Objective
We asked to what extent computerized processing of the full free-text clinical documentation could enhance syndrome detection compared to the sole use of structured data elements from a comprehensive electronic medical record.
Objective
We asked to what extent computerized processing of the full free-text clinical documentation could enhance syndrome detection compared to the sole use of structured data elements from a comprehensive electronic medical record.
The ability to accurately predict influenza infection by symptoms and local epidemiology prior to lab confirmation warrants further study and is particular concern as the threat of pandemic flu heightens. Antiviral drugs are effective when given within 48 hours of symptom onset, but this usually precludes culture confirmation. Further, rapid tests can be clinically helpful but lack the sensitivity of viral culture. Hence, ILI symptoms are a potentially important covariate in the early diagnosis of flu. However, gaps remain in several areas of flu symptom research, including knowledge of potential differences between symptoms of Influenza A and of Influenza B [1]. Therefore, an examination of symptoms generally associated with Influenza infection was begun, as well as an examination of symptoms specifically associated with Flu A and Flu B. An additional focus in this study was to evaluate the performance of the current ILI case definition used by the DoD flu program. This definition is useful to identify individuals who are likely to be infected with influenza, as the ability to capture and characterize novel strains of influenza is an important component to this program. Better yields of influenza mean less time and money spent processing negative specimens.
Objective
This study describes clinical symptoms reported in conjunction with influenza, non-influenza respiratory viruses, and negative viral cultures from the Department of Defense (DoD) Global Influenza Surveillance Program; influenza-like illness (ILI) case questionnaires were linked to corresponding laboratory specimen results for the 2005-06 influenza season for analysis.
The syndromic surveillance system in Scotland was implemented in response to Gleneagles hosting the G8 summit in July 2005. Part of this surveillance system used data from NHS24, a nurse led telephone help line that is the means of access to out of hours general practice services for the Scottish population. This data was processed by the ERS system and reports generated for 10 syndromes considered relevant to possible bio-terrorism or disease outbreaks. These syndromes are; colds and flu, difficulty breathing, fever, diarrhoea, coughs, double vision, eye problems, rash, lumps and vomiting. Following the G8 summit the ERS has been updated weekly using data pre-catagorised into syndromes at NHS24 (known as protocolled data). The proportion of calls processed by the protocol at NHS24 over this time has however fallen to around 40%. This change has given the impetus to create a free text searching algorithm which can classify all calls received by NHS 24 into one of the 10 syndromes or “other”. This therefore allows all calls to be analysed by the ERS.
Objective
Public Health consultants at Health Protection Scotland (HPS) monitor routine data from the NHS24 telephone helpline to provide information on possible epidemics of flu or other infectious diseases in Scotland. Within this paper the exception reporting system run at HPS is described and the adaptations made to the classification system as a response to the change of data recording patterns at NHS24 are described.
Syndromic surveillance aims to decrease the time to detection of an outbreak compared to traditional surveillance methods. Emergency department (ED) syndromic surveillance systems vary in their methodology and complexity and are usually based on presenting chief complaints. Prior work in ED-based syndromic surveillance has shown conflicting results on agreement between chief complaint and discharge diagnosis, which may be syndrome-dependent. The use of ED discharge diagnosis may improve surveillance validity if it can be done in a timely fashion.
Objective
The purpose of this study is to characterize the relationship of emergency department chief complaint and final primary ICD-9 diagnosis assigned at the time of emergency department disposition for patients with symptoms and/or ICD-9 codes associated with influenza like illness (ILI) using an electronic medical record.
This study aims to evaluate the sensitivity, specificity and Positive Predictive Value (PPV) of body temperature measurements > 100.5 F in relationship to laboratory confirmation of influenza and other ILI pathogens.
Facing public health threats of bioterrorism and emerging infectious diseases (EID), the traditional passive surveillance system is not efficient and outmoded. Evidences reveal that several newly developed syndromic surveillance system (SSS) in different countries can provide an active, powerful, timely, and effective epidemiological investigation. Using this SSS, we can find non-specific symptoms, and set up baseline clinical data and epidemic threshold. Due to English barriers and standardized language problem in the past, we initiated to develop an emergency department-based syndromic surveillance system (ED-SSS) using clinical data involving both check-list format chief complaints (CoCo) and International Classification of Diseases, Ninth Revision (ICD-9) that best fit the situations in Taiwan.
Objective
The aims of this study are to set up a SSS for detecting newly EID outbreaks early using more standardized information of triage CoCo of hospital emergency department in metropolitan Taipei City to (1) break through Chinese language barrier; (2) investigate its feasibility to detect influenza like illness (ILI) outbreaks using integrated clinical and epidemiological information installed within information technology system; and (3) compare the sensitivity, specificity, and kappa value of ILI between ICD-9 and CoCo.
The Maryland Department of Health and Mental Hygiene conducts enhanced surveillance using the Electronic Surveillance System for Early Notification of Community-Based Epidemics (ESSENCE). The current version of ESSENCE for the National Capital Region consists of information from multiple data sources for syndromic surveillance in Maryland, Washington DC, and Virginia. Chief complaint data from emergency department (ED) visits and over-the-counter (OTC) medications are categorized into syndromes and alerts are generated when observed counts are outside the expected range. ESSENCE alerts users to unusual counts of a particular syndrome based on both temporal and spatial distribution for enhanced surveillance of disease activity. While several studies have examined the usefulness of ED data to detect the start of the influenza season, a lack of information exists on the usability of OTC sales to detect influenza. OTC data may provide an earlier alert to illness than other sources, if people self-treat with OTC medications.
Objective
This study examines the ability of syndromic surveillance data to detect seasonal influenza. ED visits for influenza-like illness and OTC flu medication sales are evaluated to determine whether these data sources are useful in the detection of the influenza season. Data sources that can detect seasonal influenza may also be used to help detect the start of pandemic influenza.
The 2003/04 influenza season included a more pathogenetic organism and had an earlier onset. There were noticeably more deaths in otherwise healthy children than in previous seasons. Following this season, States were asked by the Centers for Disease Control and Prevention to increase their surveillance efforts for influenza illness.
Objective
This paper describes data that was available in Ohio for analysis and considered valuable to determine the occurrence of influenza-like illness (ILI). These data sources were studied to determine their value to ILI surveillance and to develop an improved method of establishing influenza activity levels.
The threat of terrorism and high-profile disease outbreaks has drawn attention to public health syndromic surveillance systems for early detection of natural or man-made disease events. In this sense, the Miami-Dade County Health Department has implemented ESSENCE (Electronic Surveillance System for the Early Notification of Community-based Epidemics) in 2005; which has been developed and updated by the Johns Hopkins University.
Objective
This paper describes the dual monitoring process of Influenza-like Illness (ILI) syndrome in Miami-Dade County using the ESSENCE syndromic surveillance system, and their potential use as part of the seasonal influenza and pandemic influenza surveillance strategies.
The purpose of this study was to compare the 2005- 2006 and 2006-2007 Influenza seasons using Influenza-like illness (ILI) data received from Emergency Departments in Miami-Dade County.