Staes CJ

Public health informatics is an emerging interdisciplinary field that uses information technology and informatics methods to meet public health goals. To achieve these goals, education and training of a new generation of public health informaticians is one of the essential components. AMIA0 s 10 ! 10 program aims to realize the goal of training 10,000 health care professionals in applied health and medical informatics by the year 2010.1 The Department of Biomedical Informatics of the University of Utah was established in 1964. As one of the largest biomedical informatics training programs in the world, the department is internationally recognized as a leader in biomedical informatics research and education.2 The poster hereby describes the collaborative effort between Utah and AMIA to develop a public health informatics online course.

Objective

This poster describes the development and delivery of an online American Medical Informatics Association (AMIA) 10 ! 10 Public Health Informatics course at the University of Utah.

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-ofcare rapid influenza testing in an outpatient, setting for the identification of the onset of influenza in the community