NSSP

In 2016, the CDC funded 12 states, under the Enhanced State Opioid Overdose Surveillance (ESOOS) program, to utilize SyS to increase timeliness of state data on drug overdose events. In order to operationalize the objectives of the grant, there was a need to assess and monitor the quality of Kentucky’s SyS data, with limited resources. We leveraged the NSSP’s R Studio Server to automate quality assurance (QA) monitoring and reporting to meet these objectives.

Objective:

The aim of this project was to develop a nimble system to both monitor and report on the quality of Kentucky emergency department syndromic surveillance (SyS) data at system-wide and facility levels.

The National Syndromic Surveillance Program (NSSP) is a community focused collaboration among federal, state, and local public health agencies and partners for timely exchange of syndromic data. These data, captured in nearly real time, are intended to improve the nation's situational awareness and responsiveness to hazardous events and disease outbreaks. During CDC’s previous implementation of a syndromic surveillance system (BioSense 2), there was a reported lack of transparency and sharing of information on the data processing applied to data feeds, encumbering the identification and resolution of data quality issues. The BioSense Governance Group Data Quality Workgroup paved the way to rethink surveillance data flow and quality. Their work and collaboration with state and local partners led to NSSP redesigning the program’s data flow. The new data flow provided a ripe opportunity for NSSP analysts to study the data landscape (e.g., capturing of HL7 messages and core data elements), assess end-to-end data flow, and make adjustments to ensure all data being reported were processed, stored, and made accessible to the user community. In addition, NSSP extensively documented the new data flow, providing the transparency the community needed to better understand the disposition of facility data. Even with a new and improved data flow, data quality issues that were issues in the past, but went unreported, remained issues in the new data. However, these issues were now identified. The newly designed data flow provided opportunities to report and act on issues found in the data unlike previous versions. Therefore, an important component of the NSSP data flow was the implementation of regularly scheduled standard data quality checks, and release of standard data quality reports summarizing data quality findings.

Objective:

Review the impact of applying regular data quality checks to assess completeness of core data elements that support syndromic surveillance.

In 2005, the Cook County Department of Public Health (CCDPH) began using the Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE) as an emergency department (ED)-based local syndromic surveillance program (LSSP); 23 (100%) of 23 hospitals in suburban Cook County report to the LSSP. Data are transmitted in delimited ASCII text files (i.e., flat files) and contain a unique patient identifier, visit date and time, zip code, age, sex, and chief complaint. Discharge diagnosis and disposition are optional data elements. Prior to 2017, the Illinois Department of Public Health placed facilities participating in the Cook LSSP in a holding queue to transform their flat file submissions into a HL7 compliant message; however as of 2017, eligible hospitals must submit HL7 formatted production data to IDPH to fulfill Meaningful Use. The primary syndromic surveillance system for Illinois is the National Syndromic Surveillance Program (NSSP), which transitioned to an ESSENCE interface in 2016. As of December 2016, 20 (87%) of 23 hospitals reporting to the LSSP also reported to IDPH and the NSSP. As both syndromic surveillance systems aim to collect the same data, and now can be analyzed with the same interface, CCDPH sought to compare the LSSP and NSSP for data completeness, consistency, and other attributes.

Objective:

This analysis was undertaken to determine how the data completeness, consistency, and other attributes of our local syndromic surveillance program compared to the National Syndromic Surveillance Platform.

In 2017, the National Syndromic Surveillance Program (NSSP) continued to expand as a national scope data source with over 6,500 facilities registered on the BioSense Platform, including 4,000 active, 1,800 onboarding, and 700 planned or inactive facilities. 2,086 of the active facilities are Emergency Departments across 49 sites in 41 states. The growth of data available in NSSP has been driven by continued enhancements to tools and processes used by the NSSP Onboarding Team. These enhancements help to rapidly integrate new healthcare facilities and onboard new public health sites in support of American Hospital Association (AHA) Emergency Department (ED) representativeness goals. Furthermore, with these improvements to the onboarding process, including the Master Facility Table update process and automated data validation reporting, NSSP has broadened stakeholder participation in the onboarding process.

Objective:

This session will present the impacts of enhancements made to National Syndromic Surveillance Program (NSSP) BioSense Platform Onboarding in 2017 from the perspective of CDC and public health jurisdictions.

One of the more recent successes of NSSP has been the introduction of more robust data quality monitoring and reporting. However, despite the increased insight into data quality, there are still concerns about data sharing and comparisons across sites. For NSSP to be most effective, users need to feel confident in sharing data and making comparisons across sites.

Objective:

As the BioSense Platform matures and more sites submit surveillance data, many in the community have voiced concerns about comparing data across sites. Recently, a number of jurisdictions from across the country were asked to provide opioid overdose data to a news agency highlighting the epidemic. Many jurisdictions requested information on how to present syndromic surveillance data from across sites and shared concern about how the data would be interpreted. This round table will address those concerns and explore options for comparing data across sites.

One of the early successes for the National Syndromic Surveillance Program'™s (NSSP'™s) BioSense Platform was community agreement on what should make up national and regional picture of the data. For NSSP to meet program objectives, National level surveillance and situational awareness had to be made available – not just to CDC, but to the entire community. To make this possible, the community had to agree on a limited dataset that would be sufficient to produce national and regional picture. Currently when NSSP staff at CDC or a particular program review HHS Regional data, they can only see trends at high levels. Although, this information is proving useful, when very unusual data spikes occur there is insufficient information to determine its public health significance. CDC would like to set up HHS Regional Epi groups made up of syndromic surveillance practitioners within regions in order to communicate about potentially unusual findings and discuss implications for local jurisdictions.

Objective:

Within the BioSense Platform, users have the ability to view HHS Region level data that can provide insight into what may be happening around the country. Epidemiologists can examine this information for changes in trends of subsyndromes or other potential issues of public health concern and compare it to their local data. However, the insight that regional data can provide is limited without better understanding of what is happening in the jurisdictions that make up the region. This round table will discuss the benefits of engaging with other jurisdictions within regions and attempt to define rules of engagement that can be used to facilitate interactions.