Infectious Disease

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

Under leadership of the Secretary of Veterans Affairs (VA), Office of Operations, Security and Preparedness has established the Veterans Affairs Integrated Operations Center, with the goal of enhancing integration and analysis of data, and information from VA’s preparedness partners, both internal and external, for timely decision support. The Office of Operations, Security and Preparedness oversee emergency preparedness for the VA, which includes responsibility for preparedness activities at Veterans Health Administration (VHA). The VHA provides medical care to over 5 million patients a year at 153 medical centers, and over 900 outpatient clinics in the United States, and the United States territories. The Office of Operations, Security and Preparedness is developing a VA–Subject Matter Expertise Center for Biological Events in collaboration with the VHA–National Infectious Diseases Program Office. The Subject Matter Expertise Center for Biological Events is initiating pilot projects to examine data sources, integration, and predictive analysis. The recent increase in dengue cases internationally prompted the Office of Operations, Security and Preparedness, and the Subject Matter Expertise Center for Biological Events to establish collaborations, and investigate factors influencing dengue disease patterns in VHA facilities. The National Weather Service has the mission to provide weather, water and climate data, forecasts and warnings for the protection of life and property, and enhancement of the national economy. The Veterans Affairs Integrated Operations Center enabled collaboration with the National Weather Service for integration of weather, water and climate data, and retrospective analysis into preparedness activities.

Objective

The objective of this study is to describe Veterans Affairs Integrated Operations Center-enabled collaborations to enhance the synergy of relevant data/information from Veterans Affairs (VA) and non-VA partners for improved early warning, and situational awareness of infectious disease threats.

The American Health Information Community Harmonized Use Case for the Biosurveillance minimum data set (MDS) was implemented to establish data exchange between regional health information organizations (RHIOs) and the New York State Department of Health (NYSDOH) for accelerating situational awareness through the Health Information Exchange (HIE) Project. However, the completeness, timeliness of the reporting and quality of data elements in the MDS through RHIOs are still unknown and need further validation before we can utilize them for NYSDOH public health surveillance.

Objective

Evaluate the availability, timeliness, and accuracy of MDS data elements received from one RHIO for emergency department (ED), in-patient, and outpatient visits. Compare the characteristics of patients meeting the HIE influenza-like illness definition who were admitted to the hospital or expired versus those discharged home.

Current influenza-like illness monitoring in Idaho is on the basis of syndromic surveillance using laboratory data, combined with periodic person-to-person reports collected by Idaho state workers. This system relies on voluntary reporting. Electronic medical records with relational databases offer a method of obtaining data in an automated fashion. Clinical data entered in CPRS includes real-time visit information, vital signs, ICD-9, pharmacy, and labs. ICD-9 and vital signs have been used to predict influenza-like illness in automated systems. We sought to combine these with lab and pharmacy data as part of an automated syndromic surveillance system.

Objective

The objective of this paper is to study whether syndromic surveillance using data from the Veterans Administration electronic medical record computerized patient record system (CPRS) correlates to officially reported influenza activity levels in the State of Idaho.