Colanter Brit

Syndromic surveillance can provide early warning of potential public health emergencies and acute health events in a population. The sharing and aggregation of syndromic data among jurisdictions can provide more comprehensive situational awareness and improve coordination and decision-making. The BioSense 2.0 Program supports increased syndromic data-sharing among a nationwide network of local and state public health agencies. Most users of this application utilize the main web site front-door interface due to its user-friendly features for query and analysis. However, this interface currently has a limited number of analytic tools, export functions, and provides access only to binned data. The back-door interface, with access to additional data lockers containing raw and exception data, represents a potentially rich source of untapped and underutilized information. In this presentation, we discuss our ongoing development and early success of a capacity (consisting of code libraries, a parser, and an implementation guide) that allows users to tailor a program-specific, automated process for generating surveillance reports from their BioSense 2.0 data locker. The product will soon be available to members of the BioSense User Community.

Objective

The purpose of this project is to develop a capacity to facilitate implementation of a user-driven enhanced process for generating program-specific surveillance reports from BioSense 2.0 locker data.

Syndromic surveillance can be a useful tool for the early recognition of outbreaks and trends in emergency department (ED) data. In addition, as a more timely data source than traditional disease reporting, syndromic data may also be leveraged to identify individual disease cases, increasing the utility for first time or redundant case recognition.

San Diego County (COSD) performs daily ED syndromic surveillance. In order to assess the utility for early identification of specific conditions of public health interest (e.g., salmonellosis, meningitis, hazardous exposures, heat-related illness), a novel process entitled Priority Infectious Conditions Capture, was developed.

Objective

This paper describes an assessment of an enhanced surveillance process used to identify reportable diseases and conditions of public health importance from ED chief complaint data in COSD.

San Diego County Public Health has been conducting syndromic surveillance for the past few years. Currently, the system has become largely automated and processes and analyzes data from a variety of disparate sources including hospital emergency departments, 911 call centers, prehospital transports, and over-the-counter drug sales. What has remained constant since the system’s initial conceptualization is the local opinion that the data should be analyzed and interpreted in a variety of ways, in anticipation for the variety of contexts in which events that are of public health interest may unfold. Relatively small increases in volume that are sustained over time will likely be detected by methods designed to detect “small process shifts”, and include the CUSUM and EWMA methods. Larger increases in volume that are not sustained over time will likely be detected by other employed methods (P-Chart in the event of a non-proportional increase in volume, U-Chart in the event of a proportional increase in volume). A retrospective analysis was conducted on historical data from various data sources to determine the frequency of signals and detected events as well as the context within which the alert occurred (i.e., the “shape” of the data). Findings regarding several actual public health events will also be discussed.

Objective

This paper describes the frequency, various “shapes” and magnitudes of data anomalies, and varying ways actual public health events may present themselves in syndromic data.

With increasing availability of syndromic meaningful use data, new approaches to disease surveillance utilizing linkages to other data systems are possible. Expanded communicable disease information may be valuable during outbreaks or other public health emergencies. San Diego County is experiencing a significant and protracted hepatitis A outbreak. The disease has been transmitted person-to-person through close contact or through a fecally-contaminated environment, and has been primarily affecting homeless people and injection and non-injection illicit drug users. As of August 31, 2017, there were nearly 400 cases with 15 deaths. Approximately, 70% of the cases were hospitalized. This is one of the nation’s largest hepatitis A outbreaks since the introduction of the hepatitis A vaccine in 1995. Additional cases are expected over the next twelve months. The population affected by this outbreak presents some challenges for outbreak response. It is often a difficult population to reach. In addition, many have multiple comorbidities and often have health care seeking behaviors that differ from the general population. Using the medical record number (MRN) to link hepatitis A disease cases from the communicable disease registry to syndromic HL7 messages for emergency department visits and hospitalizations enabled the identification of additional hospital encounters the cases may have had before, during, or following their hepatitis A disease incident. This allowed an exploration of the ways in which this unique population interacted with the health care system in the context of a communicable disease outbreak. This presentation will highlight the steps to link information across surveillance systems, the results, the challenges, and the benefits of linked information to public health departments.

Objective:

To describe how the County of San Diego linked information from a communicable disease registry and syndromic surveillance system to further describe cases associated with a large hepatitis A outbreak. Specifically, to detail the linkage process which resulted in a longitudinal understanding of individuals’ hospital visits before, during, and after the reported hepatitis A incident.