Estimating the Potential Medicare Savings from Comparative Effectiveness Research

通过比较有效性研究估计潜在的医疗保险节省

• 批准号: 8042729
• 负责人: ALAN Michael GARBER
• 金额: $ 5.2万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-04-01 至 2011-07-16
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8042729
• 关键词: Adoption; Advisory Committees; Affect; American; Area; Attention; Caring; Clinical; Cost Effectiveness Analysis; Cost Savings; Data; Data Analyses; Diagnostic; Disease; Economics; Effectiveness; Elderly; Expenditure; Frequencies; Future; Growth; Health; Health Expenditures; Health Insurance; Healthcare; Individual; Intervention; Investigation; Link; Malignant Neoplasms; Malignant neoplasm of prostate; Measures; Medical; Medicare; Medicare claim; Modeling; Outcome; Patients; Performance; Placebos; Policies; Policy Analysis; Population; Price; Process; Research; Savings; Subgroup; Techniques; Uncertainty; base; beneficiary; clinical efficacy; clinical practice; clinically relevant; cohort; comparative effectiveness; copayment; cost; cost effective; cost effectiveness; effectiveness research; improved; life time cost; payment; programs; research study

DESCRIPTION (provided by applicant): Comparative effectiveness research (CER) is intended to measure how alternative approaches to health care affect health outcomes. CER has the potential to reduce expenditures by limiting the use of both ineffective care and care that is no more effective than less costly alternatives. We propose to study the benefits that might accrue to Medicare from the application of CER to six high- priority medical areas. Our specific aims are to: 1. Identify areas of CER that have the greatest potential to improve the efficiency and appropriateness of care delivered to Medicare beneficiaries. 2. Estimate (long-term) incremental expenditures attributable to the use of competing strategies in these high-priority clinical areas. 3. Determine the expenditure implications for Medicare that would result from the adoption of clinical strategies supported by CER criteria, including cost-effectiveness, for each high-priority area, and to describe policy options (e.g. reference pricing, bundled payments, etc.) for implementing these findings for Medicare. Our analyses are principally based on complete Medicare claims files for Parts A and B from years 1991 to 2009 and Part D from 2006 to 2009. Data for the analysis of cancer management (e.g., localized prostate cancer), will include SEER-Medicare linked data. We will first select the medical areas for further research based upon a prioritization process considering, for each potential area of investigation, effects on total Medicare expenditures, potential for growth, and evidence of variability or uncertainty in clinical approaches. A distinguished expert Advisory Committee, representing health care, health insurance, and consumer perspectives, will provide close guidance for this component and several other aspects of the project. For each high-priority medical area selected, we will identify the relevant cohort from the Medicare claims files (or SEER-Medicare files) and assign individuals to management strategies based upon treatment or diagnostic interventions received. In addition to descriptive statistical analyses (frequency of the use of each strategy, rates of important outcomes, and total and related health expenditures), the project will include multivariate statistical analysis to investigate the relationship between strategy, outcome (including expenditures) and key variables. Where possible, we will use instrumental variable analysis and related techniques to control for bias in the selection of management strategies. Separate models will be estimated for important subgroups. We will estimate the potential consequences to Medicare of implementing our findings for each medical area by constructing a population model that shifts (with scenarios of varying degrees of adoption) patients to the strategy(ies) supported by our findings (least costly with equivalent outcomes or additional cost worth the incremental benefit based on cost-effectiveness analysis). Finally, we will investigate approaches that Medicare might use to implement these findings, including payment reform options such as bundled payments, reference pricing and value-based copayments. PUBLIC HEALTH RELEVANCE: This project identifies clinical strategies supported by comparative-effectiveness research that have the potential, through greater use, to decrease costs to Medicare without adversely affecting health outcomes. It estimates the long-term impact on expenditures of shifting current clinical practices to these strategies and evaluates options for implementing these findings.

描述（由申请人提供）：比较有效性研究（CER）旨在衡量医疗保健的替代方法如何影响健康结果。 CER有可能通过限制使用无效的护理和护理的使用来减少支出，这比昂贵的替代方案更有效。 我们建议研究从CER到六个高优先医疗领域的应用可能带来的Medicare的好处。我们的具体目的是：1。确定CER的领域，这些区域具有提高向医疗保险受益人提供的护理效率和适当性的最大潜力。 2。估计（长期）增量支出归因于这些高优先级临床领域中使用竞争策略的估计。 3.确定对Medicare的支出影响，这将是由于采用CER标准支持的临床策略，包括成本效益，每个高优先级领域，并描述政策选择（例如，参考定价，捆绑付款等）来实施这些发现的医疗保险。 我们的分析主要基于从1991年到2009年的A和B部分的完整Medicare索赔文件，以及2006年至2009年的D部分。癌症管理分析的数据（例如局部前列腺癌）将包括Seer-Medicare链接数据。我们将首先根据优先考虑过程选择医疗领域进行进一步研究，以考虑每个潜在的调查领域，对医疗保险总支出的影响，增长潜力以及临床方法中可变性或不确定性的证据。代表医疗保健，健康保险和消费者观点的杰出专家咨询委员会将为该项目的其他几个方面提供密切指导。对于所选的每个高优先级医疗领域，我们将从Medicare索赔文件（或SEER-MEDICARE文件）中确定相关的队列，并根据接受的治疗或诊断干预措施将个人分配给管理策略。除了描述性统计分析（每种策略的使用频率，重要结果的频率以及总和相关的健康支出）外，该项目还将包括多元统计分析，以调查策略，结果（包括支出）和关键变量之间的关系。在可能的情况下，我们将使用仪器变量分析和相关技术来控制管理策略的偏见。对于重要的亚组，将估算单独的模型。我们将估计Medicare对每个医疗领域实施发现的潜在后果，通过构建一个人口模型（带有不同程度的收养）患者转移到我们的发现支持的策略（IES）（IES）（IES）（IES）（IES）（IES）所支持的结果（昂贵的结果，或基于成本效益分析的额外成本值得额外的成本值得逐步的成本）。最后，我们将调查Medicare可能用来实施这些发现的方法，包括付款改革选项，例如捆绑付款，参考定价和基于价值的共付额。 公共卫生相关性：该项目确定了比较效率研究支持的临床策略，这些研究有可能通过更大的利用来降低医疗保险的成本而不会对健康结果产生不利影响。它估计了将当前临床实践转移到这些策略的长期影响，并评估实施这些发现的选择。