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Racial/Ethnic Disparities in Health Care and Challenges in Insurance Plan Choices among Older People with Alzheimer’s Disease and Related Dementia: A Mixed Methods Study of Medicare Options

Racial/Ethnic Disparities in Health Care and Challenges in Insurance Plan Choices among Older People with Alzheimer’s Disease and Related Dementia: A Mixed Methods Study of Medicare Options
患有阿尔茨海默病和相关痴呆症的老年人在医疗保健方面的种族/民族差异以及保险计划选择的挑战:医疗保险选项的混合方法研究
批准号:
10723148
负责人:
Elham Mahmoudi
金额:
$72.68万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-08-01 至 2028-04-30

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英文摘要
Project Summary/Abstract Medicare is the primary health insurance for older adults (65+) living in the U.S. Eligible beneficiaries must choose between two different plan types: traditional Medicare (TM) and Medicare Advantage (MA). MA enrollment has doubled in the last decade, currently covering about 45% of all Medicare beneficiaries. This growth has been driven, in part, by an increasing proportion of Black and Hispanic MA enrollees. While evidence suggests that some MA patient populations receive better-quality care and experience fewer racial/ethnic health disparities, it is unknown whether this is true for socioeconomically disadvantaged Black and Hispanic Medicare beneficiaries, who are at substantially greater risk of incident Alzheimer’s disease and related dementia (ADRD). Because they have more complex healthcare needs but receive less coordinated care and fewer preventive services, they are at significantly higher risk of potentially preventable hospitalization, 30-day hospital readmission, and other adverse health events than their White counterparts. Further, there is considerable variation in the quality of MA plans. Many MA plans in Black- and Hispanic- populated counties have low quality ratings, which may contribute to racial/ethnic health disparities. Moreover, beneficiaries’ health plan decision-making is complex, potentially exacerbating racial/ethnic health disparities among ADRD beneficiaries. Finally, racial/ethnic health care disparity research has been mainly observational and descriptive, thus limiting its usefulness in informing policy. The specific aims of this mixed methods study are to use innovative econometric causal methods to (1) examine and explain racial/ethnic disparities in 16 measures of care continuity, receipt of preventive services, and quality of care in MA vs. TM; (2) examine racial/ethnic disparities within and between MA plans in 16 measures of care continuity, receipt of preventive services, and quality of care; and (3) explore health plan decision-making challenges among beneficiaries with ADRD and/or their caregivers. Our multidisciplinary team, with decades of experience in ADRD research, racial/ethnic healthcare disparity analysis, claims data and econometrics, qualitative and mixed methods, and health policy is uniquely qualified to conduct this innovative research. This study will inform Medicare policies to promote more equitable health care and facilitate easier health plan decision-making for socioeconomically disadvantaged Black and Hispanic Medicare beneficiaries with ADRD. With our national Policy Advisory Committee of stakeholders, including a beneficiary with ADRD and/or a caregiver, we are well-positioned to disseminate findings and promote quality and equitable health care for racial/ethnic minority Medicare beneficiaries with ADRD.
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Using Machine Learning to Improve Readmission Prediction in Alzheimer's Disease and Related Dementia
Using Machine Learning to Improve Readmission Prediction in Alzheimer's Disease and Related Dementia
Using Machine Learning to Improve Readmission Prediction in Alzheimer's Disease and Related Dementia
Using Machine Learning to Improve Readmission Prediction in Alzheimer's Disease and Related Dementia
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