A Replicable, Solution-Focused Approach to Cross-Sector Data Sharing for Evaluation of Community Violence Prevention Programming

Abstract

Context: Community violence is a public health problem that erodes social infrastructure. Structural racism contributes to the disparate concentration of violence in communities of color. In Mecklenburg County, North Carolina, increasing trends in community violence show racial and geographic disparities that emphasize the need for cross-sector, data-driven approaches to program and policy change. Cross-sector collaborations are challenged by data sharing barriers that hinder implementation.

Program: In response to community advocacy, Mecklenburg County Public Health (MCPH) launched a Community Violence Prevention Plan with evidence-based programming. The Cure Violence (CV) model, a public health approach to disrupting violence through equitable resource provision, network building, and changing norms, was implemented at the community level. The Health Alliance for Violence Intervention (HAVI) model, a hospital-based screening and case management intervention for victims of violence, was implemented at Carolinas Medical Center in Charlotte, the region's only level I trauma center.

Methods: A data collaborative was created to optimize evaluation of CV and HAVI programs including MCPH, the city of Charlotte, Atrium Health, Charlotte-Mecklenburg Schools, Johnson C. Smith University, and the University of North Carolina Charlotte. A comprehensive approach to facilitate data sharing was designed with a focus on engaging stakeholders and generating solutions to commonly reported barriers. Structured interviews were used to inform a solution-focused strategy.

Results: Stakeholders reported perceptions of their organization's barriers and facilitators to cross-sector data sharing. Common technology, legal, and governance barriers were addressed through partnership with a local integrated data system. Solutions for trust and motivational challenges were built into ongoing collaborative processes.

Discussion: Data silos inhibit the understanding of complex public health issues such as community violence, along with the design and evaluation of collective impact efforts. This approach can be replicated and scaled to support cross-sector collaborations seeking to influence social and health inequities stemming from structural racism.