# Emergency Department Utilization by Women of Reproductive Age for Mental Illness in St. Louis Before and During the COVID-19 Pandemic

## TL;DR

The study examines how women of reproductive age in St. Louis used emergency departments for mental health before and during the pandemic, revealing disparities linked to socioeconomic factors.

## Contribution

The study introduces a spatio-temporal model to identify geographic disparities in mental health ED utilization among vulnerable women during the pandemic.

## Key findings

- Census tracts with higher public insurance and lower income had greater emergency mental health resource demand.
- ED visits for mental illness increased during the pandemic, especially in disadvantaged urban areas.
- Geospatial analysis highlights service gaps, guiding targeted interventions for high-need neighborhoods.

## Abstract

Public health relevance—How does this work relate to a public health issue?
Women are generally at greater risk of mental illness than menUrban residents may increasingly rely on emergency departments for acute care due to limited capacity

Women are generally at greater risk of mental illness than men

Urban residents may increasingly rely on emergency departments for acute care due to limited capacity

Public health significance—Why is this work of significance to public health?
Mental health among women of child-bearing age affects not just the mother, but also the child.Geospatial tools reveal greatest service gaps among reproductive-age women with behavioral health conditions, directing interventions to unmet needs.

Mental health among women of child-bearing age affects not just the mother, but also the child.

Geospatial tools reveal greatest service gaps among reproductive-age women with behavioral health conditions, directing interventions to unmet needs.

Public health implications—What are the key implications or messages for practitioners, policy makers and/or researchers in public health?
The spatio-temporal model indicates that census tracts with a higher proportion of public insurance, a higher proportion of those with a high school diploma, and greater age tended to have a higher demand for emergency mental health resources.Those census tracts with a higher proportion of private insurance and higher income tended to have a lower demand for mental health resources.The analysis captures ED utilization’s temporal trends and neighborhood variations, providing actionable insights for data-driven strategies that target high-need areas.

The spatio-temporal model indicates that census tracts with a higher proportion of public insurance, a higher proportion of those with a high school diploma, and greater age tended to have a higher demand for emergency mental health resources.

Those census tracts with a higher proportion of private insurance and higher income tended to have a lower demand for mental health resources.

The analysis captures ED utilization’s temporal trends and neighborhood variations, providing actionable insights for data-driven strategies that target high-need areas.

Mental illness and related health inequities are disproportionately concentrated in economically disadvantaged urban neighborhoods. The COVID-19 pandemic has been associated with a rise in mental illness prevalence, with women generally at greater risk than men. Urban areas facing multiple structural and socioeconomic challenges may have limited capacity to meet the mental healthcare needs of residents, leading to increased reliance on emergency departments (EDs) for acute care. This ecological study uses data over four years (2018–2021) and examines spatial variations in ED utilization at the census tract level, focusing on geographic areas with women of reproductive age diagnosed with mental illness to compare patterns before and during the COVID-19 pandemic. Of the 22,565 ED visits in the four-year period, 12,832 occurred before COVID-19 and 9733 during COVID-19. Our findings highlight persistent structural disparities in mental healthcare access across census tracts characterized by high concentrations of vulnerable women of reproductive age. Understanding these spatial disparities allows for geographically targeted interventions and the prioritization of resources for neighborhoods identified as most underserved.