Surveillance Systems

Maryland’s electronic surveillance system for the early notification of community-based epidemics (ESSENCE) data includes emergency department visits from all acute care hospitals, over-the-counter medication sales and poison control data that cover all jurisdictions in Maryland. Maryland Department of Health and Mental Hygiene (DHMH) uses ESSENCE daily for the early detection of public health emergencies. DHMH also utilizes ESSENCE for other purposes including situational awareness during high security events, assistance with outbreak investigation and for the H1N1 pandemic.

Objective

The purpose of this paper is to describe how Maryland’s syndromic surveillance system, electronic surveillance system for the early notification of community-based epidemics (ESSENCE), has many utilities including identifying threats, case investigation and situational awareness.

Twitter is a free social networking and micro-blogging service that enables its millions of users to send and read each other’s ‘tweets’, or short messages limited to 140 characters. The service has more than 190 million registered users and processes about 55 million tweets per day. Despite a high level of chatter, the Twitter stream does contain useful information, and, because tweets are often sent from handheld platforms on location, they convey more immediacy than other social networking systems.

Objective

This paper describes a system that uses Twitter to estimate influenza-like illness levels by geographic region.

Group A beta-hemolytic Streptococcus (GABHS) has caused outbreaks in recruit training environments, where it leads to significant morbidity and, on occasion, has been linked to deaths. Streptococcal surveillance has long been a part of military recruit public health activities. All Navy and Marine Corps training sites are required to track and record positive throat cultures and rapid tests on weekly basis. The Navy and Marine Corps have used bicillin prophylaxis as an effective control measure against GABHS outbreaks at recruit training sites. Though streptococcal control program policies vary by site, a minimum prophylaxis protocol is required and mass prophylax is indicated when local GABHS rates exceed a specific threshold. Before July 2007, prophylaxis upon initial entry was required between October and March, and when the local rate exceeded 10 cases per 1000 recruits. In July 2007, the Navy instituted a policy of mass prophylaxis upon initial entry throughout the year. Evaluation of GABHS cases before and after implementation of the new policy, including overall rates, identification of outbreaks, and inpatient results will help enhance the Navy’s ability to evaluate threshold levels, provide systematic/standardized monitoring across the three recruit sites, and inform prophylaxis and monitoring strategies.

Objective

To compare trends of group A beta-hemolytic Streptococcus among recruits before and after changes in prophylaxis implementation using electronic laboratory and medical encounter records.

A comprehensive electronic medical record (EMR) represents a rich source of information that can be harnessed for epidemic surveillance. At this time, however, we do not know how EMR-based data elements should be combined to improve the performance of surveillance systems. In a manual EMR review of over 15 000 outpatient encounters, we observed that two-thirds of the cases with an acute respiratory infection (ARI) were seen in the emergency room or other urgent care areas, but that these areas received only 15% of total outpatient visits. Because of this seemingly favorable signal-to-noise ratio, we hypothesized that an ARI surveillance system that focused on urgent visits would outperform one that monitored all outpatient visits.

Electronic disease surveillance systems can be extremely valuable tools; however, a critical step in system implementation is collection of data. Without accurate and complete data, statistical anomalies that are detected hold little meaning. Many people who have established successful surveillance systems acknowledge the initial data collection process to be one of the most challenging aspects of system implementation. These challenges manifest from varying degrees of economical, infrastructural, environmental, cultural, and political factors. Although some factors are not controllable, selecting a suitable collection framework can mitigate many of these obstacles. JHU/APL, with support from the Armed Forces Health Surveillance Center, has developed a suite of tools, Suite for Automated Global bioSurveillance (SAGES), that is adaptable for a particular deployment’s environment and takes the above factors into account. These subsystems span communication systems such as telephone lines, mobile devices, internet applications, and desktop solutions--each has compelling advantages and disadvantages depending on the environment in which they are deployed. When these subsystems are appropriately configured and implemented, the data are collected with more accuracy and timeliness.

Objective

This paper describes the common challenges of data collection and presents a variety of adaptable frameworks that succeed in overcoming obstacles in applications of public health and electronic disease surveillance systems and/or processes, particularly in resource-limited settings.

Group A beta-hemolytic Streptococcus (GABHS) has caused outbreaks in recruit training environments, where it leads to significant morbidity and, on occasion, has been linked to deaths. Streptococcal surveillance has long been a part of military recruit public health activities. All Navy and Marine Corps training sites are required to track and record positive throat cultures and rapid tests on weekly basis. The Navy and Marine Corps have used bicillin prophylaxis as an effective control measure against GABHS outbreaks at recruit training sites. Though streptococcal control program policies vary by site, a minimum prophylaxis protocol is required and mass prophylax is indicated when local GABHS rates exceed a specific threshold. Before July 2007, prophylaxis upon initial entry was required between October and March, and when the local rate exceeded 10 cases per 1000 recruits. In July 2007, the Navy instituted a policy of mass prophylaxis upon initial entry throughout the year. Evaluation of GABHS cases before and after implementation of the new policy, including overall rates, identification of outbreaks, and inpatient results will help enhance the Navy’s ability to evaluate threshold levels, provide  systematic/standardized monitoring across the three recruit sites, and inform prophylaxis and monitoring strategies.

