. EDs ability to manage both seasonal and pandemic influenza surges is dependent on coupling early detection with graded rapid response. Although many EDs have devised influenza response measures, the potential utility of coupling early warning systems with various response strategies for managing influenza outbreaks in the ED setting has not been rigorously studied. While practical use of traditional surveillance systems has been limited due to the several week lag associated with reporting, new internet-based surveillance tools, such as GFT, report surveillance data in near-real time, thus allowing rapid integration into healthcare response planning [5].

Objective

Google Flu Trends (GFT) is a novel internet-based influenza surveillance system that uses search engine query data to estimate influenza activity. This study assesses the temporal correlation of city GFT data to both confirmed cases of influenza, as well as standard crowding indices from one inner-city emergency department (ED).

Epidemic acute gastroenteritis (AGE) is a major contributor to the global burden of morbidity and mortality. Rotavirus and norovirus epidemics present a significant burden annually, with their predominant impact in temperate climates occurring during winter periods. Annually, epidemic rotavirus causes an estimated 600,000 deaths worldwide, and 70,000 hospitalizations in the US, primarily among children <5 years of age. The US burden from norovirus is estimated at 71,000 hospitalizations annually, with the impact more generally across age groups. Changes in rotavirus vaccine use have significantly reduced the impact of epidemic rotavirus.

Objective 

We describe the initial phase of the ISDS Distribute pilot for monitoring AGE syndromic emergency department visits, and present preliminary analysis of age-specific trends documenting a dramatic shift in AGE consistent with US rotavirus vaccine policy and use.

Syndromic surveillance of health care data such as the International Classification of Diseases, Ninth Revision (ICD-9), codes related to Influenza-Like-Illness (ILI), was used to track the progression of the 2009 Fall Novel H1N1 Outbreak in the Madison area. Early studies focused on prediction of an outbreak, however further investigation of patient resource utilization would be helpful in developing an action plan for addressing community and patient needs during future outbreaks. There is a paucity of research comparing emergency department (ED) and urgent care utilization rates during the 2009 Novel H1N1 Pandemic, though there is regional data suggesting that urgent care centers bore a larger portion of the burden of H1N1 influenza than emergency departments. Furthermore, one group found that ILI related phone calls to urgent care centers predicted influenza outbreak at least one week ahead of peaks in the ILI hospital care consultation rates. ED data on its own has proven useful for public health disease surveillance and many studies group urgent care and ED care together. The literature is lacking subgroup analysis of these two very different care environments. Understanding the correlation between urgent care and ED utilization rates will provide a more in depth understanding of the stress that the 2009 Fall Novel H1N1 placed on community resources in our geographic region.

Objective

To compare the proportion of patients presenting with ILI to urgent care centers versus the ED during the 2009 Fall Novel H1N1 Outbreak.

Time-of-arrival (TOA) surveillance methodology consists of identifying clusters of patients arriving to a hospital emergency department (ED) with similar complaints within a short temporal interval. TOA monitoring of ED visit data is currently conducted by the Florida Department of Health at the county level for multiple subsyndromes [1]. In 2011, North Carolina's NC DETECT system and CDC's Biosense Program collaborated to enhance and adapt this capability for 10 hospital-based Public Health Epidemiologists (PHEs), an ED-based monitoring group established in 2003, for North Carolina's largest hospital systems. At the present time, PHE hospital systems include coverage for approximately 44% of the statewide general/acute care hospital beds and 32% of all emergency department visits statewide. We present findings from TOA monitoring in one hospital system.

Objective

To describe collaborations between North Carolina Division of Public Health and the Centers for Disease Control and Prevention (CDC) implementing time-of-arrival (TOA) surveillance to monitor for exposure-related visits to emergency departments (ED) in small groups of North Carolina hospitals.

The North Carolina Division of Public Health (NC DPH) has been collecting emergency department data in collaboration with the Carolina Center for Health Informatics in the UNC Department of Emergency Medicine since 1999. As of August 2011, there are 113 of 115 emergency departments sending data electronically at least once daily to NC DETECT. Data elements include disposition, initial vital signs, up to 11 ICD-9-CM final diagnosis codes, up to five external cause of injury codes (E-codes),as well as the arrival date and time, patient sex and age, patient zip and county, and chief complaint. As of January 2008, NC DETECT emergency department data covered 99% of the NC population and captures approximately 4.5 million ED visits each year. As a result, requests for data from researchers continue to increase. Use of the data for public health purposes is covered by the mandate requiring hospitals to submit their emergency department data to NC DPH.

