Impact of Medicare Polices on Beneficiaries with ADRD

医疗保险政策对 ADRD 受益人的影响

基本信息

批准号：
10728582
负责人：
JOHN HSU
金额：
$ 249.76万
依托单位：
MASSACHUSETTS GENERAL HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-09-01 至 2026-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10728582
关键词：
Accounting Address Admission activity Affect Alzheimer&apos s disease diagnosis Alzheimer&apos s disease patient Alzheimer&apos s disease related dementia Area Attention Budgets COVID-19 pandemic Caring Case Mixes Certification Clinical Code Cognitive Communities Complement Complex Data Diagnosis Diagnostic Disadvantaged Discipline of Nursing Disparity Disparity population Electronic Health Record Eligibility Determination Enrollment Equity Ethnic Origin Evaluation Event Family Fee-for-Service Plans Frequencies Future Grouping Growth Health Health and Retirement Study Heterogeneity Home Home Health Agency Home Health Care Agencies Hospitalization Impaired cognition Impairment Incentives Individual Link Location Machine Learning Maximum Likelihood Estimate Measurement Measures Medical Medicare Medicare claim Methodology Methods Modeling Movement Natural experiment Nature Nursing Homes Outcome Pathway interactions Patient Care Patient-Focused Outcomes Patients Pattern Performance Persons Police Policies Policy Maker Population Provider Race Rehabilitation therapy Resources Risk Risk Adjustment Risk Factors Services Shock Social isolation Surveys System Time United States Centers for Medicare and Medicaid Services Validation Variant Visit access disparities behavioral health beneficiary care delivery care episode care outcomes classification algorithm clinical care comorbidity data complexity data resource disease diagnosis experience feeding financial incentive food insecurity functional status improved mortality mortality risk nursing skill pandemic disease patient home care payment post stroke programs rehabilitation service response social capital social disparities social factors spatial temporal variation telehealth treatment effect

项目摘要

Abstract Medicare beneficiaries with Alzheimer’s Disease and Related Dementias (ADRD) experience progressive cognitive impairment and frequently require assistance to manage their complex care needs at home. Medicare pays Home Health Agencies (HHAs) billions of dollars annually to provide home care, including skilled nursing and rehabilitation therapies. Because of concerns about the quality and value of HHA services, Medicare has two new payment policies: a) switch to a case-mix payment system, the Patient Driven Groupings Model (PDGM) in 2020; and b) implementation of the Home Health Agency Value Based Payment (HHVBP) program in 2023. Neither program, however, addresses potential differences in outcomes due to social factors, such as individual-level race/ethnicity or area-level social capital, despite past experiences where new Medicare payment policies that ignored social factors exacerbated disparities. Evidence on the impact of the new policies on HHA service use is limited, especially as the national HHVBP implementation starts in 2023. Any evaluation will require accounting for contemporaneous changes in other policies, and attention to how the pandemic is impacting who receives HHA services or how care is delivered. Thus, to examine the impact of HHA services on beneficiary outcomes, we propose three aims: 1) to characterize changes in the population of community-dwelling beneficiaries eligible for HHA services and enrolled in traditional, fee-for-service Medicare (TM), accounting for switches to Medicare Advantage (MA), transitions to long-term nursing homes, and increases in new ADRD diagnoses after the introduction of greater financial incentives for ADRD coding; 2) to evaluate the impact of PDGM and HHVBP policies on HHA use in TM beneficiaries with ADRD compared with similar beneficiaries enrolled in MA; and, 3) to examine the effect of HHA service use on clinical events, such as hospitalizations, long-term nursing home admission, or mortality, among TM and MA beneficiaries with ADRD. Our three aims are complementary and address a critical service for vulnerable beneficiaries with ADRD while carefully examining population and delivery changes occurring over time. We will use multiple data resources to capture the changes; then to address the complexity of the data, we will use ensemble machine learning approaches combined with longitudinal targeted maximum likelihood estimation methods to assess the average HHA treatment effect as well as potential effect heterogeneity with respect to social factors measured at the individual and area levels. Study findings could inform policy makers, clinicians, patients, and families about the impact of HHA services over time and potential variation in this impact with respect to social factors.

抽象的患有阿尔茨海默氏病和相关痴呆症（ADRD）的医疗保险受益人经验认知障碍，经常需要帮助以应对他们在家中复杂的护理需求。 Medicare每年支付家庭健康机构（HHAS）数十亿美元，以提供家庭护理熟练的护士和康复疗法。由于担心HHA服务的质量和价值， Medicare有两个新的付款政策：a）切换到病例混合支付系统，患者驱动 2020年的分组模型（PDGM）； b）实施基于家庭健康机构价值付款（HHVBP）计划在2023年。但是，这两个程序都无法解决因结果的潜在差异社会因素，例如个人级别的种族/种族或地区级社会资本，目的地过去的经验忽略社会因素加剧分布的新的Medicare支付政策。关于新政策对HHA服务使用的影响有限，尤其是国家HHVBP实施从2023年开始。任何评估都需要考虑其他政策的当代变更，以及注意大流行如何影响谁获得HHA服务或如何提供护理。那是检查HHA服务对受益人结果的影响，我们提出三个目标：1）表征符合HHA服务并参加的社区居民受益人人口的变化传统的，费用的服务医疗保险（TM），会计转换为Medicare Advantage（MA），过渡到长期护理房屋，并在引入更大财务后的新ADRD诊断物增加 ADRD编码的激励措施； 2）评估PDGM和HHVBP策略对TM中HHA使用的影响与参加MA的类似受益人相比，ADRD受益人； 3）检查 HHA服务用于临床活动，例如住院，长期疗养院入院或死亡率，在ADRD的TM和MA受益人中。我们的三个目标是完整的，并解决了关键服务对于具有ADRD的脆弱受益人，同时仔细检查人口和交付变化随着时间的推移。我们将使用多个数据资源来捕获更改；然后解决复杂性数据，我们将使用合奏机器学习方法与纵向目标最大评估平均HHA治疗效果以及潜在效果的可能性估计方法关于在个人和地区水平上测得的社会因素的异质性。研究结果可以随着时间的推移，政策制定者，临床医生，患者和家庭都会对HHA服务的影响以及这种影响在社会因素方面的潜在变化。