Improving Methods for Assessing Medical Care Spending and Financial Risk

医疗自付支出(MOPS)，即患者在医疗保健上的直接支出，可能会超过 家庭资源，损害家庭的经济福祉，并产生进一步的压力和不健康。一个 长期以来，文献一直关注拖把的财政负担--一种流行的衡量拖把相对于 可支配收入门槛。然而，最近的理论研究已经引起了人们对金融风险的关注--一种截然不同的 捕捉相对于个人健康变化的不确定的拖把时间和幅度的概念 家庭资源的地位和波动。然而，金融风险的经验衡量仍然难以捉摸。 而且，据我们所知，该计划尚未成功实施。此外，金融风险与 家庭财务焦虑和预防性行为--这正是保险单的目标。而当 《平价医疗法案》(ACA)减轻了财政负担，但该法案对经济福祉的影响仍然较小 很好理解，特别是市场报道的影响。因为拖把的时机和规模 在市场覆盖范围内，取决于不同补贴的保费和成本分摊计划 当地保险市场，衡量金融风险，而不是负担，可能会独一无二地瓦解细微差别 市场计划对财务健康的影响。利用新颖的数据结构和联系，我们将： (1)制定有理论基础的金融风险前瞻性衡量标准，如12个月的发病率 灾难性和贫困的拖把，并将其与传统的负担措施进行比较。我们会 构建个人/家庭特征和医疗保健事件的分层月度数据集 医疗支出小组调查(2000-2016)，与国民健康访谈的基线数据相联系 调查(1998-2014年)和补充贫困措施的历史门槛。使用活动时间 方法，我们将分析我们的财政风险和传统负担措施的趋势(2000-2016) 成人人口总数，并按关键亚群分列。这些分析将(A)告知如何最好地衡量财务状况 福利，特别是用于区分替代保险单设计的保护潜力；(B)对比 传统措施与拟议措施中的价值判断；以及(C)提供具体的方法来监测 使用公共使用数据的金融风险，在这个高度不确定的改革后时代尤其及时。 (2)评估ACA市场覆盖和医疗补助扩大对金融的准实验效应 风险。我们将每月数据集(2010-2016)与县级未参保率(2009-2013)联系起来，并 健康计划数据来自HIX比较项目(2014-2016)。这些联系将使我们能够识别ACA 使用严格的差异差异设计，并捕获更细粒度的策略- 地方(县)保险市场可获得的费用分担降低和保费补贴的相关效果。

Medical out-of-pocket spending (MOOPS), i.e. direct patient spending on medical care, can overwhelm household resources, compromise families’ financial wellbeing, and engender further stress and ill health. A long-standing literature has focused on MOOPS financial burden- a prevalent measure of MOOPS relative to a disposable income threshold. Recent theoretical work, however, has drawn attention to financial risk- a distinct concept that captures the uncertain timing and magnitude of MOOPS relative to changes in individuals’ health status and fluctuations in family resources. Empirical measurement of financial risk, however, remains elusive and, to our knowledge, is yet to be successfully implemented. Further, financial risk is intimately tied to household financial anxiety and precautionary behaviors- the very objects of insurance policy. While the Affordable Care Act (ACA) has reduced financial burden, the law’s effects on financial wellbeing remain less well understood, especially effects of Marketplace coverage. Because the timing and magnitude of MOOPS under Marketplace coverage depend on the premium and cost-sharing schemes variably subsidized across local insurance markets, measurement of financial risk, rather than burden, could uniquely unravel nuanced effects of Marketplace plans on financial wellbeing. Leveraging novel data construction and linkages, we will: (1) Develop theoretically-grounded prospective measures of financial risk as the 12-month incidence of catastrophic and impoverishing MOOPS, and compare them with traditional burden measures. We will construct a hierarchical monthly dataset of individual/family characteristics and healthcare events from the Medical Expenditure Panel Survey (2000-2016), linked to baseline data from the National Health Interview Survey (1998-2014) and historical thresholds of the Supplemental Poverty Measure. Using time-to-event methods, we will analyze trends (2000-2016) of both our financial risk and traditional burden measures in the adult population overall, and by key subgroups. These analyses will (a) inform how best to measure financial wellbeing, especially for differentiating protective potential of alternative insurance policy designs; (b) contrast value judgments in traditional vs. proposed measures; and (c) provide concrete methodology for monitoring of financial risk using public-use data, which is especially timely in this highly uncertain, post-reform era. (2) Estimate quasi-experimental effects of ACA Marketplace coverage and Medicaid expansions on financial risk. We will link our monthly dataset (2010-2016) to county-level uninsurance rates (2009-2013), and to health-plan data from the HIX Compare Project (2014-2016). These linkages will enable us to identify ACA effects using a rigorous difference-in-difference-in-differences design, and to capture more granular, policy- relevant effects of cost-sharing reduction and premium subsidies available in local (county) insurance markets.