Using Maven to Enhance Public Health Response: Tracking HIV/AIDS Cases in North Carolina

Tuesday, June 6, 2017: 4:30 PM
400B, Boise Centre
Anne Hakenewerth , North Carolina Department of Health and Human Services, Raleigh, NC
Tara Riley-Williams , North Carolina Department of Health and Human Services, Raleigh, NC
Fran Thomas , North Carolina Department of Health and Human Services, Greensboro, NC

BACKGROUND: North Carolina is one of several jurisdictions (e.g. CT, MA, MN, NYC, SD) using the Maven disease surveillance and case management system. Although the core functionality of Maven is the same for all jurisdictions, in North Carolina we have been able to utilize the North Carolina Electronic Disease Surveillance System (NC EDSS) to track our work on behalf of persons living with HIV (PLWH). NC included HIV/AIDS in NC EDSS along with other communicable diseases, primarily to eliminate separate and redundant applications for disease surveillance, reporting, and field services. For HIV/AIDS, NC EDSS was envisioned not only as a repository for surveillance data and enabler of case notification to CDC, but also a system for field services staff to track timely follow-up and treatment activities for PLWH.

METHODS: NC used the Maven data import engine to convert HIV cases and contacts and to bring in electronic laboratory reporting (ELR) tests for new and existing patients, and Maven capabilities to customize alert flags, workflows, and data extracts.

RESULTS: Once ELR and manual data entry are complete, NC EDSS auto-sets Disease Status using positive HIV test result flags, physician confirmation if lab results are absent, and flags indicating low CD4 based on eHARS age rules and HIV-detected flags. Workflows identify Low-CD4 flags without HIV detected, annotated case report form (ACRF) completion status, and test results of interest (new cases, activity on closed cases, pediatric activity, labs needing HIV confirmation). NC EDSS also tracks field staff activity to promote timely case and contact follow-up. Data are automatically extracted from NC EDSS to create ACRF documents that feed into eHARS as eHARS documents. Maven Denormalized Tables are used to feed data from NC EDSS to an integration system that automatically links testing and demographic records on the person level from five data sources, to quickly identify persons who are out of care and enable specialized analytics and quality assurance determinations.

CONCLUSIONS: NC EDSS has allowed North Carolina to expedite contract tracing activities and enabled a centralized repository of all HIV/AIDS follow-up activity as well as expedited reporting to eHARS. The system has allowed NC to extend automation to bridge counselor activities and report on the overall state of HIV disease in NC. Patient/contact communications are improved and NC tracks the timeliness of each step in an investigation which provides documented statistics for management to act on to enable improvement in process and/or staff.