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Enhanced Surveillance

Ontologies representing knowledge from the public health and surveillance domains currently exist. However, they focus on infectious diseases (infectious disease ontology), reportable diseases (PHSkbFretired) and internet surveillance from news text (BioCaster ontology), or are commercial products (OntoReason public health ontology). From the perspective of biosurveillance text mining, these ontologies do not adequately represent the kind of knowledge found in clinical reports. Our project aims to fill this gap by developing a stand-alone ontology for the public health/biosurveillance domain, which (1) provides a starting point for standard development, (2) is straightforward for public health professionals to use for text analysis, and (3) can be easily plugged into existing syndromic surveillance systems.

 

Objective

To develop an application ontology - the extended syndromic surveillance ontology - to support text mining of ER and radiology reports for public health surveillance. The ontology encodes syndromes, diagnoses, symptoms, signs and radiology results relevant to syndromic surveillance (with a special focus on bioterrorism).

Referenced File
Submitted by hparton on

During the spring of 2009, a public health emergency was declared in response to the emergence of the 2009 Influenza A (H1N1) virus. Owing to the response, timely data were needed to improve situational awareness and to inform public health officials. Traditional influenza surveillance is time-consuming and resource intensive, and electronic data sources are often more timely and resource saving. Collaboration began between the Centers for Disease Control and Prevention (CDC), the International Society for Disease Surveillance, and the Public Health Informatics Institute to expand syndromic Emergency Department (ED) surveillance through the Distribute project.

Distribute collects aggregate, daily or weekly reports of influenza-like illness (ILI) and total patient visits to EDs from participating health jurisdictions, stratified by age group and other variables. Additional variables included the three digit zip code of the patient’s residence as well as the disposition and temperature, however not all jurisdictions collect these variables. Distribute data are typically extracted from ED-based electronic health data systems. The ILI definition is determined by the participating jurisdiction that can be a city, county, or state. At the time of analysis, the network consisted of 33 jurisdictions.

Because ILI data reported to Distribute had not been systematically compared with data reported through other surveillance systems, CDC planned an evaluation of the Distribute data, which included a comparison to the Influenza-like Illness Network (ILINet). 

ILINet is a collaborative effort between the CDC, local and state health departments and primary health care providers. The network currently consists of approximately 3000 healthcare providers in all 50 states, Chicago, the District of Columbia, New York City, and the US Virgin Islands. Enrolled providers send CDC weekly reports via internet or fax that consist of the total number of patients seen for any reason and the number of those patients with ILI by age group. ILI is defined as fever (temperature of X1001F (37.8 1C)) and a cough and/or sore throat in the absence of a known cause other than influenza.

 

Objective

To compare ILI data reported to the Distribute surveillance project to data from an existing influenza surveillance system, the US Outpatient ILINet.

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

In Reunion Island, the non-specific surveillance was developed since 2006 and was based on the activity of only one hospital emergency department and on mortality. To respond to the threat of influenza A(H1N1) pandemic emergence, this surveillance system was significantly enhanced. All hospital emergency departments of the island have been included as well as the emergency medical service regulation center. In 2010, a new surveillance was implemented from National Health Insurance data.

 

Objective

To demonstrate that the different surveillance systems allow to establish complementary indicators.

Referenced File
Submitted by elamb on

Influenza affects millions of people and causes about 36,000 deaths in the United States each winter. Pandemics of influenza emerge at irregular intervals. National influenza surveillance is used to detect the emergence and spread of influenza virus variants and to monitor influenza-related morbidity and mortality. Existing surveillance consists of seven data types, which are reported weekly. Newly available national electronic data sources created as part of the routine delivery of medical care might supplement current data sources. Nurse call data offer national coverage, are timely, and do not require any extra manual data entry. Using such data for influenza-like illness (ILI) surveillance may lead to earlier detection of ILI in the community, both because people with ILI may call a nurse line before seeking care at a health-care facility and because the data are more timely than existing weekly data.

 

Objective

Our purpose was to compare nurse call data for respiratory and ILI against CDC national influenza surveillance data from the 2004-2005 season by region to determine if the call data were informative and might allow earlier detection of influenza activity.

