BACKGROUND: Data governance refers to the management of public health information systems and data. It is an infrastructure designed to “mediate divergent interests, solicit involvement from and communicate effectively with diverse constituent groups, and provide direction in the coordinated development of public health information systems that support the health improvement efforts of communities” (Yasnoff). With the emergence of more and more sophisticated informatics technologies, growth of data available, and push for data-sharing, it is increasingly important that public health practitioners responsible for the development and management of their information systems be fully informed when making decisions on system design, data integration and use.
METHODS: This poster will focus on integrated disease information systems, primarily Consilience MAVEN systems from local health departments. Data governance becomes especially important for integrated systems due to the “divergent interests” of end users from different program areas and different diseases that no longer operate in organizational siloes due to technology availability facilitating integration. Program areas examined include: surveillance, education, outreach, screening, case management and clinical care. Diseases included are: HIV/AIDS, STDs, TB, viral Hepatitis and other communicable diseases. The poster will display three data governance models from health departments and outline structures supporting the following functions found as best practice from surveying twelve state and local health departments from across the country.
RESULTS: Data governance models range in size, structure and composition depending on health department needs and resources, however each model supports the following functions:
- End User and Program Area Needs
- Grant Reporting Requirements
- Security, Access and Data Use Agreements
- Policy, Procedure and Business Processes
- Emergent Needs
- Help Desk Issues
- System Training
CONCLUSIONS: The purpose of data governance is to manage public health information systems and data by creating a structure of strategic alliances that foster collaboration and coordination amongst end-users. Composition of data and system governance committees is key to ensuring their effectiveness in collecting, integrating, maintaining, reporting and using data to drive efforts to identify and address health disparities. This poster examines published evidence on data governance design as well as three health department case study models. SOURCES: Yasnoff, W. A., Overhage, J. M., Humphreys, B. L., & LaVenture, M. (2001). A National Agenda for Public Health Informatics: Summarized Recommendations from the 2001 AMIA Spring Congress. Journal of the American Medical Informatics Association: JAMIA, 8(6), 535–545.