The research team created a systems-level dataset that includes state and local health and public health spending, social and community services spending (from the US Census finance divisions), total county debt, demographics (from the US Census demographics divisions), social determinants (from various datasets), as well as both health and non-health outcomes for investigation into the causal impact of cross-sector spending and activity on health and non-health outcomes. Fixed effects regression models controlled for heterogeneity bias at the state level as well as national and state specific trends.
Models suggest non-hospital health spending (NHHS) was associated with a reduction in mortality. Overall, a 10% increase in NHHS was associated with a 0.024% (p< 0.001) decrease in all-cause mortality after one year from the initial spending. This effect was larger in counties with a higher proportion of people of color. Age distribution, socioeconomic status, and other social investments also had statistically significant associations with mortality outcomes.
Increases in per capita NHHS had a statistically significant, if modest, association with mortality reduction over time. It appears that other socioeconomic characteristics, such as educational attainment and proportion of county that are persons of color interact with social investments and their impact on health outcomes. Our findings in comparison to those of other researchers, seem to indicate that health care related spending is likely less cost-effective than population-based spending on prevention and public health. Thus, suggesting the potential of population-oriented work as a more cost-effective means to reduce mortality over time.
The United States spends more money on healthcare than other developed countries, yet experiences significantly worse health outcomes. But, understanding healthcare spending alone is not enough. While the importance of nonmedical barriers to health, such as lack of adequate housing, education, transportation is well known, how state and local public health and social spending affects health outcomes is less clear. This study examines all levels of government spending across medical care, public health, and social service sectors to characterize the impact of such spending on health outcomes and disparities. The research team created a novel longitudinal dataset, based on U.S. Census of State and Local Government Finance data, that merges medical, public health, social services and community service state and local governmental spending with population health outcomes. This novel dataset allows us to move beyond current “siloed” health care spending estimates to examine spending across sectors such as, education, human services, transportation, and housing and characterize the impact of state and local spending on health outcomes and disparities. Our public-release data file, as well as our research findings, support the growth of a community of scholars and policymakers to design and implement evidence-based strategies to foster stewardship of governmental medical, public health, social and community services resources to achieve better health outcomes and reduce health disparities.