Objective

To compare trends of GABHS among recruits before and after changes in prophylaxis implementation using electronic laboratory and medical encounter records.

Influenza causes significant morbidity and mortality, with attendant costs of roughly $10 billion for treatment and up to $77 billion in indirect costs annually. The Centers for Disease Control and Prevention conducts annual influenza surveillance, and includes measures of inpatient and outpatient influenza-related activity, disease severity, and geographic spread. However, inherent lags in the current methods used for data collection and transmission result in a one to two weeks delay in notification of an outbreak via the Centers for Disease Control and Prevention’s website. Early notification might facilitate clinical decision-making when patients present with acute respiratory infection during the early stages of the influenza outbreak. 

In the United States, the influenza surveillance season typically begins in October and continues through May. The Utah Health Research Network has participated in Centers for Disease Control and Prevention’s influenza surveillance since 2002, collecting data on outpatient visits for influenza-like illness (ILI, defined as fever of 100F or higher with either cough or sore throat). Over time, Utah Health Research Network has moved from data collection by hand to automated data collection that extracts information from discrete fields in patients’ electronic health records.

We used statistical process control to generate surveillance graphs of ILI and positive rapid influenza tests, using data available electronically from the electronic health records. 

Objective

The objective of this study is to describe the use of point-of-care rapid influenza testing in an outpatient, setting for the identification of the onset of influenza in the community. 

The Office of the Medical Examiner (OME) is a statewide system for investigation of sudden and unexpected death in Utah. OME, in the Utah Department of Health (UDOH), certified over 2000 of the 13,920 deaths in Utah in 2008.

Information from OME death investigations is currently stored in three separate UDOH data silos that have limited interoperability. These three electronic data systems include death certificates, medical examiner investigations, and laboratory results. Without interoperability, OME staff is required to enter the same data into multiple systems. In addition, the process of requesting laboratory analysis and receiving results is paper based, significantly slowing final cause of death determination in a majority of cases.

Epidemiological studies and surveillance activities are hindered by the lack of systems integration in UDOH and often require retrospective data linkage. As an example, in 2005, CDC and the UDOH reported that deaths in Utah caused by drug poisoning from non-illicit drugs had increased fivefold from 1991 to 2003.1 This significant finding relied on retrospective linkage of death certificates, medical examiner records, and toxicology results to describe the problem.

In 2008, funding from a bioterrorism grant from the US Department of Homeland Security was secured to support development of a unique, integrated system for medical examiner and death certificate data.

Objectives

The objectives of the Utah Medical Examiner Database (UMED) project are:

• To provide a single point of entry for medical examiner pathologists and staff to manage investigation information.
• To develop an operational system that links death certificate, medical examiner, and laboratory data in real time as a resource for epidemiology and public health surveillance.

Previous reports have demonstrated the media’s influence on ED visits in situations such as dramatized acetaminophen overdose, media report of celebrity suicides, television public announcements for early stroke care and cardiac visits following President Clinton’s heart surgery. No previous study has demonstrated the influence of media-publicized trauma on ED visits. On 16 March 2009, the actress Natasha Richardson suffered a traumatic brain injury leading to her death on 18 March; these events were widely publicized by national news sources. The health departments of New York City, Boston, Duval County and Seattle monitor ED visits daily, and capture 95, 100, 100 and 95% of all ED visits, respectively. The data collected include basic demographic information, chief complaint and in some cases ICD-9 diagnosis codes.

Objective

This study describes an increase in head trauma-related visits to emergency departments (ED) in New York City, New York; Boston, Massachusetts; Duval County, Florida; and Seattle, Washington following the widespread media coverage of actress Natasha Richardson’s head injury and subsequent fatal epidural hematoma.

A comprehensive electronic medical record (EMR) represents a rich source of information that can be harnessed for epidemic surveillance. At this time, however, we do not know how EMR-based data elements should be combined to improve the performance of surveillance systems. In a manual EMR review of over 15 000 outpatient encounters, we observed that two-thirds of the cases with an acute respiratory infection (ARI) were seen in the emergency room or other urgent care areas, but that these areas received only 15% of total outpatient visits. Because of this seemingly favorable signal-to-noise ratio, we hypothesized that an ARI surveillance system that focused on urgent visits would outperform one that monitored all outpatient visits.