Results:

• Too many measures create confusion, and the best measures are linked to interventions and lead to action in multiple sectors. Metrics should have a clear purpose.
• Measurements collected over time can help track progress. Organizations reporting data should be transparent about their measurements and results.
• The County Health Rankings use data as a starting point for community discussion about social and economic factors and potential courses of action.
• Qualitative data can add context and narratives to quantitative data to help motivate people to action.
• Maps are powerful tools for communicating differences in health outcomes across geographic areas and can show impacts of historical policy decisions on poor health outcomes. Measuring disparities over time can show the high economic cost of premature death.
• Useful measures identified by workshop participants included political will; leadership and community engagement; isolation, social support, and connectedness; costs and investments; local-level social, environmental, and demographic information; resources in the community; and workforce metrics.
• Barriers to measurement included mistrust of data, data collectors, or reporting organizations; resistance to change and desire to maintain the status quo at the organizational level; validated measurements not relevant or flexible to community needs; lack of local context; technical difficulties; and competing interests in a multi-sector environment.

Methods:

• This document summarizes a workshop convened to explore the landscape and uses of measures and measurements applied toward improving population health.  The workshop also examined metrics outside the health field (i.e., built environment factors) that can influence health and measures of health equity and disparities.

National Academy of Sciences, Engineering, and Medicine. (2016). Metrics That Matter for Population Health Action: Workshop Summary. Washington, DC: The National Academies Press.