STATISTICAL INFERENCE FOR COST EFFECTIVENESS ANALYSIS

成本效益分析的统计推断

• 批准号: 2032312
• 负责人: Joseph C Gardiner
• 金额: $ 19.82万
• 依托单位: MICHIGAN STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-07-01 至 2000-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2032312
• 关键词: acute disease /disorder; behavioral /social science research tag; case history; clinical research; comorbidity; computer simulation; functional ability; gender difference; health care cost /financing; health care policy; health care service evaluation; health services research tag; hospital utilization; human data; human morbidity; human therapy evaluation; longevity; longitudinal human study; low birth weight infant human; mathematical model; model design /development; myocardial infarction; outcomes research; quality of life; racial /ethnic difference; statistics /biometry

The scope of the proposed study is to develop and test new statistical procedures for cost-effectiveness analyses (CEA). Guided by an expanding literature on methods appropriate for CEA, introduction of guidelines for conducting and reporting economic analysis, and experience in CEA analyses, this research plan addresses the development of models that reflect accurately the experience of patients in sustained and changing states of health. The analyses will be based on continuous-time Markov models (both inhomogeneous and semi-Markov) that describe the evolution of patient histories following an intervention or treatment strategy. Measures widely used in cost-effectiveness analyses such as average cost- effectiveness ratio, or C/E ratio, and marginal or incremental cost- effectiveness ration (CER), are defined as parameters in a Markov model. Effectiveness measures include life expectancy, median survival time, and survival rates, discounted where appropriate at a constant rate. Costs are viewed as the value of resources utilized, and consists of two components, 1) cost due to sojourn in health states, and 2) costs due to transition from one health state to another. Covariates that may influence cost and effectiveness measures are incorporated through semi-parametric regression models into the transition intensities of the Markov models. New statistical methods for estimation of cost-effectiveness ratios, C/E and CER, are developed in this proposal. They exploit fully data arising from the longitudinal assessment of patients through different health states following an intervention, and permit quantitation of the variability in estimated CER's, and their dependence on covariate information on patients. The methodology allows for construction of confidence intervals for CER's and statistical tests of hypothesis for given critical values of CER's that governing bodies or affected communities may establish. The performance of the proposed methods will be evaluated with simulated and actual patient history data. The methodology will be applied in two externally funded, peer-reviewed investigations. 1)The Michigan Inter-Institutional Collaborative Heart Study on cost, outcomes, and treatment in acute myocardial infarction of 1,200 patients from three institutions, will investigate factors influencing type of treatment offered to patients, variations based on race and gender, and cost-effectiveness of treatments and procedures. 2) The Strategies for the Care of the Very Low Birthweight Infant Study will investigate competing treatment strategies for care of low birthweight infants with respect to comorbidity, patient benefits and costs, using outcome data from over 3,000 births from the US, Canada, and the Netherlands. The ultimate goal of the study is to assess the cost-effectiveness and cost- utility of different patterns of newborn care utilization. The methods proposed in this investigation have immediate application to these studies, and offer an array of promising techniques for use in cost-effectiveness analysis.

拟议研究的范围是开发和测试新的 成本效益分析（CEA）的统计程序。 引导 通过扩大有关 CEA 方法的文献， 引入开展和报告经济活动的指导方针 分析，以及 CEA 分析经验，本研究计划 致力于开发准确反映 患者在持续和变化的健康状态下的经历。 分析将基于连续时间马尔可夫模型（两者 非均匀和半马尔可夫）描述了患者的进化 干预或治疗策略后的病史。 措施 广泛应用于成本效益分析，例如平均成本 有效性比率，或 C/E 比率，以及边际或增量成本- 有效性比（CER），被定义为马尔可夫中的参数 模型。 有效性衡量标准包括预期寿命、中位数 生存时间和生存率，在适当的情况下折扣 恒定速率。 成本被视为所利用资源的价值， 由两部分组成，1）因健康原因逗留的费用 状态，以及 2) 从一种健康状态转变为 其他。 可能影响成本和有效性的协变量 通过半参数回归模型合并测量 转化为马尔可夫模型的转变强度。 用于估计成本效益比的新统计方法， C/E 和 CER 是在本提案中制定的。 他们充分利用数据 来自对患者的纵向评估 干预后不同的健康状态，并允许 估计 CER 的变异性的定量及其 依赖于患者的协变量信息。 方法论 允许构建 CER 的置信区间，并且 对给定 CER 临界值的假设进行统计检验 理事机构或受影响的社区可能会建立。 所提出方法的性能将通过以下方式进行评估 模拟和实际患者病史数据。 该方法将是 应用于两项外部资助的同行评审调查。 1) 密歇根机构间协作心脏成本研究， 1,200 例急性心肌梗塞的结果和治疗 来自三个机构的患者，将调查因素 影响向患者提供的治疗类型，基于变化 种族和性别以及治疗的成本效益 程序。 2) 照顾极低收入者的策略 出生体重婴儿研究将调查竞争治疗 低出生体重婴儿的护理策略 合并症、患者利益和成本，使用来自超过 来自美国、加拿大和荷兰的 3,000 名新生儿出生。 终极 该研究的目的是评估成本效益和成本- 新生儿护理利用的不同模式的效用。 本次调查中提出的方法可立即应用 这些研究，并提供了一系列有前途的技术 在成本效益分析中。