ESSENCE: Free Text Query Negation

Free text queries are performed by ESSENCE users very often. And increasingly, those free text queries are incorporating negation terms that allow the users to find case definitions when certain terms are not present. This video attempts to explain some of the special cases where negation in free text queries may be confusing for users. The video will mention some features in ESSENCE that you may not be familiar with like the Explain Query button and Advanced Query Tool (AQT).

November 29, 2018

Opioid Overdose Ambulance Runs: How Wisconsin Uses Free Text Data

In 2016, twelve states received Center for Disease Control and Prevention (CDC) Enhanced State Opioid Overdose Surveillance grants. The purpose of the grant is to explore enhanced data sources to track nonfatal opioid overdoses. One data source is ambulance runs. Wisconsin collects ambulance run information within the Wisconsin Ambulance Runs Data System (WARDS). Around 84% of all Wisconsin administrative services report into this electronic system.

January 25, 2018

Automatically tracking diabetes using information in physicians’ notes

Patient consultations recorded as voice dictations are frequently stored electronically as transcriptions in free text format. The information stored in free text is not computer tractable. Advances in artificial intelligence permit the conversion of free text into structured information that allows statistical analysis.

 

Objective

June 18, 2019

Challenges in adapting an natural language processing system for real-time surveillance

We are developing a Bayesian surveillance system for realtime surveillance and characterization of outbreaks that incorporates a variety of data elements, including free-text clinical reports. An existing natural language processing (NLP) system called Topaz is being used to extract clinical data from the reports. Moving the NLP system from a research project to a real-time service has presented many challenges.

 

Objective

Adapt an existing NLP system to be a useful component in a system performing real-time surveillance.

June 18, 2019

Automated Monitoring of Exposures Using the BioSense System

BioSense is a national automated surveillance system designed to enhance the nation's capability to rapidly detect and quantify public health emergencies, by accessing and analyzing diagnostic and prediagnostic health data. The BioSense system currently receives near real-time data from more than 540 civilian hospitals, as well as national daily batched data from over 1100 Department of Defense and Veterans Affairs medical facilities. BioSense maps chief complaint and diagnosis data to 11 syndromes and 78 sub-syndromes.

July 30, 2018

Detecting Web Rumours with a Multilingual Ontology-Supported Text Classification System

Timely surveillance of disease outbreak events of public health concern currently requires detailed and time consuming manual analysis by experts. Recently in addition to traditional information sources, the World Wide Web has offered a new modality in surveillance, but the massive collection of multilingual texts which must be processed in real time presents an enormous challenge.

 

Objective

July 30, 2018

Development of an Integrated Surveillance System for Beijing

After the SARS outbreak in 2003, Beijing established Fever Clinics in major hospitals for the early detection of potential respiratory disease outbreaks. The data collection in Fever Clinics contains the basic patient information, body temperature, cough, and breath condition, as well as a primary diagnosis. Since the symptoms and diagnosis are mainly recorded in free text format, it is very difficult to use for data analysis. Because of the problems in data processing, the data collection has decreased.

 

Objective

July 30, 2018

Automated Detection of GI Syndrome using Structured and Non-Structured Data from the VA EMR

Objective

We performed a gold-standard manual chart review for gastro-intestinal syndrome to evaluate automated detection models based on both structured and non-structured data extracted from the VA electronic medical record.

July 30, 2018

The Performance of a NGram Classifier for Patients' Chief Complaint Based on a Computerized Pick List Entry and Free Text in an Italian Emergency Department

Syndromic surveillance of emergency department (ED) visit data is often based on computer algorithms which assign patient chief complaints (CC) and ICD code data to syndromes. The triage nurse note (NN) has also been used for surveillance. Previously we developed an “NGram” classifier for syndromic surveillance of ED CC in Italian for detection of natural outbreaks and bioterrorism. The classifier is developed from a set of ED visits for which both the ICD diagnosis code and CC are available by measuring the associations of text fragments within the CC (e.g.

July 30, 2018

Enhanced Surveillance Improved Timeliness and Sensitivity at the FIFA 2006 World Cup in Germany

Security threats and the recent emergence of avian influenza in Europe have heightened the profile of and need for a good surveillance strategy during such events. The two main rationales for enhanced infectious disease surveillance at mass events include a perceived increased risk of infectious disease events and a need to detect and respond to events more quickly.

March 26, 2019

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