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Gibbs Gillian

Description

Processing free-text clinical information in an electronic medical record (EMR) may enhance surveillance systems for early identification of ILI outbreaks. However, processing clinical text using NLP poses a challenge in preserving the semantics of the original information recorded. In this study, we discuss several NLP and technical issues as well as potential solutions for implementation in syndromic surveillance systems.

Objective

To review the natural language processing (NLP) and technical challenges encountered in an automated influenza-like illness (ILI) surveillance system.

Submitted by teresa.hamby@d… on
Description

Clinical quality measures (CQMs) are tools that help measure and track the quality of health care services. Measuring and reporting CQMs helps to ensure that our health care system is delivering effective, safe, efficient, patient-centered, equitable, and timely care. The CQM for influenza immunization measures the percentage of patients aged 6 months and older seen for a visit between October 1 and March 31 who received (or reports previous receipt of) an influenza immunization. Centers for Disease Control and Prevention recommends that everyone 6 months of age and older receive an influenza immunization every season, which can reduce influenzarelated morbidity and mortality and hospitalizations.

Objective

To explain the utility of using an automated syndromic surveillance program with advanced natural language processing (NLP) to improve clinical quality measures reporting for influenza immunization.

Submitted by Magou on
Description

The primary goal of syndromic surveillance is early recognition of disease trends, in order to identify and control infectious disease outbreaks, such as influenza. For surveillance of influenza-like illness (ILI), public health departments receive data from multiple sources with varying degrees of patient acuity, including outpatient clinics and emergency departments. However, the lack of standardization of these data sources may lead to varying baseline levels of ILI activity within a local area.

Objective

To examine the baseline influenza-like illness (ILI) rates in the emergency departments (ED) of a large academic medical center (AMC), community hospital (CH), and neighboring adult and pediatric primary care clinics.

Submitted by Magou on
Description

In 2016, the World Health Organization declared Zika virus a global public health emergency. Zika infection during pregnancy can cause microcephaly and other fetal brain defects. To facilitate clinicians’ ability to detect Zika, various syndrome definitions have been developed. 

Objective

To develop and validate a Zika virus disease syndrome definition within the GUARDIAN (Geographic Utilization of Artificial Intelligence in Real-Time for Disease Identification and Alert Notification) surveillance system.

Submitted by teresa.hamby@d… on