Referenced File
Submitted by elamb on

An outbreak of dengue fever has occured in French Guiana since the end of November 2005 until July 2006. The dengue serotype circulating was DEN-2, responsible of more than 2 000 confirmed cases and 4 deaths. The previous surveillance system was only based on the laboratories data, and didn’t permit to assess the real situation of dengue infection within the population of French Guiana. Actually, the dengue fever being a viral infection for which no etiological treatments nor immunization were available, a lot of general practioners didn’t send their patients to laboratories but prescribed only a symptomatic treatment. A survey made on the field during February 2006 in a town of 5000 inhabitants in the West of French Guiana showed that the real situation within the population was really more important than the one evaluated by the current surveillance system (135 suspected cases for only 13 confirmed cases reported by the network of laboratories). For that reason, it was decided to put in place a syndromic surveillance system, which can permit to have a better knowledge of the situation for dengue fever. The objectives of this new system were i) to detect earlier the beginning of an outbreak ii) to have a better estimation of the impact of the outbreak within the population and iii) to permit the evaluation of the Public Health strategy set up.

 

Objective

This paper describes a new syndromic surveillance system installed in French Guiana in April 2006 during an outbreak of dengue fever.

Referenced File
Submitted by elamb on

Emerging infections, both natural and intentional, have provided an impetus for improved disease surveillance and response. The recognition of the interdependence of health care systems and public health infrastructure provides an opportunity to expand beyond traditional disease-based surveillance to a more comprehensive, integrated approach that leverages existing electronic information. The Veterans Affairs (VA) hospital system is uniquely positioned to perform multi-institutional enhanced electronic surveillance. A wealth of electronic information and technology resources are available in all VA hospitals and their associated clinics, as each facility uses the same standardized Computer Patient Record System. Influenza-like illness (ILI) is a common clinical syndrome of diverse etiology that presents with respiratory and systemic symptoms. The NC health department mandates the reporting of ILI from emergency departments to facilitate monitoring of seasonal ILI and serve as an important component of pandemic preparedness. Existing surveillance systems utilize an ICD-9 respiratory code screen and subsequent manual chart review which is timeconsuming and insensitive. Automated medical record review using more comprehensive electronic data may improve the system’s timeliness and efficiency.

 

Objective

To use data collected by NC-VET to create an automated ILI surveillance program and compare its accuracy and efficiency to the existing program.

Referenced File
Submitted by elamb on

Syndromic surveillance can be a useful tool for the early recognition of outbreaks and trends in emergency department (ED) data. In addition, as a more timely data source than traditional disease reporting, syndromic data may also be leveraged to identify individual disease cases, increasing the utility for first time or redundant case recognition.

San Diego County (COSD) performs daily ED syndromic surveillance. In order to assess the utility for early identification of specific conditions of public health interest (e.g., salmonellosis, meningitis, hazardous exposures, heat-related illness), a novel process entitled Priority Infectious Conditions Capture, was developed.

 

Objective

This paper describes an assessment of an enhanced surveillance process used to identify reportable diseases and conditions of public health importance from ED chief complaint data in COSD.

Referenced File
Submitted by elamb on

The Miami-Dade County Health Department currently utilizes Emergency Department based Syndromic surveillance data, 911 Call Center data, and more recently Public School Absenteeism data. Daily monitoring of school absenteeism data may enhance early outbreak detection in Miami-Dade County in conjunction with the use of other syndromic systems. These systems were employed to detect any possible outbreaks resulting from a large outdoor festival occurring March 11th, 2007. This event had an estimated 1 million visitors and it ended at 7:00 p.m.

 

Objective

Utility of school absenteeism data to enhance syndromic surveillance activities for unusual public health events or outbreak detection.

Referenced File
Submitted by elamb on

The New York State Department of Health (NYSDOH) currently applies EARS’s CuSum analyses to Medicaid Over the Counter and Prescription Medications data obtained from the Office of Medicaid Management's data warehouse. Daily drug category counts are compared with counts for a 7-day baseline period to generate C1, C2, and C3 signals for 62 counties and 8 Syndromic Surveillance Regions. Summary tables and graphs are posted on the NYSDOH Secure Health Commerce Network for access by state, regional, and county users.

The 7-day baseline CuSum method of analysis of syndromic surveillance databases can result in the generation of a large number of signals. Many signals are generated for counts that, upon manual review of 30-day or long-term trend graphs, are clearly within the range of normal daily variation and would not require follow up by public health authorities.

In order to prevent user desensitization to generated signals and minimize NYSDOH Syndromic Surveillance System end-user burden, supplemental measures that would indicate a daily count is higher than expected are currently being investigated.

 

Objective

To supplement CuSum analyses of syndromic surveillance databases within NYSDOH's Electronic Syndromic Surveillance System with other measures that would indicate a daily count is higher than expected in order to minimize the end-user burden of following up generated signals.

Referenced File
Submitted by elamb on
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