Where you live and where you receive care: Using cross-classified multilevel modeling to examine hospital and neighborhood variation in in-hospital mortality and mortality disparities.

IF 3 3区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Alina Schnake-Mahl, Ana V Diez Roux, Bian Liu, Louisa W Holaday, Albert Siu, Edwin McCulley, Usama Bilal, Katherine A Ornstein
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引用次数: 0

Abstract

Purpose: Both hospitals and neighborhoods likely play important roles in driving health outcomes and inequities, but there has been limited prior research examining both contexts simultaneously. In this analysis we examine the contributions of these two critical contexts, neighborhoods and hospitals, to variation in in-hospital mortality and mortality disparities.

Methods: We used cross-classified multi-level models, a statistical technique that can incorporate data from multiple non-nested levels, to examine the variation in contribution of neighborhoods and hospitals to in-hospital mortality. Our study focuses on COVID-19 in hospital mortality from New York State in 2020, as a methodological case study of cross classified multilevel modeling, given the well documented variation in COVID-19 in-hospital mortality across contexts.

Results: We found that nearly one in five patients hospitalized for COVID-19 died, and there was substantial variation in risk of in-hospital mortality by neighborhoods and hospitals, with more variation across hospitals (τ00:0.29) than across neighborhoods (τ00:0.02). Neighborhoods did not explain hospital variability and vice versa: both contexts appeared to contribute independently to in-hospital mortality rates. We also found several hospital, neighborhood, and individual factors were associated with in hospital mortality disparities in fully adjusted models: lower hospital quality and safety-net hospitals, social vulnerability, older age, not having private insurance, and being Hispanic or non-Hispanic other.

Conclusions: Our findings suggest the importance of simultaneously considering hospital and neighborhood contexts to understand in-hospital outcome disparities. Understanding the contribution of these critical contexts has important implications for targeting interventions to ensure equitable hospital outcomes despite inequities in neighborhood and hospital contexts.

你住在哪里,你在哪里接受治疗:使用交叉分类多层次模型来检查医院和社区在住院死亡率和死亡率差异方面的变化。
目的:医院和社区可能在推动健康结果和不平等方面发挥重要作用,但同时检查这两种情况的先前研究有限。在本分析中,我们研究了这两个关键背景的贡献,社区和医院,在院内死亡率和死亡率差异的变化。方法:我们使用交叉分类多层次模型(一种可以纳入多个非嵌套水平数据的统计技术)来检查社区和医院对住院死亡率的贡献变化。鉴于不同背景下COVID-19住院死亡率的变化有充分记录,我们的研究重点是2020年纽约州COVID-19住院死亡率,作为交叉分类多层次建模的方法学案例研究。结果:我们发现近五分之一的COVID-19住院患者死亡,不同社区和医院的住院死亡率风险差异很大,医院之间的差异(τ00:0.29)大于社区之间的差异(τ 00:02)。社区并不能解释医院的差异,反之亦然:这两种情况似乎都独立地影响了住院死亡率。我们还发现,在完全调整的模型中,一些医院、社区和个人因素与院内死亡率差异有关:较低的医院质量和安全网医院、社会脆弱性、年龄较大、没有私人保险、西班牙裔或非西班牙裔其他。结论:我们的研究结果表明,同时考虑医院和社区背景对于了解院内结局差异的重要性。了解这些关键环境的贡献对有针对性的干预措施具有重要意义,以确保在社区和医院环境不平等的情况下公平的医院结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Annals of Epidemiology
Annals of Epidemiology 医学-公共卫生、环境卫生与职业卫生
CiteScore
7.40
自引率
1.80%
发文量
207
审稿时长
59 days
期刊介绍: The journal emphasizes the application of epidemiologic methods to issues that affect the distribution and determinants of human illness in diverse contexts. Its primary focus is on chronic and acute conditions of diverse etiologies and of major importance to clinical medicine, public health, and health care delivery.
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