Streichert Laura

As interest in One Health (OH) continues to grow, alternative surveillance infrastructure may be needed to support it. Since most population health surveillance is domain specific; as opposed to OH which crosses multiple domains, changes to surveillance infrastructure may be required to optimize OH practice. For change to occur there must be a strong motivation that propagates from a perceived need. Since the purpose of surveillance is to produce information to support decision making, the motivation for change should relate to a lack of surveillance information needed to make OH decisions, or a gap in the surveillance infrastructure required to produce the information.

Objective

The primary purpose of this study was to explore the attitudes of surveillance stakeholders from different domains to:

-determine whether there is a perceived need for OHS

-identify significant surveillance gaps

-assess the motivation to change (fill the gaps)

A secondary purpose was to gather a group of surveillance stakeholders to identify and prioritize strategies to move One Health Surveillance forward.

Sharing public health (PH) data and practices among PH authorities enhances epidemiological capacities and expands situational awareness at multiple levels. Ease of data sharing through the BioSense application, now part of the National Syndromic Surveillance Program (NSSP), and the increased use of SyS nationwide have provided opportunities for region-level sharing of SyS data. In addition, there is a need to build workforce competence in SyS given powerful new information technology that can improve surveillance system capacities. Peer-to-peer learning builds the relationships and trust among individuals and organizations that are required for inter jurisdictional data sharing.

Objective

Promote interjurisdictional syndromic surveillance (SyS) data sharing practices with a training model that engages participants in collaborative learning.

On October 1, 2015, the number of ICD codes will expand from 14,000 in version 9 to 68,000 in version 10. The new code set will increase the specificity of reporting, allowing more information to be conveyed in a single code. It is anticipated that the conversion will have a significant impact on public health surveillance by enhancing the capture of reportable diseases, injuries, and conditions of public health importance that have traditionally been the target of syndromic surveillance monitoring. For public health departments, the upcoming conversion poses a number of challenges, including: 1) Constraints in allocating resources to modify existing systems to accommodate the new code set, 2) Lack of ICD-10 expertise and training to identify which codes are most appropriate for surveillance, 3) Mapping syndrome definitions across code sets, 4) Limited understanding of the precise ICD-10 CM codes that will be used in the US Healthcare system, and 5) Adjusting for changes in trends over time that are due to transitions in usage of codes by providers and billing systems. To accommodate the ICD-9 to ICD-10 transition, the Centers of Disease Control and Prevention (CDC) partnered with the International Society of Disease Surveillance (ISDS) CoP to form a workgroup to develop the Master Mapping Reference Table (MMRT). This tool maps over 130 syndromes across the two coding systems to assist agencies in modifying existing database structures, extraction rules, and messaging guides, as well as revising established syndromic surveillance definitions and underlying analytic and business rules.

Objective

This roundtable will provide a forum for the syndromic surveillance Community of Practice (CoP) to discuss the public health impacts from the ICD-10-CM conversion, and to support jurisdictional public health practices with this transition. It will be an opportunity to discuss key impacts on disease surveillance and implementation challenges; and identify solutions, best practices, and needs for technical assistance.

As of October 1, 2015, all HIPAA covered entities transition from the use of International Classification of Diseases version 9 (ICD-9-CM) to version 10 (ICD-10-CM/PCS). Many Public Health surveillance entities receive, interpret, analyze, and report ICD-9 encoded data, which will all be significantly impacted by the transition. Public health agencies will need to modify existing database structures, extraction rules, and messaging guides, as well as revise established syndromic surveillance definitions and underlying analytic and business rules to accommodate this transition. Implementation challenges include resource, funding, and time constraints for code translation and syndrome classification, and developing statistical methodologies to accommodate changes to coding practices.

To address these challenges, the International Society for Disease Surveillance (ISDS), in consultation with the Centers for Disease Control and Prevention (CDC) and the Council of State and Territorial Epidemiologists (CSTE), has conducted a project to develop consensus-driven syndrome definitions based on ICD- 10-CM codes. The goal was to have the newly created ICD-9-CM to-ICD-10-CM mappings and corresponding syndromic definitions fully reviewed and vetted by the syndromic surveillance community, which relies on these codes for routine surveillance, as well as for research purposes. The mappings may be leveraged by other federal, state, and local public health entities to better prepare and improve the surveillance, analytics, and reporting activities impacted by the ICD-10-CM transition.

Objective

To describe the process undertaken to translate syndromic surveillance syndromes and sub-syndromes consisting of ICD-9 CM diagnostic codes to syndromes and sub-syndromes consisting of ICD-10-CM codes, and how these translations can be used to improve syndromic surveillance practice.

Evaluation and strengthening of biosurveillance systems is acomplex process that involves sequential decision steps, numerous stakeholders, and requires accommodating multiple and conflicting objectives. Biosurveillance evaluation, the initiating step towards biosurveillance strengthening, is a multi-dimensional decision problem that can be properly addressed via multi-criteria-decision models.Existing evaluation frameworks tend to focus on “hard” technical attributes (e.g. sensitivity) while ignoring other “soft” criteria (e.g. transparency) of difficult measurement and aggregation. As a result, biosurveillance value, a multi-dimensional entity, is not properly defined or assessed. Not addressing the entire range of criteria leads to partial evaluations that may fail to convene sufficient support across the stakeholders’ base for biosurveillance improvements.We seek to develop a generic and flexible evaluation framework capable of integrating the multiple and conflicting criteria and values of different stakeholders, and which is sufficiently tractable to allow quantification of the value of specific biosurveillance projects towards the overall performance of biosurveillance systems.

Objective

To describe the development of an evaluation framework that allows quantification of surveillance functions and subsequent aggregation towards an overall score for biosurveillance system performance.