ISDS Conference

Visitors from areas outside Miami-Dade County have the potential to introduce diseases and/or strains of microorganisms circulating in their regions of residence. Immunocompromised and immunonaive travelers are at higher risk of contagion by locally transmitted pathogens. The first encounter with a local health care facility for many of these visitors is often an Emergency Departments (ED). Little is known about this group of patients with regard to socio-demographic and temporal patterns. This knowledge is essential to further characterize their syndromic patterns as well as to integrate this knowledge to the growing use of syndromic surveillance as an early-warning public health tool.

Objective

To describe socio-demographic and temporal patterns of patients who reside outside Miami-Dade and who visited EDs of hospitals located in this County during 2007.

During influenza season, the Boston Public Health Commission uses syndromic surveillance to monitor Emergency Department visits for chief complaints indicative of influenza-like illness (ILI). We created three syndrome definitions for ILI to capture variable presentations of disease, and compared the trends with Boston pneumonia and influenza mortality data, and onset dates for reported cases of influenza.

Objective

To evaluate the impact of different syndrome definitions for ILI by comparing weekly trends with other data sources during the 2005-2006 influenza season in Boston.

While early event detection systems aim to detect disease outbreaks before traditional means, following up on the many alerts generated by these systems can be time-consuming and a drain on limited resources.

Authorized users at local, regional and state levels in North Carolina rely on the North Carolina Disease Event Tracking and Epidemiologic Collection Tool's (NC DETECT) Java-based Web application to monitor and follow-up on signals based on the CDC’s EARS CUSUM algorithms. The application provides users with access to aggregate syndrome-based reports as well as to patient-specific line listing reports for three data sources: emergency departments, ambulance runs and the statewide poison control center. All NC DETECT Web functionality is developed in a user-centered, iterative process with user feedback guiding enhancements and new development. This feedback, along with the need for improved situational awareness and the desire to improve communication among users drove the development of the Annotation Reports and the Custom Event Report.

Objective

We describe the addition of two reports to NC DETECT designed to improve NC public health situational awareness capability.

The Early Aberration Reporting System was developed at the Centers for Disease Control and Prevention to help assist local and state health officials to focus limited resources on appropriate activities of public health surveillance. Outbreaks of

infectious diseases are indicated in multiple spatial and temporal data sources, such as emergency department visits, drug store sales, and ambulatory clinic visits. Based on this premise, we provided correlated data sets and investigated disease clusters.

Objective

We present a pilot study of simulation of correlated outbreak signals for early aberration reporting and evaluating detection methods.

It has been noted since the era of Hippocrates that weather conditions at a specific location can influence the incidence of various infectious and noninfectious diseases. It has also been implied that variations in weather conditions influence the number of cases of infectious respiratory conditions. Syndromic surveillance was introduced in Athens, Greece, for the first time in July 2002 in the framework of increased preparedness for the Olympic Games of 2004. Our experience showed that the incidence of some syndromes parallels that of diseases surveyed by the mandatory notification system of the Hellenic Center for Diseases Control and Prevention that are known to have a strong seasonal pattern in their incidence e.g. influenza. Influenza incidence peaks at the same time with the “respiratory infection with fever” syndrome during spring. This study aimed at investigating possible relationships between the incidence of the “respiratory infection with fever” syndrome and meteorological parameters.

Objective

This study explores the possible impact of meteorological conditions on the incidence of clinical syndromes with an interest for public health in the basin of Athens, Greece.

Timely outbreak detection, and monitoring of morbidity and mortality among Katrina evacuees, and needs assessment for better planning and response were urgent information intensive priorities during Katrina relief efforts at Houston, and called for immediate deployment of a real-time surveillance and needs assessment system ad hoc, in order to collect and analyze relevant data at the scene. Initial requirement analysis revealed the following capabilities as essential to sustain effective response within the shelters:

• The ability to securely collect and integrate data from evacuees seeking any form of health services from all care providers (academic, volunteers, federal, NGOs and international aid organizations, etc), including demographic information, vital signs, chief complaints, disabilities, chronic conditions, current and past medications, traumas and injuries, exposure to toxic materials, clinical laboratory results, past medical history, discharge notes and diagnoses, and ability to collect free text entries for any other information (similar to a full-blown electronic medical records system).

