Early Impact of the Affordable Care Act Coverage Expansion on Safety‐Net Hospital Inpatient Payer Mix and Market Shares

Wu, Vivian Y.; Fingar, Kathryn R.; Jiang, Hui; Washington, Raynard; Mulcahy, Andrew W.; Cutler, Eli; Pickens, Gary

doi:10.1111/1475-6773.12812

Cited by 3 publications

(2 citation statements)

References 21 publications

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“…Studies of Medicaid expansion under the Patient Protection and Affordable Care Act (ACA) 1,2 have had conflicting findings regarding safety-net hospital (SNH) utilization and have not examined racial/ ethnic differences in SNH use. We used data with a larger number of states; substantial racial/ethnic minority populations, including nearly 83% of the national Hispanic population; and with a longer period of observation.…”

Section: Introductionmentioning

confidence: 99%

Changes in Hospitalizations at US Safety-Net Hospitals Following Medicaid Expansion

et al. 2021

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possible that the persistence of structural racism and residential segregation prevents patients from transferring care to non-SNHs. A limitation of this study is that unmeasured state policy changes may explain our findings. Extending health insurance coverage alone appears insufficient to reduce hospital segregation by race/ethnicity or socioeconomic status. Future research should identify factors that underlie the use of SNHs among patients with low income.

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Section: Introductionmentioning

confidence: 99%

Changes in Hospitalizations at US Safety-Net Hospitals Following Medicaid Expansion

et al. 2021

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“…Largely made up of public and private non-profit community hospitals, SNHs shoulder a heavy burden of the nation's provision of care to uninsured and Medicaid-insured populations, which is to say a heavy burden of un-compensated and under-reimbursed care, respectively (Coughlin et al, 2014;Sutton, 2016). Consequently, the typical SNH is intrinsically exposed to an elevated risk of financial distress, reliance on supplemental funding, and vulnerability to market and public policy dynamics, as compared to non-SNHs (Bazzoli et al, 2005;Zuckerman et al, 2001;Reiter et al, 2014;Coughlin et al, 2015;Neuhausen et al, 2014;Wu et al, 2018;Fingar et al, 2018;Machta et al, 2019). Thus, while it is certainly important that the antecedents and consequences of payment adjustments under these programs are monitored closely for all hospitals, it is particularly important that special attention be paid to the experience of SNHs under these programs given the high stakes that these institutions face and the critical role that they play in our nation's healthcare system as providers of last resort for the least well off among us.…”

Section: Introductionmentioning

confidence: 99%

Antecedents and consequences of net payment adjustments under medicare pay-for-performance programs and hospitals generally and safety net hospitals in particular

Young

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Baseline sample characteristics by level of penalty burden………………………………….67 Trends in outcomes by level of penalty burden………………………………………….…..68 Association between penalty burden and outcomes…………………………….…………..68 Validity of DiD results……………………………………………………………..………..72 Heterogeneity in effects by SNH status……………………………………….…………….74 Consequences Aim-specific Figures and Tables………………………………..…………..

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The impact of hospital safety-net status on inpatient outcomes for brain tumor craniotomy: a 10-year nationwide analysis

Tang

Perla

Lim

et al. 2020

Neuro-Oncology Advances

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Background Outcome disparities have been documented at safety-net hospitals (SNHs), which disproportionately serve vulnerable patient populations. Using a nationwide retrospective cohort, we assessed inpatient outcomes following brain tumor craniotomy at SNHs in the United States. Methods We identified all craniotomy procedures in the National Inpatient Sample from 2002-2011 for brain tumors: glioma, metastasis, meningioma, and vestibular schwannoma. Safety-net burden was calculated as the number of Medicaid plus uninsured admissions divided by total admissions. Hospitals in the top quartile of burden were defined as SNHs. The association between SNH status and in-hospital mortality, discharge disposition, complications, hospital-acquired conditions (HACs), length of stay (LOS), and costs were assessed. Multivariate regression adjusted for patient, hospital, and severity characteristics. Results 304,719 admissions were analyzed. The most common subtype was glioma (43.8%). Of 1,206 unique hospitals, 242 were SNHs. SNH admissions were more likely to be non-white (P<0.001), low-income (P<0.001), and have higher severity scores (P=0.034). Mortality rates were higher at SNHs for metastasis admissions (odds ratio [OR]=1.48, P=0.025), and SNHs had higher complication rates for meningioma (OR=1.34, P=0.003) and all tumor types combined (OR=1.17, P=0.034). However, there were no differences at SNHs for discharge disposition or HACs. LOS and hospital costs were elevated at SNHs for all subtypes, culminating in a 10% and 9% increase in LOS and costs for the overall population, respectively (all P<0.001). Conclusions SNHs demonstrated poorer inpatient outcomes for brain tumor craniotomy. Further analyses of the differences observed and potential interventions to ameliorate interhospital disparities are warranted.

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Early Impact of the Affordable Care Act Coverage Expansion on Safety‐Net Hospital Inpatient Payer Mix and Market Shares

Abstract: Postexpansion, non-SNHs experienced a greater percentage increase in Medicaid stays than did SNHs, which may reflect patients choosing non-SNHs over SNHs or a crowd-out of private insurance. More research is needed to understand these trends.

Cited by 3 publications

References 21 publications

Changes in Hospitalizations at US Safety-Net Hospitals Following Medicaid Expansion

Changes in Hospitalizations at US Safety-Net Hospitals Following Medicaid Expansion

Antecedents and consequences of net payment adjustments under medicare pay-for-performance programs and hospitals generally and safety net hospitals in particular

The impact of hospital safety-net status on inpatient outcomes for brain tumor craniotomy: a 10-year nationwide analysis

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