Community versus Facility-based Long-Term Care: Impact on Medicare Spending & Ser

描述(由申请人提供)：残疾的联邦医疗保险受益人是联邦医疗保险计划费用最高的群体之一。除了大量的医疗保健需求外，残疾老年人通常还需要长期护理(LTC)。LTC提供日常活动(如洗澡、吃饭)方面的帮助，这些活动可以在养老院之类的设施中提供(“设施LTC”)，也可以在像自己家这样的社区环境中提供(“社区LTC”)。尽管Medicare不为LTC付费，但设施LTC提供者已经增加了接触医疗保健提供者的机会，并可能有财政激励来增加其居民的Medicare服务使用，特别是急诊和急诊后护理。然而，目前尚不清楚这些激励措施是否会导致更高的医疗保险支出。拟议的研究将确定与社区长期TC相比，设施长期TC的使用是否增加了残疾老年人的医疗保险支出和医疗保健使用。我将扩展先前的研究，解决由于设施LTC使用者的高并存率和其他未观察到的因素而经常出现的混淆。我将首先寻求确定长期护理设施对急性护理、医生服务和急性后护理的医疗保险支出的独立影响。然后，我将寻求确定LTC设施对医院的影响 相关卫生服务利用，包括急诊科就诊、医院观察日和再次住院。方法：首先，Logistic回归将在2000年至2009年的医疗保险现行受益人调查中确定临床相似的社区居民群体。LTC设施的事故使用者将组成治疗组，临床相似的社区居民将组成控制组。其次，工具变量将对这些组进行伪随机化，以便于LTC进一步调整组之间的任何共同发病率和敏感度的差异。成年子女的数量、当地LTC设施的供应以及国家在家庭送餐上的支出将起到作用。第三，将构建七个第二阶段模型，其中大多数使用生存调整方法。在死亡率较高的人群中，生存调整模型是最有意义的成本衡量标准。每个因变量都会有一个模型：急性护理医疗保险支出、医生/从业者服务医疗保险支出、急性护理后医疗保险支出、急诊就诊次数、医院观察天数以及30天和60天再次住院的可能性。贡献和意义：拟议的研究试图确定政策可修改因素LTC设置对高成本医疗保险受益人的医疗支出的影响。这将为政策制定者提供证据，以纳入支付政策以及针对高成本受益人的医疗干预。同时，本研究将把新的计量经济学方法(包括生存调整方法)应用到LTC研究中。这将为其他对残疾人医疗费用感兴趣的研究人员提供一个例子，说明如何将这些令人兴奋的新方法应用于重要的政策问题。

DESCRIPTION (provided by applicant): Disabled Medicare beneficiaries are among the costliest to the Medicare program. In addition to their substantial healthcare needs, disabled older adults often require long-term care (LTC). LTC provides help with daily activities (e.g., bathing, eating) that can be delivered in a facility like a nursing home ("facility LTC") or in a community-setting like one's own home ("community LTC"). Though Medicare does not pay for LTC, facility LTC providers have increased access to healthcare providers and may have financial incentives to increase their residents' Medicare service use, particularly acute and post-acute care. However, it is unknown whether these incentives result in higher Medicare expenditures. The proposed research will determine whether facility LTC use increases Medicare expenditures and healthcare use for disabled older adults relative to community LTC. I will extend prior research by addressing the confounding often present due to high rates of comorbidities and other unobserved factors among facility LTC users. I will first seek to identify the independent effect of facility LTC on Medicare expenditures for acute care, physician services, and post-acute care. I will then seek to determine the effect of facility LTC on hospital related health services utilization, including emergency department (ED) visits, hospital observation days, and hospital readmissions. Methods: First, logistic regression will identify a clinically-similar group of community residents among the older adults in the Medicare Current Beneficiary Survey from 2000-2009. Incident users of facility LTC will comprise the treatment group and clinically similar community residents will comprise the control group. Second, instrumental variables will pseudo-randomize these groups to facility LTC to further adjust for any differences in co-morbidity and acuity between the groups. Number of adult children, local supply of LTC facilities, and state spending on home-delivered meals will act as instruments. Third, seven second stage models will be constructed, most using survival-adjusted methods. Survival-adjusted models are the most meaningful measure of cost in a population with high rates of death. There will be a model for each dependent variable: acute care Medicare expenditures, physician/practitioner services Medicare expenditures, post-acute care Medicare expenditures, number of ED visits, number of hospital observation days, and likelihood of 30- day and 60-day hospital readmission. Contribution and Significance: The proposed research seeks to determine the effect of a policy-modifiable factor, LTC setting, on the healthcare expenditures for high-cost Medicare beneficiaries. This will offer policymakers evidence to incorporate into payment policies as well as healthcare interventions targeted at high-cost beneficiaries. Meanwhile, the proposed research will apply novel econometric methods (including survival-adjusted methodologies) to LTC research. This will offer other researchers interested in the healthcare costs of the disabled an example of how to apply these exciting new methods to important policy questions.