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Is patients' rurality associated with in-hospital sepsis death in US hospitals?open access

Authors
Chang, JongwhaMedina, MarKim, Sun Jung
Issue Date
Jun-2023
Publisher
Frontiers Media S.A.
Keywords
rurality; sepsis; NIS sample; in-hospital death; health disparity
Citation
Frontiers in Public Health, v.11
Journal Title
Frontiers in Public Health
Volume
11
URI
https://scholarworks.bwise.kr/sch/handle/2021.sw.sch/25318
DOI
10.3389/fpubh.2023.1169209
ISSN
2296-2565
2296-2565
Abstract
BackgroundThe focus of this study was to explore the association of patients' rurality and other patient and hospital-related factors with in-hospital sepsis mortality to identify possible health disparities across United States hospitals. MethodsThe National Inpatient Sample was used to identify nationwide sepsis patients (n = 1,977,537, weighted n = 9,887,682) from 2016 to 2019. We used multivariate survey logistic regression models to identify predictors for how patients' rurality is associated with in-hospital death. FindingsDuring the study periods, in-hospital death rates among sepsis inpatients continuously decreased (11.3% in 2016 to 9.9% in 2019) for all rurality levels. Rao-Schott Chi-Square tests demonstrated that certain patient and hospital factors had varied in-hospital death rates. Multivariate survey logistic regressions suggested that rural areas, minorities, females, older adults, low-income, and uninsured patients have higher odds of in-hospital mortality. Further, specific census divisions like New England, Middle Atlantic, and East North Central had greater in-hospital sepsis death odds. ConclusionRurality was associated with increased in-hospital sepsis death across multiple patient populations and locations. Further, rurality in New England, Middle Atlantic, and East North Central locations is exceptionally high odds. In addition, minority races in rural areas also have an increased odds of in-hospital death. Therefore, rural healthcare requires a more significant influx of resources and should also include assessing patient-related factors.
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