The Impact of Federal COVID-19 Provider Relief Funds on Patients, Hospitals, and Disparities

联邦 COVID-19 提供者救济基金对患者、医院和差异的影响

• 批准号: 10673511
• 负责人: Jason David Buxbaum
• 金额: $ 4.31万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2024-07-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10673511
• 关键词: Impact; Federal; COVID; 19; Provider

Project Summary/Abstract The outbreak of COVID-19 in 2020 imposed extreme demands on the US medical system. Congress responded with $178 billion in emergency relief to be shared among hospitals, physicians, and other providers. However, little is known about the impact of these funds on inpatient capacity, patient experience, patient mortality, or closure and consolidation. The impact of funding on racial/ethnic disparities is also unknown. I aim to address these gaps in knowledge. I propose to exploit a natural experiment made possible by how the US Department of Health and Human Services (HHS) distributed $34 billion in COVID-19 relief funds for hospitals. These funds, awarded to safety- net hospitals and hospitals with high numbers of COVID-19 cases early in the pandemic, were allocated using formulas with inflexible thresholds. Using regression discontinuity methods, I will compare outcomes at hospitals barely missing the criteria for funding with hospitals barely surpassing the criteria for funding. I will extend the common regression discontinuity design to accommodate the multi-variable, multi-cutoff formulas adopted by HHS for fund allocation. Results will have broad policy relevance in several respects, irrespective of whether I detect statistically significant effects. Findings will speak to the advisability of channeling finite resource to the acute care system when public health conditions next overwhelm capacity. Evaluation of this relationship between funding and capacity will speak directly to AHRQ’s focus on improving safety, quality, and access. The research will increase understanding of the trade-off between quality and affordability, which can in turn inform decisions around cost containment. In addition, the research will contribute to understanding of the relationship between hospital funding, hospital closures, and competition-reducing consolidation. Closures and consolidation represent perennial challenge to access and affordability – areas of key focus for AHRQ. Finally, findings will speak to the extent that politically viable, “color-blind” policies can reduce disparities across racial and ethnic lines. In so doing, findings can inform the tactics used by policymakers and advocates to reduce healthcare inequities

项目总结/摘要 2020年爆发的COVID-19对美国的医疗系统提出了极端的要求。国会 政府提供了1780亿美元的紧急救援资金，由医院、医生和其他医疗服务提供者分担。 然而，很少有人知道这些资金对住院病人的能力，病人的经验，病人 死亡率，或关闭和巩固。供资对种族/族裔不平等的影响也不清楚。我 我们的目标是填补这些知识空白。 我建议利用一个自然的实验，使美国卫生和人类部如何成为可能， 卫生和公众服务部（HHS）为医院分发了340亿美元的COVID-19救济资金。这些资金，授予安全- 净医院和疫情初期COVID-19病例数高的医院， 具有不灵活阈值的公式。使用回归不连续方法，我将比较 医院几乎不符合资助标准，医院几乎不超过资助标准。我会 扩展通用回归不连续性设计以适应多变量、多截断值公式 由HHS分配资金。 结果将在几个方面具有广泛的政策相关性，无论我是否从统计学上发现 效果显著。调查结果将说明将有限资源引导到急性护理系统的可行性 当公共卫生条件下一次超过能力。评价供资与 能力将直接反映AHRQ对提高安全、质量和可及性的关注。这项研究将 提高对质量和可负担性之间的权衡的理解，这反过来可以为决策提供信息 围绕成本控制。此外，该研究将有助于了解 医院资金、医院关闭和减少竞争的合并。关闭和合并 是获得和负担能力方面的长期挑战-这是亚洲人权问题的主要重点领域。最后，调查结果将 在某种程度上，政治上可行的“色盲”政策可以减少种族和民族之间的差异 线在这样做的过程中，研究结果可以为政策制定者和倡导者减少医疗保健的策略提供信息 不平等