Revealing and Resolving Institutional Racism in the NICU

揭示并解决新生儿重症监护病房中的制度性种族主义

• 批准号: 10743828
• 负责人: Jochen Profit
• 金额: $ 65.61万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-21 至 2028-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10743828
• 关键词: Abbreviations; Address; Administrator; Area; Automobile Driving; Benchmarking; Black race; California; Caring; Characteristics; Clinical; Collaborations; Communication; Data; Data Set; Dimensions; Disparity; Epidemiology; Equity; Ethnic Origin; Evaluation; Exhibits; Funding; Future; Graph; Health Personnel; Healthcare; Hispanic; Hospitals; Human Milk; Infant; Infrastructure; Institutional Racism; Intervention; Interview; Joints; Knowledge; Learning; Link; Maps; Measures; Methods; Minority; Modeling; Necrotizing Enterocolitis; Neonatal Intensive Care Units; New York City; Nursing Staff; Organization administrative structures; Outcome; Ownership; Patient Discharge; Performance; Perinatal; Perinatal Care; Personal Satisfaction; Policy Maker; Population; Premature Infant; Process; Public Health; Quality of Care; Race; Reporting; Research; Resources; Risk; Risk Adjustment; Safety; Sampling; Site; Site Visit; Statistical Computing; Structure; Surveys; Time; United States; United States National Institutes of Health; Variant; Very Low Birth Weight Infant; Vital Statistics; Vulnerable Populations; Work; burnout; care delivery; clinical care; cohort; dashboard; data resource; design; deviant; disparity reduction; ethnic disparity; feeding; health care disparity; health equity; healthcare-associated infections; implementation framework; improved; informant; innovation; learning network; multimodality; novel; patient population; peer; peer learning; peer networks; population based; primary outcome; racial disparity; safety net; safety study; segregation; social; social factors

Safety net newborn intensive care units (snNICUs) have been identified as contributors to the stark disparities in care and outcomes delivered to the 60,000 very low birth weight (VLBW; <1500g) infants born annually in the United States. Usual explanations for these findings highlight social risk and limited hospital resources as key drivers. However, in our population-based California cohort of NICUs, we find large variation in performance across safety net NICUs. For example, in a key national quality metric, any breast milk feeding at discharge, which exhibits the largest racial ethnic disparities, California snNICUs as a group perform worse that non-safety net NICUs. However, some snNICUs are among the state’s best performers (positive deviants), even after risk adjustment. There is a dearth of knowledge regarding the malleable organizational features differentiating quality of care across snNICUs. We propose to bridge this gap by gaining a deep understanding of network characteristics and their links to clinical care and outcomes. We will accomplish this by leveraging the unique population-based data resources and applied quality improvement expertise of the California Perinatal Quality Care Collaborative (CPQCC) to conduct a novel improvement collaborative among snNICUs to address performance and disparities in breast milk feeding rates at discharge for VLBW infants. This collaborative will serve to create an unprecedented peer learning network of snNICUs and serve as a vehicle for our team for a multimodal inquest to study the organizational features that either promote or degrade quality of care. We propose a large, population-scale study of snNICUs, with a large estimated sample of approximately 5,300 VLBW infants receiving care in 30 NICUs between 2024 to 2026. Specific aims: 1. Conduct a quality improvement collaborative of safety net NICUs, 2. Identify organizational features that may be associated with quality of care delivery, and 3. Associate safety net NICU organizational features with clinical outcomes. Our analyses will be guided by quality and implementation frameworks. Methods will include an Institute of Healthcare Improvement style quality improvement collaborative, quantitative validated surveys of safety culture and healthcare worker well-being, key informant interviews, and guided site visits. We will link organizational features with clinical quality of care and outcome metrics using epidemiological causal and observational modeling approaches. We have a long track record of impactful research funded by NIH using CPQCC data. We expect our research to have an immediate positive impact; internally, it is designed to build quality and safety capacity in snNICUs that can readily be extended to other aspects of care; externally, it will result in actionable information for policy makers, administrators and clinicians to improve perinatal care delivery and equity. The topic is timely, the sample (~90% of all CA snNICUs) is unique, the research team is accomplished, and the focus on an outcome of high importance to snNICUs, and to public health are significant strengths of this study.

安全网新生儿重症监护病房（SNNICUS）已被确定为史塔克分布的贡献者 在每年出生的儿童的护理和结局中， 美国。这些发现的通常解释突出了社会风险，医院资源有限作为关键 司机。但是，在我们基于人口的加利福尼亚NICUS中，我们发现性能的差异很大 整个安全网NICUS。例如，在关键的国家质量指标中，出院时的任何母乳喂养， 表现出最大的种族种族分布，加利福尼亚Snnicus的表现更糟糕 NET NICUS。但是，即使在风险之后，有些人是该州表现最好的人之一 调整。关于可延展的组织特征与质量不同的知识死亡 整个Snnicus的护理。我们建议通过深入了解网络来弥合这一差距 特征及其与临床护理和结果的联系。我们将通过利用独特的方式来实现这一目标 加利福尼亚围产期质量的基于人群的数据资源和应用质量改进专业知识 护理协作（CPQCC）在SNNICUS中进行新颖的改进协作以解决 VLBW婴儿出院时母乳喂养率的表现和差异。这个协作意愿 为建立一个空前的SNNICUS同行学习网络，并为我们的团队提供工具 多模式调查以研究促进或退化护理质量的组织特征。我们 提案对SNNICUS的大量人口规模研究，大量样本约为5,300 VLBW婴儿在2024年至2026年之间在30个NICUS接受护理。具体目的： 1。进行安全网NICUS的质量改进协作， 2。确定可能与护理质量相关的组织特征，以及 3。安全网络NICU组织特征与临床结果。 我们的分析将以质量和实施框架为指导。方法将包括一个研究所 医疗保健改进样式质量改进协作，定量验证的安全文化调查 以及医护人员的福祉，主要的线人访谈和指导的现场访问。我们将链接组织 具有流行病学因果和观察性的临床护理质量和结果指标的特征 建模方法。我们拥有使用CPQCC数据资助的有影响力研究的悠久记录。我们 期望我们的研究会产生直接的积极影响；在内部，它旨在建立质量和安全性 可以轻易扩展到护理的其他方面的Snnicus的能力；在外部，这将导致可行 政策制定者，管理人员和临床医生的信息，以改善围产期护理和公平性。 主题是及时的，样本（占所有CA Snnicus的90％）是独一无二的，研究团队已完成，并且 专注于对SNNICUS和公共卫生高度重要的结果，这是这项研究的重要优势。