The impact of the Bundled Payment for Care Improvement Advanced on outcomes for patients with sepsis

项目摘要 脓毒症是一种毁灭性的条件所造成的免疫系统的反应感染。1.7万 美国人每年因败血症住院，导致超过270，000人死亡。脓毒症更常见 在老年患者中，导致2018年医疗保险受益人的支出总额为410亿美元。治疗 医院之间的成本和事件支出也存在很大差异，主要是由急性后护理的差异驱动的。 为了改善护理，脓毒症被列为31例住院患者的目标之一， Medicare的Bundled Payment for Care Improvement Advanced（BPCI-A）计划。BPCI-A是一个自愿的 该计划为医院提供激励措施，以改善患者的治疗效果，并在90年内减少支出， 出院后第2天。BPCI-A有可能鼓励医院更有效地管理 患者在入院期间，以避免随后的并发症，并出院患者较低的敏锐度 急性后环境。与此同时，BPCI-A的设计主要不是为了提高质量， 病人的治疗结果--无论是好是坏--都将与医院减少开支的努力密切相关。患者 阿尔茨海默病和相关痴呆症（ADRD）的患者更有可能发展为败血症， 更糟糕的结果。ADRD患者的发作花费非常高，特别容易受到 出院后的不良结局，使他们在BPCI-A下治疗脓毒症对于 明白在ADRD之外，患者风险和脓毒症护理途径如何影响患者结局， 在BPCI-A的背景下，脓毒症还没有得到很好的理解。在这方面，我们提出以下目标：目标1。 评价BPCI-A对脓毒症患者结局的影响。我们将把医院参与BPCI- 用国家医疗保险数据来测试该计划对死亡率、再入院、急性期后护理的影响， 在家里活着的日子，繁重的过渡，出院到临终关怀。目标2.的影响进行评估 BPCI-A对脓毒症伴ADRD患者结局的影响。使用经过验证的Medicare索赔算法来识别 在ADRD患者中，我们将测试BPCI-A对ADRD患者结局的影响。目标3.理解 临床风险，治疗和急性后护理治疗模式和结果之间的关系， BPCI-A。使用密歇根败血症倡议与医疗保险索赔数据相关的独特数据，我们将确定 临床治疗模式、患者风险因素和预测患者结局的医院特征。 我们将研究参与BPCI-A的医院是否部署了一套不同的策略来管理 脓毒症患者我们的提案意义重大，因为它结合了国家数据和详细的临床见解 了解国家政策与脓毒症患者细致入微的临床护理之间的相互作用。我们 该建议是创新的，它结合了管理和登记数据源， 用定量的方法来回答一个新的问题。

PROJECT SUMMARY Sepsis is a devastating condition resulting from the immune system’s reaction to infection. 1.7 million Americans are hospitalized annually with sepsis, resulting in over 270,000 deaths. Sepsis is more common among older patients, leading to spending among Medicare beneficiaries totaling $41B in 2018. Treatment costs and episode spending also vary widely across hospitals, driven largely by differences in post-acute care. In an attempt to improve care, sepsis was included as one of the 31 inpatient episodes targeted under Medicare’s Bundled Payment for Care Improvement Advanced (BPCI-A) program. BPCI-A is a voluntary program that creates incentives for hospitals to improve patient outcomes and reduce spending across a 90- day post-discharge episode. BPCI-A has the potential to encourage hospitals to more effectively manage patients during the admission to avoid subsequent complications and to discharge patients to lower acuity post-acute settings. At the same time, BPCI-A is not designed primarily to improve quality, and changes in patient outcomes – positive or negative – will be closely tied to hospital efforts to reduce spending. Patients with Alzheimer’s disease and related dementias (ADRD) are both more likely to develop sepsis and to have worse outcomes. Patients with ADRD have very high episode spending and are particularly vulnerable to adverse outcomes following discharge, making their treatment for sepsis under BPCI-A critically important to understand. Outside of ADRD, how patient risk and sepsis care pathways influence patient outcomes for sepsis in the context of BPCI-A are not well understood. In this context, we propose the following aims: Aim 1. Evaluate the effects of BPCI-A on outcomes for patients with sepsis. We will link hospital participation in BPCI- A with national Medicare data to test the effects of the program on mortality, readmission, post-acute care, days alive and at home, burdensome transitions, and discharge to hospice. Aim 2. Evaluate the effects of BPCI-A on outcomes for sepsis patients with ADRD. Using validated Medicare claims algorithms to identify patients with ADRD, we will test the impact of BPCI-A on outcomes for patients with ADRD. Aim 3. Understand the relationship between clinical risk, treatment, and post-acute care treatment patterns and outcomes under BPCI-A. Using unique data from the Michigan Sepsis Initiative linked to Medicare claims data, we will identify the clinical treatment patterns, patient risk factors, and hospital characteristics that predict patient outcomes. We will examine whether hospitals participating in BPCI-A deploy a different set of strategies to manage patients with sepsis. Our proposal is significant because it combines national data with detailed clinical insights to understand the interplay between national policy and nuanced clinical care for patients with sepsis. Our proposal is innovative in its combination of administration and registry data sources coupled with sophisticated quantitative methods to answer a novel question.