An Introduction to the NNDSS Message Evaluation and Testing Service (METS) and the Message Validation, Processing and Provisioning System (MVPS) Dashboard

Monday, June 15, 2015: 2:54 PM
Back Bay B, Sheraton Hotel
Sandy Chapman , Centers for Disease Control and Prevention, Atlanta, GA
Lesliann E. Helmus , Centers for Disease Control and Prevention, Atlanta, GA

BACKGROUND:  Previous experience with NNDSS message implementation and with electronic lab reporting (ELR) to public health showed that a tool enabling submitters to test and refine their message as they developed them facilitates a more efficient implementation process.  Additionally, feedback on NNDSS submission indicated that submitters wanted to be able to identify which case notifications were not included in Morbidity and Mortality Weekly Report (MMWR) statistics and determine why they were not included. The CDC-developed Message Validation, Processing and Provisioning System (MVPS) addresses both of these needs.

METHODS:  The MVPS team used requirements gathered from CDC programs, the NNDSS User Acceptance Testing team, the NNDSS Data Operations Team, the NEDSS Base System (NBS) team, and health jurisdictions to design two tools to improve the quality of NNDSS data, the METS tool and the MVPS dashboard.

RESULTS:  METS allows jurisdictions to submit messages through an interface to an automated evaluation tool that provides feedback on structural and formatting issues.  This tool is used by states for iterative improvement as they prepare new HL7-based disease-specific messages for acceptance testing by CDC, and by the CDC teams involved in acceptance testing. Through the MVPS dashboard both the submitting jurisdiction and the relevant CDC program can view notifications submitted to NNDSS to determine which were included in the MMWR counts, identify the reason that records did not meet NNDSS print criteria, and review other potential problems in the records which might need to be addressed.

CONCLUSIONS:  The features of both METS and the MVPS dashboard will be presented, along with a discussion of how they can be used to improve the quality and completeness of NNDSS data.