Objective

To describe the process by which researchers request access to data sets of emergency department data from NC DETECT,the history of this process,and the resulting best practices and lessons learned.

Beginning on March 13, 2011, ACDC experienced an unusual increase in reported bacterial meningitis cases in Los Angeles (LA) County. Early in the investigation, there were few epidemiological links between the cases. Three cases were homeless; two resided at the same Skid Row shelter in downtown LA. ACDC assessed its syndromic surveillance databases to help gauge the scope of the outbreak and detect potentially overlooked cases.

Objective

To describe the complementary usage of electronic emergency department (ED) data, Coroner deaths, and 911 dispatch call center data in a bacterial meningitis outbreak.

Tracking emergency department (ED) asthma visits is an important part of asthma surveillance, as ED visits can be preventable and may represent a failure of asthma control efforts. When using limited clinical ED datasets for secondary purposes such as public health surveillance, it is important to employ a standard approach to operationally defining ED visits attributable to asthma. The prevailing approach uses only the primary ICD-9-CM diagnosis assigned to the ED visit; however, doing so may underestimate the public health impact of asthma. We conducted this pilot study to determine the value of including ED visits with asthma-related diagnoses in secondary or tertiary positions. For example, for an ED visit with a primary diagnosis of upper respiratory infection and secondary diagnosis of asthma, it is possible that the infection triggered the asthma exacerbation and the visit could be attributed to both infection and asthma.

Objective

Determine operational definition of ED visits attributable to asthma for public health surveillance purposes.

Animal bites may have potentially devastating consequences, including physical and emotional trauma, infection, rabies exposure, hospitalization, and, rarely, death. NC law requires animal bites be reported to local health directors. However, methods for recording and storing bite data vary among municipalities. NC does not have a statewide system for reporting and surveillance of animal bites. Additionally, many animal bites are likely not reported to the appropriate agencies. NC DETECT provides near-real-time statewide surveillance capacity to local, regional, and state level users with twice daily data feeds from NC EDs. Between 2008 and 2010, 110 to 113 EDs were submitting visit data to NC DETECT. Several animal bite-related on-line reports are available and provide aggregate and visit-level analyses customized to users' respective jurisdictions. The NC DETECT ED visit database currently provides the most comprehensive and cost-effective source of animal bite data in NC.

Objective

We describe the use of emergency department (ED) visit data collected through the North Carolina Disease Event Tracking and Epidemiologic Collection Tool (NC DETECT) for surveillance of animal bites in North Carolina (NC). Animal bite surveillance using ED visit data provides useful and timely information for public health practitioners involved in bite surveillance and prevention in NC.

According to the Substance Abuse and Mental Health Services Administration’s (SAMHSA) Drug Abuse Warning Network (DAWN) surveillance of drug-related ED visits, underage (B21 years) alcohol-alone visit rates have been increasing since 2004 to 2009 (1). Similarly, the ‘‘alcohol’’ syndrome for underage (12-20 years) ED visits also shows an overall increase from 2003 to 2009 in the percentage of alcohol-related visits (2). College-aged drinkers tend to binge drink at a higher frequency than the general population, putting them at greater risk for unintentional injuries and unsafe sex practices (3). Identifying collegespecific patterns for alcohol-associated morbidity have important policy implications to reduce excessive drinking and associated harms on and around college campuses.

Objective

To develop and implement a method for using emergency department records from a syndromic surveillance system to identify alcohol-related visits in New York City, estimate trends, and describe age-specific patterns. In particular, we are interested in college-aged morbidity patterns and how they differ from other age groups.

CO poisoning poses a significant public health burden. It is preventable, yet it remains a leading cause of poisoning in the United States. An effective surveillance system is very important for targeting and monitoring CO poisoning.Methods or Description: ED data was analyzed from the Missouri Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE). The ED chief complaints of CO poisoning in ESSENCE contain keywords such as 'carbon' or 'monoxide'. The Missouri Health Strategic Architectures and Information Cooperative (MOHSAIC) database was used to collect the other information about the CO poisoning cases. Statistical Analysis Software (SAS) (version 9.3) was applied for all the analyses in this study.

Objective

This study demonstrated the utility and importance of ED data as a surveillance tool as cases of CO poisoning were identified in ESSENCE that were not identified in the passive surveillance system (MOHSAIC). The study also demonstrated the potential of ED data to assist in developing effective, more targeted prevention strategies for CO poisoning.