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Johnson Jeffrey

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.

Submitted by knowledge_repo… on

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.

Referenced File
Submitted by elamb on

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.

Referenced File
Submitted by elamb on

Twelve years into the 21st century, after publication of hundreds of articles and establishment of numerous biosurveillance systems worldwide, there is no agreement among the disease surveillance community on most effective technical methods for public health data monitoring. Potential utility of such methods includes timely anomaly detection, threat corroboration and characterization, follow-up analysis such as case linkage and contact tracing, and alternative uses such as providing supplementary information to clinicians and policy makers. Several factors have impeded establishment of analytical conventions. As immediate owners of the surveillance problem, public health practitioners are overwhelmed and understaffed. Goals and resources differ widely among monitoring institutions, and they do not speak with a single voice. Limited funding opportunities have not been sufficient for cross-disciplinary collaboration driven by these practitioners. Most academics with the expertise and luxury of method development cannot access surveillance data. Lack of data access is a formidable obstacle to developers and has caused talented statisticians, data miners, and other analysts to abandon the field. The result is that older research is neglected and repeated, literature is flooded with papers of varying utility, and the decision-maker seeking realistic solutions without detailed technical knowledge faces a difficult task. Regarding conventions, the disease surveillance community can learn from older, more established disciplines, but it also poses some unique challenges. The general problem is that disease surveillance lies on the fringe of disparate fields (biostatistics, statistical process control, data mining, and others), and poses problems that do not adequately fit conventional approaches in these disciplines. In its eighth year, the International Society of Disease Surveillance is well positioned to address the standardization problem because its membership represents the involved stakeholders including progressive programs worldwide as well as resource-limited settings, and also because best practices in disease surveillance is fundamental to its mission. The proposed panel is intended to discuss how an effective, sustainable technical conventions group might be maintained and how it could support stakeholder institutions.

Objective

The panel will present the problem of standardizing analytic methods for public health disease surveillance, enumerate goals and constraints of various stakeholders, and present a straw-man framework for a conventions group.

 

Submitted by Magou on

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.

Submitted by elamb on

Active surveillance for influenza is a useful but costly endeavor. In recent years infoveillance tools have been developed to track and analyze data available on the Internet and social media (Eysenbach 2011). While infoveillance tools have been developed, few tools focus on geo-targeted data collection at a local level combined with Geographic Information Systems (GIS) capability.

Objective

We developed geo-targeted social media application program interfaces (APIs) for Twitter and a web-based social media analytics and research testbed (SMART) dashboard to analyze “flu” related tweets. During the 2013-14 flu season, for 10 cities with active surveillance for influenza (ILI), we correlated weekly tweeting rates and visual patterns of flu tweeting rates. To facilitate widespread use and testing of this system, we developed an interactive webbased dashboard “SMART” that allows practitioners to monitor and visualize daily changes of flu trends and related flu news.

 

Submitted by Magou on

The federal meaningful use initiative is a major driver to the establishment of expanded electronic syndromic surveillance capacity across the United States. Much has been documented about the background and requirements for eligible hospitals to achieve the syndromic meaningful use objectives. However, the role and efforts by public health agencies in the syndromic onboarding process, which varies by jurisdiction, is a significant component of the success of meaningful use. 

Objective

This presentation aims to highlight technical approaches, validation activities, outcomes, and lessons learned while onboarding local hospitals through a local health information exchange (HIE) for Meaningful Use Stage 2 syndromic surveillance

Submitted by rmathes on

Syndromic surveillance information can be a useful for the early recognition of outbreaks, acute public health events and in response to natural disasters. Inhalation of particulate matter from wildland fire smoke has been linked to various acute respiratory and cardiovascular health effects. Historically, wildfire disasters occur across Southern California on a recurring basis. During 2003 and 2007, wildfires ravaged San Diego County and resulted in historic levels of population evacuation, significant impact on air quality and loss of lives and infrastructure. In 2011, the National Institutes of Health, National Institute of Environmental Health Sciences awarded Michigan Tech Research Institute a grant to address the impact of fire emissions on human health, within the context of a changing climate. San Diego County Public Health Services assisted on this project through assessment of population health impacts and provisioning of syndromic surveillance data for advanced modeling.

Objective

This presentation describes how syndromic surveillance information was combined with fire emission information and spatio-temporal fire occurrence data to evaluate, model and forecast climate change impacts on future fire scenarios.

Submitted by uysz on

Current local, state, and national initiatives related to meaningful use and the modernization of electronic health records, and the growing availability of electronic information exchanges, have become important drivers to establishing syndromic surveillance systems. Effective implementation of electronic syndromic surveillance interfaces requires approaches that ensure the receipt of quality, timely, and reliable information.

While there are published specifications for the HL7 ADT message and National Institute of Standards and Technology (NIST) validation tools, there has been little documentation about the necessary steps for a local public health department to validate and confirm that an interface that is producing consistent and quality information. The lack of effective validation efforts has led to incomplete or inconsistent data utilized by syndromic systems and their intended audiences.

The County of San Diego has developed and utilized a framework for validating new syndromic interfaces. This presentation will highlight several pragmatic methods to validate the HL7 message content, provide specific examples of validation, and describe the pitfalls that could result from a poorly validated syndromic interface.

Submitted by teresa.hamby@d… on
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