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; 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

项目摘要/摘要 Covid-19 2020年的爆发对美国医疗系统施加了极大的需求。国会 回应了1780亿美元的紧急救济，将在医院，医师和其他提供者之间分享。 但是，这些资金对住院容量，患者经验，患者的影响知之甚少 死亡率或封闭和巩固。资金对种族/族裔差异的影响也未知。我 旨在解决知识中的这些差距。 我建议探索美国卫生和人类部如何实现自然实验 服务（HHS）为医院的Covid-19救济资金分配了340亿美元。这些资金授予安全 - 在大流行中早期，大量1900例19案的净医院和医院被使用 具有不灵活阈值的公式。使用回归不连续方法，我将在 医院几乎没有缺少用于医院资金的标准，几乎没有超过资金标准。我会 扩展常见的回归不连续设计，以适应多变量的多切法公式 由HHS通过用于资金分配。 结果在几个方面都将具有广泛的政策相关性，而不管我是否从统计上检测到 重大影响。调查结果将与将有限资源传达给急性护理系统的咨询 当公共卫生条件下一个压倒性的能力时。评估资金与 容量将直接说明AHRQ专注于提高安全性，质量和访问权限。研究将 提高对质量和负担能力之间权衡的理解，这反过来可以为决策提供信息 围绕成本控制。此外，该研究将有助于理解 医院资金，医院关闭和减少竞赛的合并。封闭和合并 代表了多年生挑战和可承受能力 - AHRQ的关键重点领域。最后，发现会 在政治上可行的“色盲”政策可以减少种族和种族的分布程度 线。这样做，发现可以为决策者和倡导者使用的策略提供减少医疗保健的策略 不平等