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（snNICU）已被确定为造成严重差异的因素 在护理和结果交付给60,000极低出生体重（VLBW; <1500克）婴儿每年出生在 美国的对这些发现的解释强调了社会风险和有限的医院资源是关键 司机然而，在我们基于人口的加州NICU队列中，我们发现性能差异很大 在新生儿重症监护室的安全网里例如，在一个关键的国家质量指标中，出院时的任何母乳喂养， 表现出最大的种族差异，加州snNICU作为一个群体表现更差， 净NICU。然而，一些snNICU是该州表现最好的（积极的偏离者），即使在风险之后， 加强结构性改革有一个知识的缺乏关于可塑性的组织特征区分质量 在snNICU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 加州围产期质量中心基于人群的数据资源和应用的质量改进专业知识 护理协作（CPQCC）在snNICU之间进行新的改进协作，以解决 极低出生体重婴儿出院时母乳喂养率的表现和差异。此次合作将 服务于创建一个前所未有的snNICU同行学习网络，并作为我们团队的工具， 多模态调查研究的组织特征，无论是促进或降低护理质量。我们 我建议对snNICU进行一项大规模的人群规模研究，估计样本量约为5，300 2024年至2026年期间在30个NICU接受护理的VLBW婴儿。具体目标： 1.开展安全网NICU质量改进协作， 2.识别可能与护理质量相关的组织特征，以及 3.将安全网NICU组织特征与临床结局相关联。 我们的分析将以质量和执行框架为指导。方法将包括研究所 医疗保健改进风格质量改进安全文化的协作、定量验证调查 和医疗保健工作者的福祉，关键线人访谈，并指导现场访问。我们将组织 使用流行病学因果关系和观察性指标的临床护理质量和结局指标特征 建模方法。我们有一个由NIH使用CPQCC数据资助的有影响力的研究的长期跟踪记录。我们 我希望我们的研究能立即产生积极的影响;在内部，它旨在建立质量和安全 snNICU的能力可以很容易地扩展到护理的其他方面;外部，它将导致可操作的 为决策者、行政人员和临床医生提供信息，以改善围产期护理的提供和公平性。的 主题是及时的，样本（约90%的CA snNICU）是唯一的，研究团队是有成就的， 关注对snNICU和公共卫生高度重要的结果是本研究的重要优势。