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Racialized economic segregation and potentially preventable hospitalizations among Medicaid/CHIP-enrolled children. | LitMetric

AI Article Synopsis

  • The study aims to explore how geographic differences affect preventable hospitalizations in children enrolled in Medicaid/CHIP, particularly focusing on the link between these hospitalizations and racialized economic segregation within ZIP codes.
  • Using data from over 12 million Medicaid/CHIP enrollees and a specific measure of segregation, the research employs logistic regression to analyze the influence of economic and racial factors on hospitalization rates.
  • Findings reveal that there are significant disparities in preventable hospitalizations based on ZIP codes, with children in areas of higher racialized economic segregation experiencing notably higher rates of preventable hospitalizations, especially related to asthma.

Article Abstract

Objective: To examine geographic variation in preventable hospitalizations among Medicaid/CHIP-enrolled children and to test the association between preventable hospitalizations and a novel measure of racialized economic segregation, which captures residential segregation within ZIP codes based on race and income simultaneously.

Data Sources: We supplement claims and enrollment data from the Transformed Medicaid Statistical Information System (T-MSIS) representing over 12 million Medicaid/CHIP enrollees in 24 states with data from the Public Health Disparities Geocoding Project measuring racialized economic segregation.

Study Design: We measure preventable hospitalizations by ZIP code among children. We use logistic regression to estimate the association between ZIP code-level measures of racialized economic segregation and preventable hospitalizations, controlling for sex, age, rurality, eligibility group, managed care plan type, and state.

Data Extraction Methods: We include children ages 0-17 continuously enrolled in Medicaid/CHIP throughout 2018. We use validated algorithms to identify preventable hospitalizations, which account for characteristics of the pediatric population and exclude children with certain underlying conditions.

Principal Findings: Preventable hospitalizations vary substantially across ZIP codes, and a quarter of ZIP codes have rates exceeding 150 hospitalizations per 100,000 Medicaid-enrolled children per year. Preventable hospitalization rates vary significantly by level of racialized economic segregation: children living in the ZIP codes that have the highest concentration of low-income, non-Hispanic Black residents have adjusted rates of 181 per 100,000 children, compared to 110 per 100,000 for children in ZIP codes that have the highest concentration of high-income, non-Hispanic white residents (p < 0.01). This pattern is driven by asthma-related preventable hospitalizations.

Conclusions: Medicaid-enrolled children's risk of preventable hospitalizations depends on where they live, and children in economically and racially segregated neighborhoods-specifically those with higher concentrations of low-income, non-Hispanic Black residents-are at particularly high risk. It will be important to identify and implement Medicaid/CHIP and other policies that increase access to high-quality preventive care and that address structural drivers of children's health inequities.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10154153PMC
http://dx.doi.org/10.1111/1475-6773.14120DOI Listing

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