Evaluation

Michigan has been collecting chief complaint data from emergency departments statewide to support situational awareness activities related to communicable disease since 2004. We validated the syndromic system by comparing the chief complaint data to the electronic medical records of a tertiary hospital in southeast Michigan to better understand the utility of the system for noncommunicable disease situations.

Objective

Validation of the syndromic system by comparing the chief complaint data to the electronic medical records (EMR) of a tertiary hospital.

After the major impact of the 2003 heat wave, France needed a reactive, permanent and national surveillance system enabling to detect and to follow-up various public health events all over the territory including overseas. In June 2004, the French syndromic surveillance system based on the emergency department (ED) has been implemented by the national institute for public health surveillance (InVS). Beginning with 23 ED in 2004, the network has progressively included new ED and several steps have contributed to accelerate this permanent increase. A first evaluation of this data source was conducted for the specific surveillance of heat wave.

Objective

Implemented 10 years ago, the French emergency department surveillance system (Oscour Network) has been assessed using four major evaluation criteria in syndromic surveillance: stability, coverage, data quality and utility.

A simplified syndromic surveillance system, based on early detection and reporting of four core syndromes and immediate reporting of unusual events, was established across PICTs in 2010. An early evaluation of the system was undertaken to make recommendations on improvements. The evaluation examined whether the system was meeting its objective of serving as an early warning system and its capacity to investigate and respond to outbreaks. Metrics included system acceptability, data quality, timeliness and level of compliance. The evaluation identified a critical need to better equip local public health officials with the knowledge and skills to rapidly and appropriately respond to suspected infectious disease outbreaks across the Pacific.

In response to the evaluation findings, the RAPID (Response and Analysis for Pacific Infectious Diseases) project was implemented to strengthen capacity in surveillance, epidemiology and outbreak response across the PICTs. Principally funded by Australian aid and developed in partnership with the World Health Organization (WHO), the Secretariat of the Pacific Community (SPC) and the Pacific Public Health Surveillance Network (PPHSN), RAPID is an example of a multi-organisational approach to swiftly address identified surveillance issues and strengthen regional surveillance capacity.

Objective

Surveillance evaluations should not only describe surveillance systems but provide evidence to improve public health practice. This presentation documents how knowledge gathered through a syndromic surveillance evaluation in Pacific Island Countries and Territories (PICTs) with local health personnel was translated into action, in collaboration with global health partners.

The Research Electronic Data Capture (REDCap) application has been used to build and manage online surveys and databases in academic research settings. Public health agencies have begun to use REDCap to manage disease outbreak data. In addition to survey and database development, and data management and analysis, REDCap allows users to track data manipulation and user activity, automate export procedures for data downloads, and use ad hoc reporting tools and advanced features, such as branching logic, file uploading, and calculated fields. REDCap supports HIPAA compliance through userbased permissions and audit trails. These additional capabilities may provide an advantage over commonly used outbreak management tools such as Epi Info and Microsoft Access. The Illinois Department of Public Health (IDPH) has not used REDCap to date. Prior to adopting this web-based application, an evaluation was conducted to assess how REDCap may facilitate outbreak data management.

Objective

To evaluate the use of the Research Electronic Data Capture (REDCap) application to manage outbreak data at the local, state, and multi-jurisdictional level.

 

The National Strategy for Biosurveillance promotes a national effort to improve early detection and enable ongoing situational awareness of all-hazards threats. Implicit in the Strategy’s implementation plan is the need to upgrade capabilities and integrate multiple disparate data sources, including more complete electronic health record (EHR) data into future biosurveillance capabilities. Thus, new biosurveillance applications are clearly needed. Praedico™ is a next generation biosurveillance application that incorporates cloud computing technology, a Big Data platform utilizing MongoDB as a data management system, machine-learning algorithms, geospatial and advanced graphical tools, multiple EHR domains, and customizable social media streaming from public health-related sources, all within a user friendly interface.

Objective

The purpose of our study was to conduct an initial assessment of the biosurveillance capabilities of a new software application called Praedico™ and compare results obtained from previous queries with the Electronic Surveillance System for the Early Notification of Community-Based Epidemics (ESSENCE).

 

An electronic smart-card based school absenteeism surveillance system was introduced to Hong Kong since 2008. The pilot surveillance system initially began with 18 schools in 2008, and expanded to 107 schools in the current academic year of 2013-14. Data on all-cause absenteeism were collected from all participating schools and absenteeism due to sickness such as influenza-like illness, gastroenteritis and hand-foot-and-mouth disease were collected from 39 (36.4%) schools. Data collected were aggregated for the whole territory on a weekly basis for analysis. Temporal trend of influenza activity was disseminated with simple public health advice to each participating schools and the general public through a web-based dashboard [1]. These steps of data aggregation, analysis, and feedback report generation were automated by scripts in the software R which enhanced the timeliness and minimized workload required for maintaining the system.

Objective

This study evaluated the performance of an electronic smart-card based school absenteeism system in Hong Kong, 2008-2014.

In Mozambique about 10% of deaths in children are due to ARI. Although influenza (Flu) virus may be implicated in these infections, little is known about the circulation of this virus in the country. Thus, Mozambique implemented the influenza surveillance based on sentinel sites, facing a great challenge due to several factors. One of them is the proper influenza case definition along with others challenges since its international standardization is difficult. In order to get insights to the epidemiology of flu we reviewed the first year of surveillance implementation monitoring data to improve procedures.

Objective

Analyse challenges of the first year of surveillance implementation in Mozambique, according to samples income, hospital staff performance and available tools.

Compare two influenza surveillance approaches

The Florida Department of Health electronically receives hospital emergency department (ED) data from 180 EDs located in 54 of its 67 counties through its Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE-FL). Florida EDs have begun to offer self-registration options to patients, which include ED self check-in kiosks, and pre-visit registration smartphone applications and websites. ESSENCE-FL receives ED data from multiple hospitals that use these patient self-registration methods. To date, limited investigation has been carried out to determine the impact of these self-registration methods on the data submitted to ESSENCE-FL. This project investigates and describes how SS data are affected by these options and provides possible best practices for identifying and analyzing these data.

Objective

To assess the effect of patient self-registration methods in hospital emergency departments on data in a syndromic surveillance (SS) system and provide suggestions for analysis of these data.

The LAC SSS has been in existence since 2004. Currently, the system collects data from over 50 hospitals daily and performs a chief complaint-based syndrome classification analysis of all ED visits. The keyword “fever” is of special interest due to its inclusion within several syndrome category definitions such as influenza, meningitis, etc. However, inclusion of such terms in syndrome definitions may be a disadvantage as such keyword searches would depend upon the consistency in which the term “fever” is reported. In 2014, several LAC syndromic surveillance hospital data connections were upgraded to include notes recording patient body temperature. To evaluate the newly added temperature information, analyses were conducted on those observations that included body temperature, chief complaint, and diagnosis information.

Objective

The Los Angeles County (LAC) Emergency Department (ED) Syndromic Surveillance System (SSS) classifies patients into syndrome categories based on stated chief complaints. In an effort to evaluate the accuracy of patient- stated chief complaints and final diagnoses, both “fever” chief complaints and diagnoses were compared with patient body temperature readings.