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. 2022 Jan-Dec:59:469580221121534.
doi: 10.1177/00469580221121534.

How Would Medicaid Expansion Affect Texas Hospitals? Evidence From a Retrospective Quasi-Experimental Study

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How Would Medicaid Expansion Affect Texas Hospitals? Evidence From a Retrospective Quasi-Experimental Study

Meryem Saygili. Inquiry. 2022 Jan-Dec.

Abstract

This study aims to estimate the impact of a potential Medicaid expansion on Texas hospitals. The Affordable Care Act (ACA) Medicaid expansion increased access to health care and improved health outcomes. Still, several states, including Texas, have not adopted the expansion. This is a retrospective quasi-experimental study. We obtained inpatient data containing discharges from Texas hospitals between 2010 and 2017 from the Texas Department of State Health Services. Texas hospitals receive a significant number of patients from the adjacent states. We use a difference-in-differences methodology, where the patients from the neighboring states that expanded Medicaid in 2014 are the treatment group, and those that reside in Texas are the control group. The outcome variables are the payer mix and the cost of treatment, proxied by Diagnoses Related Group (DRG) weights assigned by the Centers for Medicare and Medicaid Services (CMS). The Medicaid expansion is associated with 4.15% lower costs of treatment among the patients from the expansion states (P < .01). Also, the uninsured rate decreased by 4.7 percentage points (from 11.3%, P < .01), while the share of Medicaid patients increased by 10.9 percentage points (from 30.7%, P < .01). There are no significant changes in the share of privately insured or Medicare patients. Texas hospitals can benefit significantly from Medicaid expansion due to reductions in average treatment costs and the share of the uninsured.

Keywords: DRG weights; Medicaid expansion; Texas Hospital Data; difference-in-differences; payer mix.

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Conflict of interest statement

Declaration of Conflicting Interests: The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Figures

Figure 1.
Figure 1.
Parallel trends. The figure shows the predictive margins of the year-treated interactions in equation (2) for each outcome variable along with their 95% confidence intervals. DRG = Diagnostic Related Group.

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