Improving Methods for Assessing Medical Care Spending and Financial Risk
Improving Methods for Assessing Medical Care Spending and Financial Risk
批准号:
10553753
负责人:
Mustafa Hussein
金额:
$7.73万
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-01-22 至 2023-02-28
中文摘要
医疗自付支出(MOOPS),即患者在医疗护理上的直接支出,
家庭资源,损害家庭的财务状况,并造成进一步的压力和健康不良。一
长期以来的文献都集中在MOOPS的财政负担-一个普遍的衡量MOOPS相对于一个
可支配收入门槛。然而,最近的理论工作引起了人们对金融风险的关注--一种独特的
一个概念,捕捉MOOPS相对于个人健康变化的不确定时间和幅度
家庭资源的状况和波动。然而,对金融风险的实证衡量仍然难以捉摸
据我们所知,这一计划尚未成功实施。此外,金融风险与以下因素密切相关:
家庭财务焦虑和预防行为-保险政策的对象。而
《平价医疗法案》(ACA)减轻了经济负担,但法律对经济福祉的影响仍然较小
很好理解,尤其是市场覆盖的影响。因为MOOPS的时间和规模
根据市场覆盖范围取决于保费和成本分摊计划,
当地保险市场,金融风险的衡量,而不是负担,可以独特地解开微妙的
市场计划对财务健康的影响。利用新的数据构建和链接,我们将:
(1)制定有理论基础的金融风险前瞻性措施,
灾难性和破坏性的MOOPS,并与传统的负担措施进行比较。我们将
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年),与国民健康访谈的基线数据相关联
调查(1998-2014年)和补充贫困措施的历史阈值。使用事件发生时间
方法,我们将分析趋势(2000-2016年),我们的财政风险和传统的负担措施,
成人总体和关键亚组。这些分析将(a)告知如何最好地衡量财务
健康,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的价值判断;(c)提供具体方法,
这在这个高度不确定的后改革时代尤其及时。
(2)估计ACA市场覆盖率和医疗补助扩张对财务状况的准实验影响
风险我们将把我们的月度数据集(2010-2016年)与县级未保险率(2009-2013年)联系起来,
来自HIX比较项目(2014-2016)的健康计划数据。这些联系将使我们能够确定ACA
使用严格的差异中的差异中的差异设计的影响,并捕捉更细粒度,政策-
地方(县)保险市场上费用分摊减少和保费补贴的相关影响。
英文摘要
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.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
国内基金
海外基金
Computational Methods for Analyzing Toponome Data
-
批准号:60601030
-
项目类别:青年科学基金项目
-
资助金额:17.0万元
-
批准年份:2006
-
负责人:Axel Mosig
-
依托单位: