Trends

The Veterans Health Administration (VHA) is the VA organization responsible for providing healthcare to over 5 million patients annually at 153 medical centers and over 900 outpatient clinics across the United States and U.S. territories. The VA Subject Matter Expertise Center for Biological Events (SMEC-bio) aims to leverage data in the extensive VHA electronic health records system and other sources to provide decision support to leadership for emerging infectious disease threats. Initial SMEC-bio work to examine this capability suggested that the increased incidence of dengue disease in the VHA patient population in PR in 2010 may be related to increased rainfall (see reference). This present work analyzes dengue incidence in the PR VHA patient population over time to understand disease trends and contribute to a framework for predictive analysis. This paper describes trend analyses of dengue and dengue-like illness in VHA patient data in Puerto Rico (PR) with the goal of developing mechanisms for improved early warning and situational awareness of infectious disease threats.

The CDC recently developed sub-syndromes for classifying disease to enhance syndromic surveillance of natural outbreaks and bioterrorism. They have developed ICD9 classifiers for six GI Illness subsyndromes: Abdominal Pain, Nausea and Vomiting, Diarrhea, Anorexia, Intestinal infections, and Food poisoning. If the number of visits for sub-syndromes varies significantly by age it may impact the design of outbreak detection methods.

Objective

We hypothesized that the percentage of visits for the GI sub-syndromes varied significantly with age.

Objective

To study if syndromic surveillance would have an added value over existing surveillance systems, we retrospectively evaluated whether known trends in respiratory pathogens are reflected in medical registrations in the Netherlands when using respiratory syndrome groupings.

In addition to utilizing syndromic surveillance data to respond to public health threats and prepare for major incidents, local health departments can utilize the data to examine patient volumes in the emergency departments (EDs) of local hospitals. The information obtained may be valuable to hospital and clinic administrators who are charged with allocating resources. 

Indianapolis represents 92% of Marion County’s population. The county’s public hospital and clinic network provide care for 1 in 3 county residents who are Medicaid enrollees or uninsured. To assess the need for extended hours at eight public primary care clinics in Marion County, Indiana, this study examined the hospital’s ED volume. We hypothesize that

changes in the ED volume trends that corresponded to the start or end of usual clinic hours (8am-5pm) would be evidence of clinic hours’ impact on ED use.

Objective

This paper highlights the use of syndromic surveillance data to examine daily trends in ED volume at an urban public hospital.

Centre for Health Protection (CHP) plans to conduct a pilot project in developing a syndromic surveillance system using data from Emergency Departments (ED) in Hong Kong. This is part of the Communicable Disease Information System initiative, which aims at enhancing the capability of Hong Kong in the control and prevention of communicable diseases.

Objective

This paper describes how the CHP of Hong Kong designed and deployed an online interactive system that uses the data from ED for syndromic surveillance.

Objective

Understanding the baseline dynamics of syndrome counts is essential for use in prospective syndromic surveillance. Therefore we studied to what extent the known seasonal dynamics of gastro-intestinal (GI) pathogens explain the dynamics in GI syndrome in general practitioner and hospital data.

 

Complex, highly parameterized data models are often used to detect syndromic outbreaks. Unfortunately, such models can pose greater maintenance challenges as parameter variations increase. As such, our work focuses on whether day-of-the-week (DoW) effects may (or may not) show little variation across hospitals.

Objective

This paper investigates the existence of the DoW effect across twenty-six hospitals within the Indiana Public Health Emergency Surveillance System. We will consider both the impact of each DoW and the impact of individual hospitals.

Crude mortality could be valuable for infectious disease surveillance if available in a complete and timely fashion. Syndromic surveillance with weekly deaths has been demonstrated to be useful in France. Such data can be of use for detecting, and tracking the impact, of unusual health events (e.g. pandemic influenza) or other unexpected or unknown events of infectious nature. To evaluate whether these aims can be achieved with crude mortality monitoring in the Netherlands, we investigated trends in death notifications and we tested whether retrospective crude mortality trends, at different days of delay, reflect known trends in infectious pathogens that are associated with death (such as influenza).

Objective

To evaluate the potential of mortality data in the Netherlands for real-time surveillance of infectious events.

During influenza season, the Boston Public Health Commission uses syndromic surveillance to monitor Emergency Department visits for chief complaints indicative of influenza-like illness (ILI). We created three syndrome definitions for ILI to capture variable presentations of disease, and compared the trends with Boston pneumonia and influenza mortality data, and onset dates for reported cases of influenza.

Objective

To evaluate the impact of different syndrome definitions for ILI by comparing weekly trends with other data sources during the 2005-2006 influenza season in Boston.