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.

拟议的研究范围是开发和测试新的 成本效益分析（CEA）的统计程序。 指导 通过扩展适用于CEA的方法的文献， 引入进行和报告经济指南 分析和CEA分析的经验，该研究计划 解决了准确反映模型的开发 患者在持续和不断变化的健康状态下的经验。 分析将基于连续的马尔可夫模型（均为 描述患者的演变的不均匀和半马尔可夫 干预或治疗策略后的历史。 措施 广泛用于成本效益分析，例如平均成本 - 有效性比，或C/E比以及边际或增量成本 有效性评分（CER）定义为马尔可夫中的参数 模型。 有效措施包括预期寿命，中位数 生存时间和生存率，在适当的情况下在 恒定速率。 成本被视为利用资源的价值， 并由两个组成部分组成，1）由于健康的逗留而导致的成本 国家和2）由于从一个健康状态过渡到 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进行了措施 进入马尔可夫模型的过渡强度。 估计成本效益比的新统计方法， C/E和CER是在此提案中开发的。 他们利用完全数据 通过对患者的纵向评估而产生的 干预后不同的健康状态，并允许 估计CER中的可变性及其定量 对患者的协变信息的依赖。 方法 允许建造CER的置信区间 给定CER的临界值的假设的统计检验 理事机构或受影响的社区可能会建立。 提出的方法的性能将通过 模拟和实际的患者病史数据。 该方法将是 应用于两项由外部资助，同行评审的调查中。 1）密歇根州的机构间合作研究成本研究， 结果和急性心肌梗塞的治疗1200 来自三个机构的患者将调查因素 影响患者提供的治疗类型，基于变异 关于种族和性别，治疗的成本效益 程序。 2）护理非常低的策略 出生体重婴儿研究将调查竞争治疗 照顾低出生体重婴儿的策略 合并症，患者福利和成本，使用来自Over的结果数据 来自美国，加拿大和荷兰的3,000个出生。 最终 该研究的目标是评估成本效益和成本 - 新生儿护理利用的不同模式的实用性。 本调查中提出的方法有立即应用 对这些研究，并提供一系列有希望的技术 在成本效益分析中。