Outcomes for Children with Asthma on Medicaid: Elucidating Key Determinants at the Policy, Plan, Neighborhood, and Person Levels to Address Disparities.

哮喘儿童医疗补助的结果：阐明政策、计划、社区和个人层面的关键决定因素，以解决差异。

• 批准号: 10429507
• 负责人: Anna Chorniy
• 金额: $ 16.76万
• 依托单位: NORTHWESTERN UNIVERSITY AT CHICAGO
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10429507
• 关键词: 18 year old; Accounting; Address; Adolescent; Adult; Affect; Algorithms; American; Architecture; Asthma; Biological; Black race; Caring; Characteristics; Child; Child Health; Childhood; Childhood Asthma; Chronic; Clinical; Community Surveys; Complement; Contracts; Data; Data Analyses; Data Analytics; Data Set; Development; Diagnosis; Disadvantaged; Economic Burden; Economics; Education; Emergency department visit; Family; Family Characteristics; Fee-for-Service Plans; Funding; Future; Geography; Goals; Health; Health Insurance; Health Personnel; Healthcare; Hospitalization; Impairment; Income; Individual; Insurance; Insurance Coverage; Justice; Knowledge; Leadership; Link; Low income; Managed Care; Managed Care Programs; Measures; Medicaid; Medicare; Mentors; Methodology; Methods; Modeling; National Heart, Lung, and Blood Institute; Natural experiment; Neighborhoods; Not Hispanic or Latino; Outcome; Patient-Focused Outcomes; Patients; Persons; Policies; Population; Privatization; Quality of Care; Quality of life; Records; Reduce health disparities; Research; Research Design; Research Personnel; Research Priority; Risk Factors; Role; Secure; Services; Shapes; Social Environment; Societies; Source; South Carolina; Time; To specify; Training; Uninsured; Variant; Vital Statistics; Work; academic preparation; advanced analytics; advanced simulation; beneficiary; care outcomes; clinical care; comorbidity; cost; design; disability; disparity reduction; economic evaluation; evidence base; experience; experimental study; health care disparity; health difference; health economics; hospitalization rates; implementation strategy; improved; innovation; insurance plan; lower income families; minority children; mortality; multidisciplinary; novel; population health; premature; preventable death; programs; provider factors; provider networks; racial and ethnic; simulation; skills; social health determinants; sociodemographics; socioeconomics

PROJECT SUMMARY/ABSTRACT Background: Asthma, a chronic condition that affects over five million US children, is more prevalent among racial/ethnic minority children and those from low-income families. Despite advances in asthma treatment, asthma clinical care and mortality rates in children have plateaued, and disparities persist across racial/ethnic and socioeconomic groups. I propose a training and research plan that will deepen my understanding of evidence-based clinical asthma care and the differential impacts of multifactorial causes underlying disparities in childhood asthma, while launching an innovative, policy-relevant research portfolio that combines multi- source, linked data to conduct “natural policy experiments” regarding Medicaid managed care (MMC) plans. Objective: To produce evidence regarding the “add-on” benefits of MMC plans and their relative effects on outcomes of children with asthma, accounting for factors at individual, family, and neighborhood levels. This evidence will be used to simulate different ways of assigning patients to MMC plans that best serve their needs and, ultimately, reduce health disparities. Aim 1. To examine evidence-based indicators of pediatric asthma care quality and outcomes across different MMC plans. Aim 2. To evaluate the role of individual, family, and neighborhood contributors—including sociodemographic, economic, and biological (comorbidity) risk factors— associated with asthma outcomes. Aim 3. To develop an algorithm that matches each patient with an MMC plan that helps them achieve the best possible asthma outcomes. Research Design: Natural experiment analyses and simulation methods using administrative longitudinal linked datasets from 2000-2021. Methods: I will collect detailed data on MMC plan benefits and rely on established quasi-random assignment of Medicaid beneficiaries to MMC plans, to specify a set of regression models aimed at estimating causal effects of plan benefits on asthma-related outcomes, individually and relative to the social determinants of health. These analyses will use individual and geographic-level linked South Carolina datasets that contain health, economic, sociodemographic outcomes, and comorbidities: Medicaid; Vital Statistics; Department of Education and Department of Juvenile Justice records; American Community Survey data. I will use simulation methods to evaluate child health outcomes under differing Medicaid policy scenarios, to match each child to an optimal MMC plan. Training Plan: To complement my existing skills in economics and data analysis and support my path to independence, I will gain essential training in: 1. Evidence and circumstances of clinical asthma care that will aid in constructing precise plan quality measures; 2. Stakeholder engagement that is key to (a) confirming details of plan coverage with MMC plans and leadership, (b) informing and disseminating research results, and (c) engaging with other states’ Medicaid programs in the future; 3. Advanced methodologic skills in policy simulations. Implications: This project will address NHLBI’s research priority to investigate factors that account for differences in health among populations via advancing methods for assessing impactful exposures.

项目总结/摘要 背景：哮喘是一种慢性疾病，影响着500多万美国儿童， 少数种族/族裔儿童和低收入家庭儿童。尽管哮喘治疗取得了进展， 儿童哮喘临床护理和死亡率趋于稳定，种族/民族之间的差异持续存在 和社会经济群体。我提出了一个培训和研究计划，以加深我对 基于证据的临床哮喘护理和多因素原因的差异性影响 儿童哮喘，同时推出一个创新的，与政策相关的研究组合，结合多， 来源，链接数据进行“自然政策实验”有关医疗补助管理式医疗（MMC）计划。 目的：提供关于MMC计划的“附加”益处及其对患者的相对影响的证据。 儿童哮喘的结果，占因素在个人，家庭和邻里水平。这 证据将用于模拟将患者分配到最适合其需求的MMC计划的不同方法 并最终减少健康差距。目标1.检查儿童哮喘的循证指标 不同MMC计划的护理质量和结果。目标2.评估个人、家庭和 邻里贡献者-包括社会人口统计学，经济和生物（comorbidity）风险因素- 与哮喘的结果有关。目标3.开发一种算法，将每个患者与MMC相匹配 帮助他们实现最佳哮喘治疗效果的计划。研究设计：自然实验 使用2000-2021年行政纵向关联数据集进行分析和模拟。方法：I 将收集有关MMC计划福利的详细数据，并依赖已建立的医疗补助准随机分配 MMC计划的受益人，指定一套回归模型，旨在估计计划的因果影响， 对哮喘相关结果的益处，单独和相对于健康的社会决定因素。这些 分析将使用个人和地理级别的链接南卡罗来纳州数据集，其中包含健康，经济， 社会人口学结局和合并症：医疗补助;生命统计;教育部和 少年司法部记录;美国社区调查数据。我将使用模拟方法， 在不同的医疗补助政策情景下评估儿童健康结果，以使每个儿童都能获得最佳的医疗补助。 MMC计划。培训计划：补充我现有的经济学和数据分析技能，并支持我的 在通往独立的道路上，我将获得以下方面的基本培训：1。哮喘临床护理的证据和情况 这将有助于构建精确的计划质量措施; 2.利益攸关方的参与是（a） 与MMC计划和领导层确认计划覆盖范围的细节，（B）通知和传播研究 结果，以及（c）在未来参与其他州的医疗补助计划; 3。先进的方法论技能， 政策模拟。影响：本项目将解决NHLBI的研究优先调查的因素， 通过改进评估影响性接触的方法，说明不同人群的健康差异。