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Adaptive Governance: Empowering Data Sharing for Public Health Impact - Insights from North Carolina Department of Health and Human Services

Authors :
Amy Hawn Nelson
Paul Hogle
Sharon Zanti
Scott Proescholdbell
Jessie Tenenbaum
Source :
International Journal of Population Data Science, Vol 9, Iss 5 (2024)
Publication Year :
2024
Publisher :
Swansea University, 2024.

Abstract

Objective and Approach At the 2022 IPDLN Conference, we presented work led by the North Carolina Department of Health and Human Services (NCDHSS), in partnership with university-based researchers, to build legal and ethical processes for routine data sharing. This session provides significant updates on the methods, results, and implications of these efforts–namely, that NCDHHS implemented an enterprise-wide data governance process and a legal framework that has enabled timely, impactful use of cross-sector data. We relied on Participatory Action Research and Deliberative Dialogue methods to engage a diverse range of partners in a data landscape overview and the co-creation of new data sharing processes that better enables the enterprise to adapt to a changing world. Results Four key actions were taken as a result of the participatory research process: NCDHHS developed a data strategy, created a data sharing guidebook, staffed their Data Office, and implemented a new legal framework. In addition to describing how these actions support data use across a large US state health and human services agency, we provide three use cases demonstrating the impact of this work. Conclusions Establishing routine data sharing presents legal, technical, and cultural challenges, particularly in large agencies. Through a collaborative, participatory approach, the NCDHHS successfully established enterprise-wide data governance and a legal framework to support data-driven policymaking and, ultimately, improve health outcomes for residents. Implications This research presents a successful, actionable, and replicable framework for developing and implementing processes to support intradepartmental data access, linkage, and use.

Details

Language :
English
ISSN :
23994908
Volume :
9
Issue :
5
Database :
Directory of Open Access Journals
Journal :
International Journal of Population Data Science
Publication Type :
Academic Journal
Accession number :
edsdoj.7bc3f0f5ba974b259739c3d9ba1970fd
Document Type :
article
Full Text :
https://doi.org/10.23889/ijpds.v9i5.2569