EnCoRe MOMS: Engaging Communities to Reduce Morbidity from Maternal Sepsis

EnCoRe MOMS：让社区参与降低孕产妇败血症的发病率

• 批准号: 10611196
• 负责人: Alexander M Friedman
• 金额: $ 95.8万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-21 至 2023-09-20
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10611196
• 关键词: Accountability; Accounting; Address; Advocacy; Affect; Algorithms; Biometry; Birth; Black race; Caring; Cessation of life; Clinical; Communication; Communities; Community Health Aides; Community Hospitals; Continuity of Patient Care; Data Set; Databases; Disadvantaged; Discipline of Nursing; Discipline of obstetrics; Education; Effectiveness; Electronic Health Record; Ensure; Ethnic Origin; Evidence based intervention; Focus Groups; Health Services Accessibility; Health Services Research; Health system; Hospitals; Individual; Informatics; Inpatients; Intervention; Interview; Joints; Knowledge; Lead; Leadership; Maternal Health; Maternal Mortality; Maternal-fetal medicine; Modeling; Morbidity - disease rate; Neighborhoods; Outcome; Outcome Measure; Patients; Pattern; Perinatal; Perinatal Epidemiology; Persons; Phase; Policies; Postpartum Period; Poverty; Pregnancy; Prevention; Process; Process Measure; Protocols documentation; Provider; Quality of Care; Race; Readiness; Reporting; Research; Research Infrastructure; Resources; Risk; Safety; Sampling; Sepsis; Services; Site; Social Environment; Social Sciences; Standardization; Structural Racism; Supportive care; System; Time; Training; Translating; Use Effectiveness; Variant; adverse maternal outcomes; base; clinical risk; community based participatory research; community center; community engaged research; community engagement; community partnership; design; disability; ethnic diversity; evidence base; experience; health care availability; health equity; health inequalities; health training; high risk; implementation framework; implementation process; implementation science; implicit bias; individual patient; inpatient service; machine learning model; maternal morbidity; maternal outcome; maternal risk; mortality; multidisciplinary; novel; patient oriented; postpartum morbidity; prevent; racial and ethnic; racial diversity; response; risk prediction; screening; severe maternal morbidity; social; social epidemiology; social health determinants; socioeconomic disadvantage; standard of care; support network; underserved community

Maternal sepsis is the second leading cause of maternal death, major cause of morbidity, and preventable in most cases. Labor, birth, and postpartum are periods of increased sepsis risk, particularly for racial and ethnic minoritized birthing people. Yet few evidence-based interventions exist. With our extensive community partnerships and community organized leadership advisory board (CoLAB), EnCoRe MoMS: Engaging Communities to Reduce Morbidity from Maternal Sepsis will address three highly related specific aims: (Aim 1) Develop, implement, and evaluate a community-informed maternal sepsis bundle in 4 diverse NYC hospitals; (Aim 2) Develop algorithms to optimize prediction of sepsis around delivery and postpartum; and (Aim 3) Conduct a co-design process and qualitative study to explore the experiences, needs, and perceived solutions for maternal care continuity, sepsis prevention, and promotion of equity in postpartum. In the UG3 phase we will establish robust community engagement and research infrastructures to: Aim 1a: Design a comprehensive obstetric sepsis bundle that i) applies and optimizes standard evidence-based components of readiness, recognition, response, reporting, and respectful care ii) incorporates multidisciplinary obstetric provider implicit bias training, and iii) integrates social determinants of health (SDOH) training and screening Aim 2a. Create a rich electronic health records (EHR) database from the Perinatal Research Consortium (PRC). Aim 2b. Collate neighborhood-level datasets characterizing social determinants of health (SDOH) Aim 3a. (3a.1) Refine our CoLAB and co-design process; (3a.2) Conduct in-depth individual patient interviews (IDIs) and focus group discussions (FGDs) with community and hospital stakeholders from one site to explore the lived experiences and perspectives of SDOH on care access/quality, outcome disparities, and solutions for care continuity. In the UH3 phase, we will engage community to implement our maternal sepsis care model, analyze results, and translate findings. Aim 1b. Implement our comprehensive obstetric sepsis bundle and evaluate its effectiveness using process and outcome measures Aim 1c. Define patterns in EHR of provider response to suspected sepsis, pre- vs post-bundle implementation; analyze associations between provider response variation and outcomes Aim 2c. Harmonize patient-level EHR and neighborhood-level SDOH datasets and use machine learning models to analyze the individual and joint contributions of patient and neighborhood factors to optimize sepsis risk prediction within the PRC sample Aim 3b. (3b.1) Complete qualitative patient IDIs and stakeholder FGDs for the three additional hospital sites; (3b.2) Co-design an integrative supportive care model, with our community partner co-lead, CoLAB, and results from other aims, that entails maternal sepsis community engagement, care linkages, education, services, and policy efforts. Our resulting model can be scaled to hospitals and communities with lesser resources and applied to other preventable causes of severe maternal morbidity.

产妇败血症是导致产妇死亡的第二大原因，也是发病率的主要原因，而且是可以预防的