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Staes Catherine

Description

Influenza causes significant morbidity and mortality, with attendant costs of roughly $10 billion for treatment and up to $77 billion in indirect costs annually. The Centers for Disease Control and Prevention conducts annual influenza surveillance, and includes measures of inpatient and outpatient influenza-related activity, disease severity, and geographic spread. However, inherent lags in the current methods used for data collection and transmission result in a one to two weeks delay in notification of an outbreak via the Centers for Disease Control and Prevention’s website. Early notification might facilitate clinical decision-making when patients present with acute respiratory infection during the early stages of the influenza outbreak. 

In the United States, the influenza surveillance season typically begins in October and continues through May. The Utah Health Research Network has participated in Centers for Disease Control and Prevention’s influenza surveillance since 2002, collecting data on outpatient visits for influenza-like illness (ILI, defined as fever of 100F or higher with either cough or sore throat). Over time, Utah Health Research Network has moved from data collection by hand to automated data collection that extracts information from discrete fields in patients’ electronic health records.

We used statistical process control to generate surveillance graphs of ILI and positive rapid influenza tests, using data available electronically from the electronic health records. 

 

Objective

The objective of this study is to describe the use of point-of-care rapid influenza testing in an outpatient, setting for the identification of the onset of influenza in the community. 

Submitted by hparton on
Description

Surveillance of deaths due to influenza and pneumonia using death records has the potential to be a relatively inexpensive and quick approach to tracking and detecting influenza and respiratory illness outbreaks; however, presently such a system does not exist because of the time delays in processing death records: in Utah, as is similar elsewhere in the United States, coded death certificate data are typically not available for at least 1–3 months after the date of death, and coded national vital statistics data are not available until after 2–3 years.

Objective

This poster presents the rationale for designing a real-time surveillance system, based on mortality data, using grid and natural language processing tools that will address the current barrier that coded death certificate data not being available for several months. To develop a public health tool that delivers a timely surveillance system for influenza and pneumonia, we integrated death certificates from the Utah Department of Health, analytical grid services, and natural language processing tools to monitor levels of mortality. This example demonstrates how local, state, and national authorities can automate their influenza and pneumonia surveillance system, and expand the number of reporting cities.

Submitted by uysz on
Description

State laws mandate clinicians and laboratories to report occurrences of reportable diseases to public health entities. For this purpose, a set of case-reporting specifications are published and maintained by public health departments. There are several problems with the existing case-reporting specifications: (1) they are described on individual state websites and posters and not structured or executable; (2) the specifications are often misleading representing case classification rather than case reporting criteria; (3) they vary across jurisdictions and change over time; and (4) reporting facilities are required to interpret the criteria and maintain logic in their own systems. To overcome these problems, we are designing and developing a prototype system to represent case-reporting specifications that can be authored and maintained by public health and published openly.

 

Objective

In this paper, we describe the content and functional requirements for a knowledge management system that can be authored by public health authorities to inform reporting facilities ‘what’s reportable where’.

Submitted by hparton on
Description

When a reportable condition is identified, clinicians and laboratories are required to report the case to public health authorities. These case reports help public health officials to make informed decisions and implement appropriate control measures to prevent the spread of disease. Incomplete or delayed case reports can result in new occurrences of disease that could have been prevented. To improve the disease reporting and surveillance processes, the Utah Department of Health is collaborating with Intermountain Healthcare and the University of Utah to electronically transmit case reports from healthcare facilities to public health entities using Health Level Seven v2.5, SNOMED CT, and LOINC. As part of the Utah Center of Excellence in Public Health Informatics, we conducted an observation study in 2009 to identify metrics to evaluate the impact of electronic systems. We collected baseline data in 2009 and in this paper we describe preliminary results from a follow-up study conducted in 2010.

 

Objective

This paper describes a comparison study conducted to identify quality of reportable disease case reports received at Salt Lake Valley health department in 2009 and 2010.

Submitted by hparton on
Description

School absenteeism data could be used as an early indicator for disease outbreaks. The increase in absences, however, may be driven by non-sickness related factors. Reason for absence combined with syndrome-specific information might make absenteeism data more useful for early outbreak detection.

 

Objective

This is a pilot evaluation to determine the usefulness of syndrome-specific school absenteeism data for public health surveillance systems.

Submitted by elamb on