Returns to Medicare Spending: Evidence from Variation Across Physicians

医疗保险支出回报：来自医生差异的证据

• 批准号: 8370531
• 负责人: AMANDA ELLEN KOWALSKI
• 金额: $ 7.78万
• 依托单位: NATIONAL BUREAU OF ECONOMIC RESEARCH
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-08-01 至 2014-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8370531
• 关键词: Accounting; Caring; Data; Development; Elderly; Emergency Situation; Expenditure; Government; Health; Health Care Sector; Health Expenditures; Healthcare; Hospitals; Income; Knowledge; Light; Measures; Medical; Medicare; Medicare claim; Methodology; Myocardial Infarction; Nature; Newborn Infant; Outcome; Patients; Physicians; Policies; Process; Public Policy; Randomized; Recording of previous events; Research; Resources; Risk; Role; Rotation; Shock; Societies; Source; Staging; Teaching Hospitals; Time; Translating; Variant; Work; base; cost; design; improved; interest; novel strategies; patient population

DESCRIPTION (provided by applicant): Whether the benefits of medical spending exceed their costs is a key policy question, especially given the government's large and expanding role in the health care sector. This project aims to develop a new approach for measuring the marginal returns to medical spending, and to investigate its applicability to several different types of medical care. Medical care that results in a large share of expenditures, especially among the elderly, is of particular interest because of its importance for the design of public policies such as Medicare. The basis for the new approach to investigating marginal returns to medical care is a natural source of variation in treatment intensity: the wide variation in treatment intensity across physicians. In empirical contexts in which patients are quasi-randomly assigned to doctors - such as when the doctors to which patients are assigned are determined by which physician is on-call at the time of an emergent condition - we can better understand the nature of this variation across physicians, and employ it in an instrumental variables framework to examine the impact of intensive treatments on health care spending and health outcomes. The main objective of the proposed research is to identify specific types of medical care to which the proposed strategy can be applied. First, relevant empirical contexts must have a doctor or team of doctors that is clearly responsible for treatment decisions, and the (anonymized) identity of the doctors must be visible in claims data. Second, there must be variation in treatment intensity across doctors. Third, patient assignment to doctors must be as good as random. After identifying a set of candidate empirical contexts by identifying costly and prevalent contexts in the data and speaking with physicians, the key analytical step will be to use the Medicare claims data to narrow in on a set of empirical contexts where each of these criteria appear to hold in the data. This process will ideally result in several empirical contextsin which it will be possible to estimate the marginal returns to medical spending, ultimately leading to new estimates. PUBLIC HEALTH RELEVANCE: This project will broaden the toolkit available to measure the marginal returns to medical spending, laying the groundwork for the development of new evidence on the value of health spending. By identifying the treatments that produce the largest health gains, society can allocate resources to improve health more efficiently, ultimately resulting in more health per dollar of health expenditure.

描述（由申请人提供）：医疗支出的收益是否超过其成本是一个关键的政策问题，特别是考虑到政府在医疗保健部门的巨大和不断扩大的作用。本研究旨在发展一种新的方法来衡量医疗支出的边际回报，并探讨其适用于几种不同类型的医疗保健。特别是在老年人中，医疗保健在支出中占很大比例，这一点特别令人感兴趣，因为它对医疗保险等公共政策的设计至关重要。研究医疗边际回报的新方法的基础是治疗强度变化的自然来源：医生之间治疗强度的广泛差异。在患者被准随机分配给医生的经验背景下-例如，当患者被分配给医生时，医生是由紧急情况下哪个医生值班决定的-我们可以更好地理解医生之间这种差异的性质，并将其用于工具变量框架，以检查强化治疗对医疗保健支出和健康结果的影响。拟议研究的主要目标是确定拟议战略可以适用的具体医疗服务类型。首先，相关的经验背景必须有一个医生或医生团队，明确负责治疗决策，并且医生的（匿名）身份必须在索赔数据中可见。其次，不同医生的治疗强度必须有所不同。第三，病人对医生的分配必须是随机的。在通过识别数据中昂贵和普遍的背景并与医生交谈来识别一组候选经验背景之后，关键的分析步骤将是使用医疗保险索赔数据来缩小一组经验背景，其中每个标准似乎都在数据中。这一过程将理想地导致几个实证contextin它将有可能估计边际回报医疗支出，最终导致新的估计。 公共卫生关系：该项目将扩大现有的工具包，以衡量医疗支出的边际回报，为发展关于卫生支出价值的新证据奠定基础。通过确定产生最大健康收益的治疗方法，社会可以更有效地分配资源来改善健康，最终导致每美元卫生支出的健康水平提高。