Standard

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.

 

Effective PH information exchange depends on standardized data to ensure system-to-system interoperability and is a critical component of preparedness and response. The Common Ground Preparedness Framework (CGPF) was developed through a three-year collaboration of eight state and local health departments to define and categorize PH business processes related to preparedness to include prepare, manage, monitor, investigate, intervene and recover. The CGPF may be used to prioritize standardization activities. Monitoring, which is the crucial CGPF category for the entire PH preparedness business processes includes assessing population trends, and conducting surveillance. The author used the CCPF monitoring process as a basis for the comparison to determine those standards that aligned with these processes and identified any gaps in the standards. This assessment may help in better understanding content standardization for preparedness and areas for improvement.

Objective

The objective of this presentation is to evaluate progress in developing semantically interoperable content for PH systems that monitor PH threats. Also, it highlights potential solutions for improve standardization of those data exchanges.