Identifying Outcomes and Implementation Strategies to Optimize Prenatal Care Coordination

确定优化产前护理协调的结果和实施策略

• 批准号: 10710060
• 负责人: Lawrence M Berger
• 金额: $ 18.77万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-26 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10710060
• 关键词: Accounting; Address; Attention; Big Data; Birth Records; Black American; Caring; Child; Client; Clinical; Clinical Trials; Communities; Community Health Aides; Consolidated Framework for Implementation Research; Data; Data Set; Data Sources; Demographic Factors; Disparity; Emergency department visit; Enrollment; Ethnic Population; Failure; Fee-for-Service Plans; Focus Groups; Future; Geographic Locations; Goals; Grant; Health; Health Services; Health education; Home visitation; Hybrids; Individual; Infant; Infant Health; Infant Mortality; Intervention; Interview; Investments; Link; Logistic Regressions; Low Birth Weight Infant; Maternal Health; Maternal Mortality; Medicaid; Medicaid services; Medical; Modeling; Morbidity - disease rate; Mothers; Native Americans; Nurses; Outcome; Perinatal; Policies; Policy Maker; Population; Population Group; Populations at Risk; Positioning Attribute; Postpartum Period; Pregnancy; Premature Birth; Prenatal care; Provider; Public Health; Qualifying; Quality of Care; Race; Registered nurse; Research; Risk Assessment; Service delivery model; Services; Site; Social Conditions; Social Work; Social Workers; Social support; Source; Structure; Time; Translations; United States; Visit; Weight; Wisconsin; Woman; adverse birth outcomes; adverse outcome; behavioral health; black/white disparity; care coordination; care systems; disparity reduction; ethnic diversity; evidence base; flexibility; health care availability; high risk; high risk population; implementation determinants; implementation outcomes; implementation process; implementation strategy; implementation trial; improved; insight; integrated care; maternal morbidity; maternal outcome; mortality; patient home care; physical conditioning; psychosocial; racial disparity; racial diversity; racial population; service coordination; severe maternal morbidity; social; social determinants; structural health determinants; theories; treatment effect

PROJECT SUMMARY AND ABSTRACT Few interventions successfully address racial disparities in maternal health outcomes. Social conditions—or social and structural determinants of health—are the major causes of persistent racial disparities in the US. Integrated models of care that offer home visiting and care coordination can support maternal health and have the potential to meaningfully reduce disparities. Prenatal care coordination (PNCC) is a fee-for-service Medicaid benefit, available in several states including Wisconsin. Its goal is to reduce rates of adverse birth outcomes including low birthweight and premature birth among mothers and infants at high risk. PNCC services include health education, care coordination, social support, and facilitating access to medical care and social services during pregnancy and up to 60 days following delivery for Medicaid-covered mothers. The long-term aim of this research is to improve the health outcomes of high-risk mothers and reduce disparities between racial and ethnic groups by strengthening the PNCC benefit’s implementation and impact. Specifically, this study aims to: 1: Describe the association of receiving PNCC services with five distinct maternal health outcomes among mothers who delivered in WI between 2011 and 2019. Leveraging a large, multisource data set, which links all Wisconsin birth records from 2011-2019 to Medicaid claims and other administrative data sources, we will develop regression models for each of five target outcomes: 1) adequate prenatal care, 2) a 6-week postpartum visit, 3) utilization of needed behavioral health services, 4) occurrence of severe maternal morbidity, and 5) emergency department visits, accounting for mother’s race and geographic location. 2: Evaluate the treatment effect of using a structured model of care to guide PNCC on the 5 target outcomes among mothers who received PNCC services between 2011 and 2019, (a) accounting for interactions with PNCC provider type and site type, and (b) additionally accounting for mother’s race and geographic location. Data will be analyzed using two-level logistic regression models with PNCC site type (public health department, clinical setting, community-based agency) at level 2 and provider type (nurse, community health worker, social worker) as a covariate, and individuals nested within those sites at level 1. 3: Qualitatively describe diverse PNCC providers’ perspectives on the relative advantage of using a structured model to guide PNCC services, implementation processes that impact PNCC, and target outcomes of PNCC. Using a deductive qualitative approach, we will conduct semi-structured interviews and focus groups at five PNCC sites across the state that vary by provider type and setting, and who serve clients from racially and ethnically diverse communities including Black and Native American mothers. Analyses will be framed by the Consolidated Framework for Implementation Science (CFIR), which describes factors that can influence implementation and is flexible enough to apply in multiple contexts.

项目概要和摘要 很少有干预措施能够成功解决孕产妇健康状况或社会状况方面的种族差异。 健康的社会和结构性决定因素——是美国持续存在种族差异的主要原因。 提供家访和护理协调的综合护理模式可以支持孕产妇健康，并有 产前护理协调 (PNCC) 是一项按服务收费的医疗补助计划。 包括威斯康星州在内的多个州都提供这项福利，其目标是降低不良分娩结果的发生率。 包括低出生体重和早产的母亲和高危婴儿 PNCC 服务包括。 健康教育、护理协调、社会支持以及促进获得医疗保健和社会服务 受医疗补助覆盖的母亲在怀孕期间和产后 60 天内。 研究旨在改善高危母亲的健康状况并减少种族和民族之间的差异 具体来说，本研究旨在： 1：描述接受 PNCC 服务与五种不同孕产妇健康结果的关联 2011 年至 2019 年间在威斯康星州分娩的母亲。利用大型多源数据集，该数据集将所有 2011-2019 年威斯康星州出生记录到医疗补助索赔和其他行政数据源，我们将 为五个目标结果中的每一个制定回归模型：1) 充分的产前护理，2) 产后 6 周 访视，3) 利用所需的行为健康服务，4) 发生严重的孕产妇发病率，以及 5) 急诊科就诊，考虑到母亲的种族和地理位置。 2：评估使用结构化护理模型指导 PNCC 5 个目标结果的治疗效果 在 2011 年至 2019 年间接受 PNCC 服务的母亲中，(a) 考虑与 PNCC 的互动 提供商类型和站点类型，以及 (b) 另外考虑母亲的种族和地理位置数据。 使用具有 PNCC 站点类型（公共卫生部门、临床部门）的两级逻辑回归模型进行分析 2 级设置、社区机构）和提供者类型（护士、社区卫生工作者、社会工作者） 作为协变量，个人嵌套在第 1 级的这些站点中。 3：定性描述不同 PNCC 提供商对使用结构化的相对优势的看法 指导 PNCC 服务的模型、影响 PNCC 的实施流程以及 PNCC 的目标结果。 使用演绎定性方法，我们将在五点进行半结构化访谈和焦点小组 PNCC 站点遍布全州，根据提供者类型和环境的不同而有所不同，并且为不同种族和不同背景的客户提供服务。 种族多元化的社区，包括黑人和美洲原住民母亲。 分析将以实施科学综合框架（CFIR）为框架，该框架描述了 可以影响实施的因素，并且足够灵活，可以在多种情况下应用。