Award Date


Degree Type


Degree Name

Master of Health Administration (MHA)


Healthcare Administration and Policy

First Committee Member

Josue Epane

Second Committee Member

Jay Shen

Third Committee Member

Soumya Upadhyay

Fourth Committee Member

Djeto Assane

Number of Pages



Hospital closures have recently been more common and a crucial concern in the United States since they can influence many aspects of patients' health conditions. This situation has led many scholars to investigate the adverse effect of hospitals closure. Previous research has well documented the effects of a hospital closure. However, there is a lack of studies on the predictor of a hospital closure. To fill this gap, the objective of this longitudinal study is to explore organizational and market factors associated with hospital closure. We used Data from the American Hospital Association (AHA), the Centers for Medicare and Medicaid Services (CMS) Cost Reports, and the Area Health Resource Files (AHRF) for this analysis. This study includes all medical/surgical acute care hospitals operating in the United States between 2005 and 2019. We used an unbalanced panel design with logistic regression and marginal effects to explore the probability of our predictor variables on hospital closure. SAS version 9.4 and STATA version 13 were utilized. Our multivariate logistic regression indicated that hospitals located in more affluent counties had a lower probability of closing (0.04%, p≤0.05). Compared to smaller hospitals; larger hospitals had a (marginally significant) lower probability of closing (1.99%, p≤0.1). Hospitals with higher financial performance had a lower probability of closing with respectively (0.02%, p≤0.0001) for operating and (0.03%, p≤0.0001) for total margin. Compared to for-profit hospitals, not-for-profit hospitals and non-federal government hospitals had a lower probability of closure (2.54%, p≤0.0001 and 3.35%, p≤0.0001), respectively. After the full implementation of the ACA, hospitals had a lower probability (0.87%, p≤0.0001) of closing. Finally, hospitals with higher occupancy rates had a lower probability of closing (0.03%, p≤0.001). Our study findings will give policymakers and hospital leadership teams tools to design effective policies and strategies to help prevent hospital closure.


Closure; Financial Condition; Healthcare; Hospital; Hospital closure


Health and Medical Administration

File Format


File Size

878 KB

Degree Grantor

University of Nevada, Las Vegas




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