2021
DOI: 10.1186/s12913-021-06219-4
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A multilevel mixed-effects regression analysis of the association between hospital, community and state regulatory factors, and family income eligibility limits for free and discounted care among U.S. not-for-profit, 501(c)(3), hospitals, 2010 to 2017

Abstract: Background Not-for-profit hospitals are facing an uncertain financial future, especially following the COVID-19 pandemic. Nevertheless, they are legally obligated to provide free and discounted health care services to communities. This study investigates the hospital, community, and state regulatory factors and whether these factors are associated with family income eligibility levels for free and discounted care. Methods Data were sourced from Int… Show more

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Cited by 2 publications
(2 citation statements)
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“…Since its launch, CBI has supported data collection and analysis for several publications comparing community benefit expenditure data across states; 13 comparing community benefit spending across organizations; 14 determining whether hospital, community, and state regulatory factors are associated with family income eligibility levels for free or discounted care; 15 and examining community benefit expenditures around a specific social determinant of health. 16 In addition, community benefit organizations have routinely used CBI to support data analysis at the state and local levels.…”
Section: Current Use Of Cbimentioning
confidence: 99%
“…Since its launch, CBI has supported data collection and analysis for several publications comparing community benefit expenditure data across states; 13 comparing community benefit spending across organizations; 14 determining whether hospital, community, and state regulatory factors are associated with family income eligibility levels for free or discounted care; 15 and examining community benefit expenditures around a specific social determinant of health. 16 In addition, community benefit organizations have routinely used CBI to support data analysis at the state and local levels.…”
Section: Current Use Of Cbimentioning
confidence: 99%
“…The presence of multiple regulations increased spending, but no single type of regulation yielded a statistically significant increase ( Singh et al, 2018 ). Other studies have found a positive association between state regulations on free and discounted care ( Mose, 2021 ), the amount of charity care and resource allocation decisions ( Gray & Schlesinger, 2009 ; Lamboy-Ruiz et al, 2019 ), and types of community benefit spending ( Lo Sasso & Seamster, 2007 ).…”
Section: Introductionmentioning
confidence: 96%