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Crossen Sophia

Description

On November 20, 2017, several sites participating in the NSSP reported anomalies in their syndromic data. Upon review, it was found that between November 17-18, an EHR vendor’s syndromic product experienced an outage and errors in processing data. The ISDS DQC, NSSP, a large EHR vendor, and many of the affected sites worked together to identify the core issues, evaluate ramifications, and formulate solutions to provide to the entire NSSP CoP.

Objective: The National Syndromic Surveillance Program (NSSP) Community of Practice (CoP) works to support syndromic surveillance by providing guidance and assistance to help resolve data issues and foster relationships between jurisdictions, stakeholders, and vendors. During this presentation, we will highlight the value of collaboration through the International Society for Disease Surveillance (ISDS) Data Quality Committee (DQC) between jurisdictional sites conducting syndromic surveillance, the Centers for Disease Control and Prevention’s (CDC) NSSP, and electronic health record (EHR) vendors when vendor-specific errors are identified, using a recent incident to illustrate and discuss how this collaboration can work to address suspected data anomalies.

Submitted by elamb on
Description

The Kansas Syndromic Surveillance Program (KSSP) utilizes the ESSENCE v.1.20 program provided by the National Syndromic Surveillance Program to view and analyze Kansas Emergency Department (ED) data. Methods that allow an ESSENCE user to query both the Discharge Diagnosis (DD) and Chief Complaint (CC) fields simultaneously allow for more specific and accurate syndromic surveillance definitions. As ESSENCE use increases, two common methodologies have been developed for querying the data in this way. The first is a query of the field named “CC and DD.” The CC and DD field contains a concatenation of the parsed patient chief complaint and the discharge diagnosis. The discharge diagnosis consists of the last non-null value for that patient visit ID and the chief complaint parsed is the first non-null chief complaint value for that patient visit ID that is parsed by the ESSENCE platform. For this comparison, this method shall be called the CCDD method. The second method involves a query of the fields named, Chief Complaint History and œDischarge Diagnosis History. While the first requires only one field be queried, this method queries the CC History and DD History fields, combines the resulting data and de-duplicates this final data set by the C_BioSense_ID. Chief Complaint History is a list of all chief complaint values related to a singular ED visit, and Discharge Diagnosis History is the same concept, except involving all Discharge Diagnosis values. For this comparison, this method shall be called the CCDDHX method. While both methods are based on the same query concept, each method can yield different results.

Objective:

To compare and contrast two ESSENCE syndrome definition query methods and establish best practices for syndrome definition creation.

Submitted by elamb on
Description

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.

Submitted by elamb on
Description

Once a facility meets data quality standards and is approved for production, an assumption is made that the quality of data received remains at the same level. When looking at production data quality reports from various states generated using a SAS data quality program, a need for production data quality assessment was identified. By implementing a periodic data quality update on all production facilities, data quality has improved for production data as a whole and for individual facility data. Through this activity several root causes of data quality degradation have been identified, allowing processes to be implemented in order to mitigate impact on data quality. 

Objective

To explore the quality of data submitted once a facility is moved into an ongoing submission status and address the importance of continuing data quality assessments. 

 

Submitted by Magou on