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

项目总结 脓毒症是一种由免疫系统对感染的反应引起的毁灭性疾病。170万 美国人每年因脓毒症住院治疗，导致超过27万人死亡。脓毒症更常见 在老年患者中，导致2018年联邦医疗保险受益人的支出总计410亿美元。治疗 不同医院的费用和剧集支出也有很大差异，这在很大程度上是由急性后护理的差异推动的。 为了改善护理，脓毒症被列为下列31个目标住院病例之一 联邦医疗保险的高级护理改善捆绑付款(BPCI-A)计划。BPCI-A是一项志愿服务 该计划为医院创造激励措施，以改善患者的结果并减少90- 出院后一天的插曲。BPCI-A有可能鼓励医院更有效地管理 患者在入院期间避免后续并发症和出院时视力下降 急性后设置。同时，BPCI-A并不主要是为了提高质量而设计的，而且在 患者的结果--无论是积极的还是消极的--将与医院减少支出的努力密切相关。病人 患有阿尔茨海默病和相关痴呆(ADRD)的人更有可能发展为脓毒症和 更糟糕的结果。ADRD患者的病程费用非常高，尤其容易患上 出院后的不良后果，使他们在BPCI-A下对脓毒症的治疗至关重要 理解。在ADRD之外，患者风险和脓毒症护理路径如何影响患者预后 BPCI-A中的脓毒症还没有被很好地理解。在这方面，我们提出以下目标：目标1。 评价BPCI-A对脓毒症患者预后的影响。我们将把医院参与BPCI联系起来- A使用国家医疗保险数据来测试该计划对死亡率、再入院、急性后护理、 活着和在家的日子，繁重的过渡，以及出院到临终关怀。目标2.评估以下项目的效果 BPCI-A对脓毒症患者ADRD预后的影响。使用经过验证的Medicare索赔算法来识别 对于ADRD患者，我们将测试BPCI-A对ADRD患者预后的影响。目标3.理解 以下情况下临床风险、治疗和急性护理后治疗模式和结果的关系 BPCI-A。使用密歇根州败血症计划中链接到联邦医疗保险索赔数据的唯一数据，我们将确定 预测患者结局的临床治疗模式、患者风险因素和医院特征。 我们将检查参与BPCI-A的医院是否采用了一套不同的战略来管理 脓毒症患者。我们的建议意义重大，因为它将国家数据与详细的临床见解结合在一起 了解国家政策与脓毒症患者细微差别临床护理之间的相互作用。我们的 Proposal的创新之处在于它将管理和注册数据源与复杂的 用定量的方法来回答一个新问题。

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.