Novel approaches to profiling hospitals on critical illness mortality

 描述(由申请人提供)：危重疾病给卫生系统带来了极大的负担。每年有400万至700万美国人住进重症监护病房(ICU)，随着美国人口老龄化，急性呼吸衰竭、急性肺损伤和脓毒症等危重疾病综合征的发生率预计将大幅上升。因此，ICU是旨在改善患者结局的质量改进倡议和比较有效性研究的一个日益重要的领域。然而，由于缺乏对危重患者的医院绩效的强有力的衡量，这些努力受到限制。现有的经风险调整的死亡率指标在几个关键方面受到限制。 首先，他们只关注住进ICU的患者，忽视了没有入院的重症住院患者，忽视了ICU入院决定对患者预后的作用，没有奖励医院在医院病房为患者提供高质量的护理。其次，它们排除了从其他医院转来的患者，也没有考虑到不同医院之间出院做法的差异，忽视了危重疾病后护理过渡在预后中的作用，也没有奖励为复杂转院患者提供高质量护理的医院。第三，由于结果测量本身的不可靠性，它们缺乏足够的精确度，无法在临床或卫生政策决策中发挥作用。因此，目前的风险调整死亡率指标可能无法准确识别表现良好的医院，阻碍了比较有效性研究和将临床证据转化为实践的努力。该项目将通过开发和验证衡量危重患者特定医院风险调整死亡率的新方法来解决这些问题。E我们的方法基于危重护理质量的概念模型，该模型强调危重疾病的整个病程，而不仅仅是ICU内的护理病程。使用来自宾夕法尼亚州医院的临床和管理数据，我们将应用最先进的贝叶斯技术和创新的边际结构建模方法来创建和测试医院特定的危重护理死亡率，这些死亡率考虑到ICU入院实践和医院间转移的差异。然后，我们将开发一种新的重症监护死亡率的综合衡量标准，该衡量标准结合了有关护理结构和结果的信息，以提高结果评估的精确度。我们的结果将为临床医生和政策制定者提供新的衡量工具，用于评估全国范围内的危重护理表现，并为研究人员提供新的衡量标准，以测试旨在改善急性呼吸衰竭和其他形式危重疾病患者预后的全系统临床和政策创新的有效性。

 DESCRIPTION (provided by applicant): Critical illness represents an extraordinarily high burden on the health system. Between 4 and 7 million Americans are admitted to an intensive care unit (ICU) each year, and the incidence of critical illness syndromes like acute respiratory failure, acute lung injury and sepsis is expected to rise dramatically with the aging of the US population. As a result, the ICU is an increasingly important area for quality improvement initiatives and comparative effectiveness research designed to improve patient outcomes. However, these efforts are limited by the lack of a robust measure of hospital performance for critically ill patients. Existing risk-adjusted mortality measures are limited in several key ways. First, they only focus on patients admitted to the ICU, neglecting severely ill hospitalized patients who are not admitted, ignoring the role of ICU admission decisions in patient outcomes, and failing to reward hospitals for high-quality care for sick patients on the hospital ward. Second, they exclude patients transferred in from other hospitals and do not account for variation in discharge practices across hospitals, neglecting the role of care transitions in outcomes following critical illness and failing to reward hospitals for high-quality care of comple transfer patients. Third, due to the inherent unreliability of outcome measures they lack sufficien precision to be useful in clinical or health policy decisions. As a result, current risk-adjusted mortality measures may fail to accurately identify high-performing hospitals, hindering both comparative effectiveness research and efforts to translate clinical evidence into practice. This project will address each of these problems through the development and validation of novel methods for measuring hospital-specific risk-adjusted mortality rates for critically ill patients. e base our approach on a conceptual model of critical care quality that emphasizes the entire episode of critical illness, not just the episode of care within an ICU. Using clinical and administrative data from Pennsylvania hospitals, we will apply state-of-the-art Bayesian techniques and an innovative marginal structural modeling approach to create and test hospital- specific critical care mortality rates that account for variation in ICU admission practices and inter- hospital transfers. Then we will develop a new composite measure of critical care mortality rates that combines information about the structure and outcome of care to increase the precision of outcome assessment. Our results will provide clinicians and policy makers with novel measurement tools for assessing critical care performance on a national scale, as well as provide researchers with new measures to test the effectiveness of system-wide clinical and policy innovations designed to improve outcomes for patients with acute respiratory failure and other forms of critical illness.