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.

项目摘要/摘要 背景：哮喘是一种影响超过500万美国儿童的慢性病，​​在 种族/族裔少数民族儿童以及来自低收入家庭的孩子。尽管哮喘治疗进展， 儿童的哮喘临床护理和死亡率已经平稳，种族/族裔的差异持续 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影响 在童年哮喘中，在推出创新的，与政策相关的研究组合时结合了多种多样的研究组合 来源，链接的数据以进行有关医疗补助托管护理（MMC）计划的“自然政策实验”。 目的：提供有关MMC计划“附加”益处及其对其对其对相对影响的证据 患有哮喘儿童的结果，考虑个人，家庭和邻里水平的因素。这 证据将用于模拟将患者分配到最能满足其需求的MMC计划的不同方式 并最终减少健康差异。目的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 社区贡献者 - 包括社会人口统计学，经济和生物学（合并症）风险因素 - 与哮喘结局有关。 AIM 3。开发与每个患者与MMC匹配的算法 计划有助于他们实现最佳的哮喘成果。研究设计：自然实验 从2000-2021开始使用管理纵向链接数据集的分析和仿真方法。方法：i 将收集有关MMC计划收益的详细数据，并依靠已建立的准随机分配医疗补助 MMC计划的受益人，指定一组旨在估算计划因果影响的回归模型 与健康的社会决定者有关哮喘相关结果的好处。这些 分析将使用包含健康，经济， 社会人口统计学结果和合并症：医疗补助；重要统计；教育部 少年司法记录；美国社区调查数据。我将使用仿真方法 在不同的医疗补助政策方案下评估儿童健康结果，以使每个孩子与最佳 MMC计划。培训计划：完成我在经济学和数据分析方面的现有技能，并支持我 独立之路，我将获得：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措施； 2。利益相关者参与是（a）的关键 通过MMC计划和领导层确认计划覆盖的详细信息，（b）通知和传播研究 结果，以及（c）将来与其他州的医疗补助计划互动； 3。高级方法论技巧 政策模拟。含义：该项目将解决NHLBI的研究优先事项，以调查因素 通过预先评估有影响力的暴露方式来解释人群之间的健康差异。