Health Impact Assessments

Health Impact Assessments (HIAs) are a decision-support tool designed to help community stakeholders investigate how a proposed program, project, policy, or plan may impact the health and well-being of a population. The major steps in conducting an HIA are screening, scoping, assessment, recommendations, reporting, and monitoring and evaluation.

HIAs are flexible, using available resources and variations of qualitative and quantitative data sources and methods. Programs may use a range of primary and secondary data for conducting an HIA. Potential quantitative data sources that can help programs identify priorities include:

• Claims data
• Local needs assessments (for example, Community Health Needs Assessments)
• Tools and indexes for measuring SDOH at the community level, including Rural Data Central, PLACES, the Opportunity Atlas, and the Distressed Communities Index
• Benchmarks at the local, state, and national level from sources such as the Behavioral Risk Factor Surveillance System (BRFSS)

HIAs are also based on stakeholder input, providing the opportunity to engage with community members, planners, and non-traditional health partners. Rural communities may collect information directly from the community and those who work with intended program participants. Potential qualitative data sources include:

• Community members who receive services or who would be served by SDOH efforts
• Lay health workers and social services providers with deep ties to intended program participants
• Community groups and organizations that serve intended program participants

Some rural communities experience challenges accessing data, which creates barriers to informed decision-making at all levels. Many rural communities are making improved data collection and sharing a priority. The Center for Rural and Primary Healthcare at the University of South Carolina launched the SC Rural Healthcare Resource Dashboard to provide communities in their state with access to reliable cross-sector data so that they may plan and implement programs with confidence.

In rural areas, smaller populations and lower population densities can complicate data collection and reporting. Data disaggregation can be important in rural communities with small population sizes, where aggregation of data may mask differences in health outcomes among different groups of people. Where data disaggregation is not possible, rural communities can consider conducting additional data collection through traditional methods like surveys and interviews and less traditional approaches like community mapping and Photovoice.