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.

项目概要/摘要 背景：哮喘是一种影响超过 500 万美国儿童的慢性疾病，在 尽管哮喘治疗取得了进展，但少数族裔儿童和来自低收入家庭的儿童。 儿童哮喘临床护理和死亡率已趋于稳定，不同种族/族裔之间仍然存在差异 我提出了一项培训和研究计划，以加深我对以下方面的理解： 基于证据的临床哮喘护理和多因素根本原因差异的不同影响 在儿童哮喘方面，同时推出了一个创新的、与政策相关的研究组合，该组合结合了多方面的研究 来源，链接数据以进行有关医疗补助管理式医疗（MMC）计划的“自然政策实验”。 目标：提供有关 MMC 计划的“附加”好处及其对人的相对影响的证据 哮喘儿童的结局，考虑个人、家庭和社区层面的因素。 将使用证据来模拟将患者分配到最能满足其需求的 MMC 计划的不同方式 目标 1：检查小儿哮喘的循证指标。 不同 MMC 计划的护理质量和结果 目标 2. 评估个人、家庭和患者的作用。 社区因素——包括社会人口、经济和生物（合并症）风险因素—— 目标 3. 开发一种将每位患者与 MMC 相匹配的算法。 帮助他们实现最佳哮喘结果的计划 研究设计：自然实验。 使用 2000 年至 2021 年的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，指定一组旨在估计计划因果效应的回归模型 对哮喘相关结果的益处，无论是个体还是相对于健康的社会决定因素。 分析将使用个人和地理层面链接的南卡罗来纳州数据集，其中包含健康、经济、 社会人口统计结果和合并症：医疗补助；教育和人口统计部； 青少年司法部记录；我将使用模拟方法来记录。 评估不同医疗补助政策下的儿童健康结果，以将每个孩子匹配到最佳方案 MMC 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工作。 为了走向独立，我将获得以下方面的基本培训： 1. 临床哮喘护理的证据和情况 这将有助于制定精确的计划质量衡量标准； 2. 利益相关者的参与是 (a) 的关键 与 MMC 计划和领导层确认计划覆盖范围的详细信息，(b) 通报和传播研究成果 结果，以及 (c) 未来参与其他州的医疗补助计划； 3. 先进的方法技能； 政策模拟：该项目将解决 NHLBI 的研究重点，以调查影响因素。 通过先进的评估影响暴露的方法来解释人群之间的健康差异。