Loschen Wayne

To date, most syndromic surveillance systems rely heavily on complicated statistical algorithms to identify aberrations. The assumption is that when the statistics identify something unusual, follow-up should occur. However, with multiple strata analyzed, small numbers for some strata, and wide variances in daily counts, the statistical algorithms will generate flags too often. Experience has shown that these flags usually have little or no public health significance. As a result, syndromic surveillance systems suffer from the ‘boy who cried wolf’ syndrome. It is clear that the analyst’s ability to use professional judgment to sift through multitudes of flags is very important to the success of the system, which suggests that statistics alone cannot identify issues of public health importance from ED data.

Objective

This study's aim was to refine an automated biosurveillance system in order to better suit the daily monitoring capabilities and resources of a health department.

Versatile, user-friendly visualization tools are required to organize the wealth of information available to users of large, regional surveillance systems into a coherent view of population health status. Communications components must allow multiple users of the same system to share information about the health of their populations in an organized fashion and facilitate communications among jurisdictions.

The Johns Hopkins University Applied Physics Laboratory has developed a communications tool to be used within the regional disease surveillance system in the National Capital Region. This abstract describes this new communications component that is designed to encourage and facilitate communication between multiple jurisdictions using a common surveillance system.

Objective

The objective is to create a capability within an existing regional disease surveillance system that allows event information to be shared easily, thoroughly, and in a timely manner, while gathering the knowledge needed to improve the entire system in the future. The functionality of this communication component must balance the utility of immediate situational awareness with the long term benefits of capturing critical information, such as system usage patterns and user response behavior, which can be used to develop future system enhancements. 

Advanced surveillance systems require expertise from the fields of medicine, epidemiology, biostatistics, and information technology to develop a surveillance application that will automatically acquire, archive, process and present data to the user. Additionally, for a surveillance system to be most useful, it must adapt to the changing environment in which it operates to accommodate emerging public health events that could not be conceived of when the initial system was developed.

Objective

The objective of this presentation is to describe both within-discipline and across-discipline changes to standard methods and operating procedures that must be adopted to achieve automated systems that will be an effective complement and extension to traditional disease surveillance. This presentation describes adaptations already in place, as well as those still needed to rapidly recognize and respond to public health emergencies.

Regional disease surveillance systems allow users the ability to view large amounts of population health information and examine automated alerts that suggest increased disease activity. These systems require users to view and interpret which of these alerts or data streams are epidemiologically important. This interpretation is valuable information that may benefit other users. In addition to the daily interpretation of data done by users, the ability to communicate local concerns and findings during a public health event to neighboring jurisdictions is of great public health importance. Public health officials also need constant situational awareness and a venue to share their concerns about increases in disease activity before a health emergency is declared. The Event Communications Component (ECC) was created to provide this venue. The ECC was developed for the National Capital Region (NCR) public health surveillance network to facilitate the need for users to communicate. The NCR system is an operational multi-jurisdictional biosurveillance system employed in the District of Columbia and in surrounding Maryland and Virginia counties. NCR users include epidemiologists and public health officials from different levels of government. The ECC has been in operation for a year in the NCR system. ECC 2.0 is being developed to improve on the original version’s capabilities and solve its shortcomings.

 

Objective

Identify areas of improvement and establish design goals of ECC 2.0. These design goals include: the incorporation of comment centric design versus event centric, automatic notification of new events/comments, the use of action oriented concern levels and user interface improvements. Focus design goals by utilizing prototyping and user group reviews. Develop ECC 2.0 and integrate it into the NCR system.

We evaluated several classifications of emergency department (ED) syndromic data to ascertain best syndrome classifications for ILI.

In order to be best prepared to identify health events using electronic disease surveillance systems, it is vital for users to participate in regular exercises that realistically simulate how events may present in their system following disease manifestation in the community. Furthermore, it is necessary that users exercise methods of communicating unusual occurrences to other intra and extra-jurisdictional investigators quickly and efficiently to determine first, if an event actually exits and if one does its characteristics. A simulation exercise held in the National Capital Region (NCR) in the spring of this year exercised a novel format for engaging users while testing the utility of an embedded event communication tool.

Objective

This is a description of an innovative design and format used to exercise public health preparedness in a tri-jurisdictional disease surveillance system in the spring of 2006.

Automated disease surveillance systems that analyze data by syndrome categories have been used to look for outbreaks of disease for about 10 years. Most of these systems notify users of increases in the prevalence of reports in syndrome categories and allow users to view patient level data related to the increase. For most situations this level of investigation is sufficient, but occasionally a more dynamic level of control is required to properly understand an emerging illness in a community. During the SARS outbreak, for example, the respiratory syndrome was defined too broadly to allow users to track SARS. However, some systems, allowed users to build dynamic queries that allowed them to search their data by using the SARS case definition [1]. Users could perform free-text queries that identified records containing specific keywords in the chief complaint or specific combinations of ICD9 codes. This advanced querying capability has proven to be one of the most used features used by monitors of disease surveillance systems. Objective: The objective of this project is to build a new, more flexible query interface that allows users to define and build their query as if they were writing a logical expression for a mathematical computation. The interface is designed so that it can be easily adapted to fit into nearly any syndromic surveillance system.The interface will be evaluated in future versions of the ESSENCE and BioSense Systems.