How do women access maternal care? Spatial and social dimensions of maternal healthcare visits in Florida

Abstract

Unequal access to maternal healthcare is a persistent driver of poor maternal and neonatal outcomes, particularly in rural and socioeconomically marginalized U.S. communities. While spatial access is often assessed using proximity or travel time to the nearest facility, such assumptions overlook the realities of where women actually seek prenatal and childbirth care. Overcoming the limitations of traditional access measures, this project examines the spatio-social dimensions of maternal healthcare visit patterns to better understand how women actually access care during their pregnancy and the geographic and social barriers they encounter. The patient visit data includes the total number of prenatal visits between origin-destination (OD) pairs, with origins defined as the women’s residential zip codes and destinations as the healthcare facilities they visited. The data also contains patients’ OD visit patterns disaggregated by age group, race, and health conditions. The OD data were merged with zip code-level demographic, health, and rural-urban indicators, including insurance coverage, income, transportation access, food insecurity, and chronic disease prevalence. Using these zip code-level datasets, we clustered patients’ origin into socioeconomic and health-status groups using hierarchical clustering methods to explore the neighborhood contexts behind these patterns. We performed several exploratory analyses to locate zip codes and hospitals with the highest visit volumes, as well as to examine the differences in visit patterns and distances traveled across racial groups, age categories, and health conditions. Lastly, we applied a negative binomial-based spatial interaction model to explore how geographic, socio-economic, and health factors influence women’s maternal healthcare visit patterns. Our findings reveal that women do not always attend the nearest facility, and access patterns vary substantially by geography, income, and urban-rural classification. This study provides a data-driven foundation for identifying communities experiencing limited access to maternal care. These insights can inform more equitable planning and policy interventions in maternal healthcare infrastructure.