Can Medicaid Managed Care mitigate race/ethnic health disparities in diabetes?

医疗补助管理式医疗能否减轻糖尿病中的种​​族/民族健康差异？

• 批准号: 10528738
• 负责人: Mohammed Kumail Ali
• 金额: $ 52.59万
• 依托单位: GEORGETOWN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-23 至 2027-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10528738
• 关键词: Accident and Emergency department; Acute; Address; Admission activity; Adult; Affect; Age; American; Americas; Amputation; Behavior; Black race; COVID-19; COVID-19 pandemic; COVID-19 pandemic effects; Caring; Characteristics; Chronic Disease; Communities; Contracts; Data; Data Analyses; Data Set; Databases; Diabetes Mellitus; Diagnosis; District of Columbia; Economic Burden; Eligibility Determination; Emergency department visit; Enrollment; Ethnic Origin; Expenditure; Florida; Future; Goals; Health Care Costs; Heterogeneity; Hospitalization; Hyperglycemia; Incentives; Indigenous; Information Systems; Insurance Carriers; Interview; Investigation; Kentucky; Latinx; Lawyers; Link; Managed Care; Managed Care Programs; Medicaid; Medicare/Medicaid; Methods; Minority; National Institute on Minority Health and Health Disparities; Non-Insulin-Dependent Diabetes Mellitus; Obesity; Occupations; Outcome; Patients; Penetration; Performance; Persons; Pharmaceutical Preparations; Policies; Population; Poverty; Preventive care; Primary Health Care; Privatization; Process; Quality of Care; Race; Research; Risk; Sampling; Selection Bias; Services; Shock; Testing; Time; Titrations; Variant; Vulnerable Populations; Work; base; beneficiary; black patient; burden of illness; care outcomes; cohort; comorbidity; coronavirus disease; cost; data modeling; design; disenfranchised population; disparity reduction; ethnic disparity; ethnic health disparity; ethnic minority; evidence base; experience; family burden; foot; health disparity; high risk; improved; insight; medical specialties; member; pandemic disease; people of color; post-COVID-19; programs; response; service utilization; sex; socioeconomic disadvantage; trend

ABSTRACT This study represents a timely investigation that addresses race/ethnic disparities in type 2 diabetes (T2DM) care over a period that included a major pandemic shock. T2DM is burdensome and disproportionately impacts vulnerable and disenfranchised populations; of note, there are stark race/ethnic disparities in T2DM care goals, emergency department (ED) visits, and hospitalizations. Medicaid covers 25% of Americans with T2DM. More than 80% of Medicaid beneficiaries nationally receive at least some of their care from Medicaid managed care organizations (MMCO). States contract with private (non-profit or for-profit) MMCOs to lower costs, increase quality, and pass on financial risks of covering Medicaid beneficiaries. Heterogeneity across and within state programs can have implications for quality of T2DM care and, specifically, race/ethnic disparities through benefit generosity or by affecting MMCO entry and post-entry behavior. State policymakers also have significant influence over marketplaces in which MMCOs compete, which can have consequences for race/ethnic disparities, given that Medicaid disproportionately covers non-white populations. Little is known about whether and how MMCOs and the state programs they operate in influence disparities in T2DM care and, if or how the COVID-19 pandemic changed the trajectory of health disparities. We propose to answer these unknowns using a convergent mixed-methods study: we will compile a database of MMCO/state program features that could influence care using a health disparities conceptual framework (Aim 1); we will empirically explore race/ethnic disparities among adults with T2DM and whether these vary by MMCO/state features and pre-/post-COVID-19 using comprehensive data from the Transformed Medicaid Statistical Information System over 2016-2025 (Aims 2 and 3); and we will collect and analyze qualitative data from Medicaid stakeholders to triangulate and contextualize the quantitative findings (Aim 4). We focus on non- disabled, non-pregnant 18-64-year-old adults with T2DM who tend to remain stably covered by Medicaid over time. To reduce selection bias, we focus our analyses on 12 states and the District of Columbia that mandate enrollment in comprehensive MMCOs. We will use panel data models to examine race/ethnic and sex-specific receipt of key T2DM services and ED visits and hospitalizations, overall and by MMCO/state features. We will also follow a continuously enrolled cohort over 2020-2025 to assess if and how MMCO/state program features moderate the pandemic’s effects on T2DM disparities. Sensitivity analyses will explore the influence of churn. Further, our preliminary analyses identify Kentucky and Florida as having the lowest and highest disparities in T2DM care, respectively; we will conduct interviews in these states to examine what MMCO/state features and implementation might explain these disparities. This policy-relevant work will provide critical insights into how Medicaid managed care programs can be designed to reduce disparities in chronic disease burdens.

摘要 这项研究是一项及时的研究，旨在解决2型糖尿病（T2 DM）的种族/民族差异 在包括大流行冲击在内的一段时期内提供护理。T2 DM是一种负担， 弱势和被剥夺权利的人群;值得注意的是，T2 DM护理目标存在明显的种族/民族差异， 急诊科（艾德）就诊和住院。医疗补助覆盖了25%的美国T2 DM患者。更 超过80%的医疗补助受益人在全国范围内至少从医疗补助管理医疗中获得部分护理 （MMCO）。国家与私营（非营利或营利）微型和微型企业签订合同，以降低成本， 质量，并传递覆盖医疗补助受益人的财务风险。跨州和州内的异质性 计划可能会影响T2 DM护理质量，特别是种族/民族差异， 受益慷慨或通过影响MMCO进入和进入后的行为。国家政策制定者也有 对MMCO竞争的市场产生重大影响，这可能对 种族/民族差异，因为医疗补助不成比例地覆盖非白人人口。知之甚少 关于MMCO及其运作的州计划是否以及如何影响T2 DM护理的差异 以及COVID-19大流行是否或如何改变了健康差距的轨迹。我们建议回答 这些未知数使用收敛混合方法研究：我们将编译一个数据库的MMCO/状态 使用健康差异概念框架（目标1）可能影响护理的计划功能;我们将 经验性探索T2 DM成人患者中的种族/民族差异，以及这些差异是否因MMCO/州而异 功能和前/后COVID-19使用综合数据从转换医疗补助统计 2016-2025年信息系统（目标2和3）;我们将收集和分析来自 医疗补助利益相关者对定量结果进行三角测量和背景分析（目标4）。我们专注于非- 残疾、未怀孕的18-64岁T2 DM成人，他们倾向于保持医疗补助的稳定覆盖， 时间为了减少选择偏差，我们将分析重点放在12个州和哥伦比亚特区， 在综合MMCO中注册。我们将使用面板数据模型来检查种族/民族和性别特异性 接受关键T2 DM服务以及艾德访视和住院，总体和按MMCO/州特征。我们将 我还跟踪了2020-2025年连续登记的队列，以评估MMCO/州计划是否以及如何具有 缓和大流行对T2 DM差异的影响。敏感性分析将探讨流失的影响。 此外，我们的初步分析确定，肯塔基州和佛罗里达在以下方面的差异最低和最高： T2 DM护理;我们将在这些州进行访谈，以检查MMCO/州的特征， 执行情况可以解释这些差异。这项与政策有关的工作将提供关键的见解， 医疗补助管理式护理计划的设计可以减少慢性病负担的差异。