Novel approaches to profiling hospitals on critical illness mortality

分析医院危重病死亡率的新方法

基本信息

批准号：
9031140
负责人：
Jeremy M Kahn
金额：
$ 37.67万
依托单位：
UNIVERSITY OF PITTSBURGH AT PITTSBURGH
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-04-01 至 2018-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9031140
关键词：
Accounting Acute Acute Lung Injury Acute respiratory failure Address Admission activity Aging American Area Beds Caring Clinical Complex Critical Care Critical Illness Data Data Set Development Effectiveness Goals Health Health Policy Health care facility Health system Hospitals Incidence Intensive Care Units Measurement Measures Methods Modeling Organizational Change Outcome Outcome Assessment Outcome Measure Patient Transfer Patient-Focused Outcomes Patients Pennsylvania Performance Policies Policy Maker Population Probability Quality of Care Research Design Research Personnel Rewards Risk Role Sepsis Services Statistical Methods Statistical Models Structural Models Structure Syndrome System Techniques Testing Translating Translations Triage United States Validation Variant base care episode comparative effectiveness design effectiveness research high risk improved improved outcome innovation mortality neglect novel novel strategies tool ward

项目摘要

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.

描述（由适用提供）：危害疾病代表了卫生系统的极高烧伤。每年有4至700万美国人进入重症监护病房（ICU），而急性呼吸衰竭，急性肺损伤和败血症等重症疾病综合症的发生率将随着美国人群的老龄增长而急剧上升。结果，ICU是质量改进计划和旨在改善患者预后的比较有效性研究的越来越重要的领域。但是，由于缺乏对重症患者的医院绩效的良好测量，这些努力受到限制。现有的风险调整死亡率措施以几种关键方式受到限制。首先，他们只专注于接受ICU的患者，忽略了未被录取的严重住院的患者，忽略了ICU入院决策在患者预后中的作用，并且未能奖励医院病房中病人的高质量护理医院。其次，他们排除了从其他医院转移的患者，并且不考虑医院的出院习惯的差异，忽略了危重疾病后的护理过渡的作用，并且未能奖励医院对完全转移患者的高质量护理。第三，由于继承了结果措施的不可靠性，它们缺乏足够的精度，无法在临床或健康政策决策中有用。结果，当前经过风险调整的死亡率措施可能无法准确确定高性能的医院，从而阻碍了比较有效性研究和将临床证据转化为实践的努力。项目将通过开发和验证新的方法来解决这些问题的每一个问题，用于测量重症患者的医院特定风险调整的死亡率。 e基础我们的方法是在重点的重症监护质量的概念模型上，该模型强调了整个重症疾病的一集，而不仅仅是ICU中的护理情节。使用宾夕法尼亚州医院的临床和行政数据，我们将采用最先进的贝叶斯技术和创新的边缘结构建模方法来创建和测试医院特异性的重症监护死亡率，以说明ICU入院实践和医院间转移的变化。然后，我们将开发一种对重症监护死亡率率的新综合测量，该测量结合了有关护理结构和结果的信息，以提高结果评估的精度。我们的研究结果将为临床医生和政策制定者提供新的测量工具，以评估全国范围内的重症监护绩效，并为研究人员提供新的措施，以测试旨在改善急性呼吸衰竭和其他形式的重症患者的系统范围临床和政策创新的有效性。