Benefits of ICU admission for patients with acute respiratory failure or sepsis: A mixed-methods study across 26 hospitals

患有急性呼吸衰竭(ARF)和脓毒症(急性呼吸衰竭最常见和致命的原因)的患者 呼吸窘迫综合征)在美国通常被送进重症监护病房(ICU)，甚至 当他们不需要生命支持的时候。然而，这些患者的ICU入院率差别很大。 由于床位的可获得性，随着时间的推移，在医院之间甚至在医院内也是如此。这种做法的可变性表明 一些病人可能被“分流不足”到病房，而他们的结果可以通过送到病房来改善。 直接送往ICU(例如，由于护士或呼吸治疗师的密切监测)。其他病人可能会“过度-- 当他们的结果和护理费用会一样好或更好时，通过直接将他们送到 病房(例如，由于较少的精神错乱或不能动)。此外，确定这些“随意”ICU中的哪一个 病房的入院可以得到同样或更好的治疗，这将改善患有以下疾病的患者及时获得ICU的机会 更高级的心肺衰竭形式和更明显的ICU入院指征。 为了通过优化ARF和/或脓毒症患者的分诊来改善他们的预后，该应用程序提出了一种 上海地区26家不同医院急诊科就诊患者的混合方法研究 Kaiser Permanente North California Health System和宾夕法尼亚大学健康系统。我们的 主要目标是确定哪些ARF和/或脓毒症患者从ICU入院中受益，哪些 急诊科、病房和ICU的护理特点和流程有助于形成这样的网络ICU 福利。几项方法创新将使我们能够实现这些目标，并超越关键 先前的研究试图确定哪些危重患者从ICU入院中受益，但这些研究存在局限性。 首先，尽管之前的所有研究都使用了因果推理的方法，但这些方法容易被 医院之间不可测量的差异，我们将获得对哪些患者从ICU受益的公正估计 或通过将医院内变量-分诊时的ICU容量-建模为 工具变量。第二，尽管之前的研究无法准确确定哪些患者 结果适用于，我们研究医院中可用的细粒度电子健康记录数据将使我们的 结果直接适用于具有良好特征的个体患者，促进个性化分诊决定。 第三，我们在获得大小净ICU的医院中使用人种志和半结构化访谈 效益将确定不同医院在ICU和病房实现改善结果的机制。 完成这项研究的目标将通过确定紧急情况下 科室、ICU和病房可以改善每个住院的400多万美国人的结局 患有ARF和/或脓毒症的一年。这样的结果还将提供开发和测试分诊所需的证据 向急诊科提出的改善ARF和/或脓毒症患者预后的算法。

Patients with acute respiratory failure (ARF) and sepsis (the most common and lethal cause of the acute respiratory distress syndrome) are commonly admitted to intensive care units (ICUs) in the United States even when they do not require life support. However, ICU admission rates for these patients vary considerably among hospitals and even within hospitals over time due to bed availability. This practice variability suggests that some patients may be “under-triaged” to wards when their outcomes could be improved by sending them directly to the ICU (e.g., due to closer nurse or respiratory therapist monitoring). Other patients may be “over- triaged” to ICUs when their outcomes and costs of care would be as good or better by sending them directly to wards (e.g., due to less delirium or immobility). Furthermore, determining which of these “discretionary” ICU admissions could be treated as well or better on wards would improve timely access to ICUs for patients with more advanced forms of cardiorespiratory collapse and more obvious indications for ICU admission. To improve outcomes for patients with ARF and/or sepsis by optimizing their triage, this application proposes a mixed-methods study of patients admitted through the emergency departments of 26 diverse hospitals in the Kaiser Permanente Northern California health system and the University of Pennsylvania Health System. Our primary goals are to determine which patients with ARF and/or sepsis benefit from ICU admission, and which emergency department, ward, and ICU characteristics and processes of care contribute to such net ICU benefits. Several methodological innovations will enable us to achieve these goals, and to surmount key limitations to prior studies that have sought to determine which acutely ill patients benefit from ICU admission. First, whereas all prior studies used approaches to causal inference that were susceptible to confounding by unmeasured differences among hospitals, we will obtain unbiased estimates of which patients benefit from ICU or ward admission by modeling a within-hospital variable – ICU capacity at the time of triage – as an instrumental variable. Second, although prior studies have been unable to determine exactly which patients the results apply to, the granular electronic health record data available across our study hospitals will enable our results to apply directly to well-characterized individual patients, promoting personalized triage decisions. Third, our use of ethnography and semi-structured interviews in hospitals that obtain large and small net ICU benefits will identify mechanisms by which different hospitals achieve improved outcomes in ICUs and wards. Completing the aims of this study will improve public health by identifying ways in which emergency departments, ICUs, and wards can improve outcomes for the more than 4 million Americans hospitalized each year with ARF and/or sepsis. Such results will also provide the evidence needed to develop and test triage algorithms to improve outcomes for patients with ARF and/or sepsis presenting to emergency departments.