Integrating Health Equity into State and Local Data Sharing Practices

July 16, 2024 | Morgan Zialcita, Lana McKinney, Christina Severin, Reema Mistry, Melissa Lewis

Timely and efficient public health data sharing improves public health response and decision-making. It enables local public health agencies (PHAs) to enhance community-level interventions and state PHAs to provide equitable response and allocation of resources within the jurisdiction. However, data sharing between state and local PHAs can be challenging due to resource capacity constraints, factors that limit technical solutions, and sensitivities and complexities associated with public health data collection and dissemination.

Adopting policies to advance state and local data sharing and incorporating health equity principles into these relationships can help PHAs better identify and address data disparities, utilize resources effectively, and create an equity-centered public health data infrastructure.

Equity Impact Assessment for Policy Changes

Adopting data sharing policies using a health equity-focused framework can mitigate unintentional harm to specific populations. An equity assessment requires the systematic examination of available data and expert input to understand how a policy, program, or process will affect various groups, especially those who are either at risk of or experiencing health disparities. The Health Equity Impact Assessment (HEIA), designed to address racial disparities and root causes of inequities that could arise from policy changes, can help agencies explore potential inequities that may result from a policy initiative.

Health Equity Considerations for Key State and Local Data Sharing Priorities

Informatics Workforce

Developing a diverse workforce that is representative of the communities it serves is important for advancing an equitable, inclusive approach to data modernization. However, recruiting and retaining diverse informatics staff—with strong technical, relationship-building, and change management skills—can be challenging for PHAs, especially in resource-limited locations. Health agencies can incorporate health equity principles into their workforce strategies in several ways:

• Consider soft skills, such as communication and collaboration, alongside technical expertise. These skills are important in establishing and maintaining state and local data sharing relationships.
• Include data sharing tasks in job descriptions to promote accountability and transparency amongst staff. This approach helps identify the role(s) responsible for data sharing activities and can also support sustainability by minimizing staff turnover.
• Prioritize inclusive practices and invest in ongoing development of agency staff. For example, provide training on cultural humility and data sovereignty to better equip staff working with tribal nations on data-sharing initiatives, and provide on-the-job training to help employees grow and build capacity.
• Reassess location, remote work, salary, and tenure policies to attract a diverse and skilled informatics workforce.

Agency Alignment and Governance

The type of public health governance model in a given state (e.g., centralized, decentralized, shared, or mixed) can influence how state and local PHAs work together both overall and on data-focused initiatives. The following health equity-focused recommendations are applicable across governance types:

• Establish strong communication channels and processes across partners to ensure all parties explore and understand the health equity considerations associated with data sharing initiatives.
• Consider options for shared resources to leverage expertise and promote collaboration on data-sharing initiatives (e.g., shared training programs, IT systems, and liaison roles that could perform epidemiology or informatics functions). This shared approach can bridge resource and knowledge gaps between state and local PHAs, especially for communities with limited resources.
• Consider ways to include local PHA input and ongoing feedback (e.g., through advisory boards) to encourage shared decision-making.
• Establish processes and policies to identify appropriate levels of data access across both local and state PHAs, so that shared data can inform population health analysis and reporting purposes at community, state, territory, tribal, and federal levels.

Data Sharing Agreements and Organizational Policies

When pursuing a new or amended data sharing relationship, engaging with legal experts is essential to safeguard sensitive public health data and ensure compliance with all relevant laws. Failure to successfully navigate these relationships and the inherent complexities associated with certain types of data can limit access to valuable information for important public health initiatives that improve equitable outcomes. Health agencies can take the following actions to promote effective collaboration between program, technical, and legal staff:

• Share the scope of the data relationship, the details of the proposed data exchange, and the overall programmatic purpose of the arrangement with the legal team. This is necessary for effective discussions with legal counsel and will help inform the agency’s approach to documenting the data relationship (e.g., in the form of a data-sharing agreement or DSA).
• Use decision-support tools, such as the HEIA, alongside the legal team to consider how the new proposed data sharing policy may impact equity across populations.
• Use clear and accessible language in DSAs and related protocols and policies, with support from legal counsel. Documents written in plain language support transparency, help build trust, and facilitate understanding among interested parties.
• Foster a culture of knowledge sharing between program, technical, and legal staff. For example, consider inviting legal staff to join advisory committees, listening sessions, or town halls about data sharing considerations to enhance program staffs’ understanding of legal considerations, address perceived barriers, and promote relationships and knowledge exchange between program teams.

Conclusion

In addition to adopting policies that make data accessible across government levels, it is important to develop mechanisms for communicating with communities about how their data is being used. For example, developing public-facing data dashboards (such as Alaska Department of Health’s Public Health Data Hub) that are easily accessible and understandable can be an effective way to increase transparency and build trust with the public.

By committing to these strategies, PHAs can support a more collaborative, coordinated, and equitable approach to state and local data sharing, and strengthen PHAs’ capacity to address public health challenges.