Automated Real-Time Surveillance Using Health Indicator Data Received at Different Time Intervals

The Johns Hopkins Applied Physics Laboratory and the Armed Forces Health Surveillance Center have developed a hybrid processing engine that alerts monitors when a severe health condition exists based on corroboration among several sources of data. The system was designed to ingest a day’s worth of recent data and provide results to monitors daily. In some theaters, the health of the US Forces must be determined at near-real time rates requiring a reassessment of current surveillance practices.

August 22, 2018

Using Cloud Technology to Support Monitoring During High Profile Events

Hospital emergency departments in Cook and surrounding counties currently send data to the Cook County Department of Public Health (CCDPH) instance of ESSENCE on CCDPH servers. The cloud instance of ESSENCE has been enhanced to receive and export all meaningful use data elements in the meaningful use format. The NATO summit provided the opportunity for a demonstration project to assess the ability of an Amazon GovCloud instance of ESSENCE to ingest and process meaningful use data, and to export meaningful use surveillance data to the Cook County Locker in BioSense 2.0.

July 06, 2018

Establishing a Federal and State Data Exchange Pilot for Public Health Situational Awareness

ASPR deploys clinical assets, including an EMR system, to the ground per state requests during planned and no-notice events. The analysis of patient data collected by deployed federal personnel is an integral part of ASPR and FDOH’s surveillance efforts. However, this surveillance can be hampered by the logistical issues of field work in a post-disaster environment leading to delayed analysis and interpretation of these data to inform decision makers at the federal, state, and local levels.

March 19, 2018

Evaluation of ESSENCE in the Cloud Using Meaningful Use Syndromic Surveillance Data

In November of 2011 BioSense 2.0 went live to provide tools for public health departments to process, store, and analyze meaningful use syndromic surveillance data. In February of 2012 ESSENCE was adapted to support meaningful use syndromic surveillance data and was installed on the Amazon GovCloud. Tarrant County Public Health Department agreed to pilot the ESSENCE system and evaluate its performance compared to a local version ESSENCE they currently used.

May 14, 2018

Operational Experience: Integration of ASPR Data into ESSENCE-FL during the RNC

Florida has implemented various surveillance methods to augment existing sources of surveillance data and enhance decision making with timely evidence based assessments to guide response efforts post-hurricanes. Historically, data collected from deployed federal assets have been an integral part of this effort.

July 09, 2018

Essential Requirements for Effective Advanced Disease Surveillance

Advanced surveillance systems require expertise from the fields of medicine, epidemiology, biostatistics, and information technology to develop a surveillance application that will automatically acquire, archive, process and present data to the user. Additionally, for a surveillance system to be most useful, it must adapt to the changing environment in which it operates to accommodate emerging public health events that could not be conceived of when the initial system was developed.

 

Objective

July 30, 2018

Support Vector Machines for Syndromic Surveillance

Early and reliable detection of anomalies is a critical challenge in disease surveillance. Most surveillance systems collect data from multiple data streams but the majority of monitoring is performed at univariate time series level. Purely statistical methods used in disease surveillance look at each time series separately and tend to generate a large number of false alarms. Support Vector Machines can be used to develop rich multivariate models that allow detecting abnormal relationships between different time series leading to greatly reduced number of false alarms.

 

July 30, 2018

Translational Research for Surveillance

Presented January 28, 2008

January 26, 2019

Synthesizing the American Health Information Community's Minimum Data Set

The objectives of this presentation are to describe the need for synthetic data containing the elements of the American Health Information Communityís (AHIC) Minimim Data Set (MDS). Approaches for creating synthetic data with MDS data elements will be presented and methods for insuring maintenance of confidentiality will be discussed.

July 30, 2018

A Simple Method of Using Linked Health Data in Syndromic Surveillance

This paper describes a simple technique for utilizing linked health information in syndromic surveillance. Using knowledge of which patient encounters resulted in laboratory test requests and prescriptions may improve sensitivity and specificity of detection algorithms.

July 30, 2018

Pages

Contact Us

INTERNATIONAL SOCIETY FOR
DISEASE SURVEILLANCE

288 Grove Street, Box 203
Braintree, MA 02184
(617) 779 0880
Email:syndromic@syndromic.org

This Knowledge Repository is made possible through the activities of the Centers for Disease Control and Prevention Cooperative Agreement/Grant #1 NU500E000098-01, National Surveillance Program Community of Practice (NSSP-CoP): Strengthening Health Surveillance Capabilities Nationwide, which is in the interest of public health.

Site created by Fusani Applications