• Proactive survey of demographic profile, physical and mental health status, as well as special needs assessment (e.g., dialysis, medications, etc) from all evacuees.

• The ability to collect uniform information, using any network-enabled device available: PCs, tablets, and handheld devices. 

• The ability to classify observations by processing sign and symptom, chief complaint, medication, and other diagnostic data (including free text entries) through ad-hoc definition of concepts such as (Gastrointestinal, Respiratory, Fever and Rash, etc). 

Objective

This paper presents lessons learned from leveraging Internet-based technologies and Services Oriented Architecture in providing timely, novel, and customizable solutions, just in time and for preparedness against unprecedented events such as natural disasters (e.g., Katrina) or terrorism.

The use of syndromic surveillance systems to assist with the timely detection of unusual health events first occurred prior to the events of September 11, 2001. In the State of Michigan a pilot project with emergency departments began collecting syndromic data in 2004. Little research has been done in rural settings which have unique characteristics such as having one medical facility for a large geographic region. In addition to being rural, the community in which the following study was done is a resort com-munity where the population differs between the summer and winter months in number and composi-tion. Another unique factor in this study is that there is little published literature utilizing triage and dis-charge syndromic groups as a means for determining system sensitivity and specificity.

Objective

This paper describes the analysis of sensitivity and specificity of an ICD-9 based syndromic surveillance system in a rural emergency department located in Northern Lower Michigan.

Previously we developed an “Ngram” classifier for syndromic surveillance of emergency department (ED) chief complaints (CC) in Turkish for bioterrorism. The classifier is developed from a set of ED visits for which both the ICD diagnosis code and CC are available. A computer program calculates the associations of text fragments within the CC (e.g. 3 characters for a “3-gram”) with a syndromic group of ICD codes. The program then generates an algorithm which can be deployed to evaluate chief complaint data in real-time. However, the N-gram method differs from most other classifiers in that it assigns a probability that each visit falls within the syndrome rather than ruling the visit “in” or “out” of the syndrome. It is possible to dichotomize visits “in” or “out” using N-grams by choosing a cut-off sensitivity for the n-grams used, but this affects the specificity of the method. The effect of this trade-off is best measured by a receiveroperator curve.

Objective

Our objective was to determine the sensitivity and specificity of the Ngram CC classifier for individual ED visits. We also wish to compare these results to those obtained when we substituted anglicized characters for 6 problematic Turkish characters.

Chief complaints are often represented textually and as a mixture of complex and context-dependant lexical symbols with little formal sentence structure. Although human experts usually comprehend this information in its right context intuitively and effortlessly, use of chief complaint data by computers is a challenge. Semantic approaches for text understanding are concerned with the meaning of terms and their relationships, driven from an explicit model rather than their syntactic forms. Explicit representation of domain concepts along with computer reasoning enables a knowledgeable computer agent to identify those concepts in a given text and pinpoint relevant relationships if they make sense according to an existing formal model available to the agent .

Objective

This paper proposes a semantic approach to processing free form text information such as chief complaints using formal knowledge representation and Description Logic reasoning. Our methods extract concepts and as much contextual information as is available in the text. Output consists of a computationally interpretable representation of this information using the Resource Definition Framework (RDF) and UMLS Metathesaurus.

BioSense is a Centers for Disease Control and Prevention (CDC) national near real-time public health surveillance system. CDC’s BioIntelligence Center (BIC) analysts monitor, analyze, and interpret BioSense data daily and provide support to BioSense users at state and local health departments and facilities sending data. The BioSense Application is continually being enhanced in concordance with public health and clinical partners. Ongoing dialogue between the BIC and these partners is required to gather user feedback, understand what would improve system utility, build collaborative relationships, and develop appropriate jurisdictionspecific communication protocols. In May 2006, BioSense hosted a face-to-face meeting in Atlanta with approximately 50 users to solicit recommendations for the program in general and the application. Also, every 1 to 2 months, a teleconference (“Real Time, Real Talk”) is held for all BioSense users. Because of confidentially issues, jurisdiction-specific data and issues can not be raised during such meetings, thus warranting the need for a forum in which such topics could be addressed.

Objective

To present lessons learned from the BioSense jurisdiction-specific webinars conducted in 2007.