Available online 2 March 2024
Author links open overlay panel, , , , , ABSTRACTPurposeTo examine whether hospital closure is associated with high levels of area socioeconomic disadvantage and racial/ethnic minority composition.
MethodsPooled cross-sectional analysis (2007-2018) of 6,467 U.S. hospitals from the American Hospital Association’s Annual Survey, comparing hospital population characteristics of closed hospitals to all remaining open hospitals. We used multilevel mixed-effects logistic regression models to assess closure as a function of population characteristics, including area deprivation index ([ADI], a composite measure of socioeconomic disadvantage), racial/ethnic composition, and rural classification, nesting hospitals within hospital service areas (HSAs) and hospital referral regions. Secondary analyses examined public or private hospital type.
ResultsOverall, 326 (5.0%) of 6,467 U.S. hospitals closed during the study period. In multivariable models, hospitals in HSAs with a higher burden of socioeconomic disadvantage (per 10% above median ADI ZIP codes, AOR 1.05; 95% CI, 1.01-1.09) and Black Non-Hispanic composition (highest quartile, AOR 4.03; 95% CI, 2.62-6.21) had higher odds of closure. We did not observe disparities in closure by Hispanic/Latino composition or rurality. Disparities persisted for Black Non-Hispanic communities, even among HSAs with the lowest burden of disadvantage.
ConclusionsDisproportionate hospital closure in communities with higher socioeconomic disadvantage and Black racial composition raises concerns about unequal loss of healthcare resources in the U.S.
Section snippetsINTRODUCTIONHospital closure has been accelerating over the past 30 years, [1], [2] with renewed attention amidst hospital bed shortages during the COVID-19 pandemic. [2] Rates of U.S. hospital closure were especially high in the 1990s, with 7.8% of all rural hospitals and 10.6% of all urban hospitals closing between 1990-2000. [3] Hospital closure has been associated with delays in medical care, [4] higher transport times and ED volume for nearby hospitals, [5], [6] and increased morbidity and mortality
METHODSData Sources. We used the American Hospital Association (AHA) Landscape Changes in U.S. Hospitals Report (2007-2018), which provides the most comprehensive census available of hospital closures in the U.S. Fiscal year 2018 was the most recent year available at the time of data retrieval in 2020, which includes hospitals that closed in 2017 and were reported in 2018. The AHA Annual Survey also provided data on each hospital’s Core Based Statistical Area (CBSA), used to capture rural
RESULTSOverall, 326 (5.0%) of 6,467 U.S. hospitals closed during the study period (Table 1). Closed hospitals were located in HSAs with a higher burden of socioeconomic disadvantage relative to open hospitals (35.9% versus 28.9% in very high ADI ZIP codes, P<0.001). Similarly, we observed a larger proportion of closed hospitals in HSAs with a higher percentage of Black Non-Hispanic residents (38.3% versus 24.3% in highest quartile; P<0.001). We observed no statistically significant differences in
DISCUSSIONIn our analysis of 6,467 U.S. hospitals from 2007-2018, we found that hospitals located in areas with higher socioeconomic disadvantage and Black racial composition had higher rates of hospital closure. Disparities in hospital closure were largest in areas with high Black racial composition. While the bulk of prior literature focuses on the alarming rates of rural hospital closure, [25], [26] we observed similarly alarming trends in hospital closure in urban communities. During the study
ConclusionsWe observed consistent associations of hospital closure with population-level socioeconomic disadvantage and Black racial composition. Areas with the highest Black racial composition had 4 times the odds of closure compared to those with the lowest, with higher rates of closure across all levels of socioeconomic disadvantage. Our findings underscore concerns about systematic underinvestment of healthcare resources in low-income and racially minoritized communities. At a time when the U.S. has
Funding and DisclosuresDr. Tung was supported by career development grant 1K23HL145090-01 from the National Heart, Lung, and Blood Institute. Drs. Huang, Chin, Tung and Peek were supported by grant P30DK092949 from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). Dr. Huang was supported by grant P50MD017349 from the National Institute on Minority Health and Health Disparities (NIMHD) and grant K24AG069080 from the National Institute on Aging. Drs. Chin and Peek are funded in part by a
Conflicts of InterestThe authors declare no conflicts of interest.
Access to Data StatementAll authors had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
CRediT authorship contribution statementMarshall H Chin: Conceptualization, Data curation, Project administration, Resources, Supervision, Writing – review & editing. Joseph D Bruch: Conceptualization, Data curation, Investigation, Methodology, Writing – review & editing. Elizabeth L Tung: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Visualization, Writing – original draft, Writing – review & editing. Elbert S Huang:
Declaration of Competing InterestThe authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Tung reports financial support was provided by National Heart Lung and Blood Institute. Huang, Chin, Tung and Peek reports financial support was provided by National Institute of Diabetes and Digestive and Kidney Diseases. Huang reports financial support was provided by National Institute on Minority Health and Health Disparities. Huang reports financial support
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