STATISTICAL INFERENCE FOR COST-EFFECTIVENESS ANALYSIS

成本效益分析的统计推断

• 批准号: 6199084
• 负责人: Joseph C Gardiner
• 金额: $ 26.21万
• 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 2003-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6199084
• 关键词: attention deficit disorder; behavioral /social science research tag; clinical research; comorbidity; computer simulation; cost effectiveness; data collection methodology /evaluation; health care cost /financing; health care policy; health care quality; health care service evaluation; health services research tag; hospital utilization; human data; human morbidity; human therapy evaluation; implantable defibrillators; longitudinal human study; mathematical model; model design /development; mother /infant health care; myocardial infarction; neoplasm /cancer diagnosis; outcomes research; statistics /biometry

Motivated by the need for new techniques for analyses of health care costs from clinical and epidemiological studies, the goal of this study is to develop statistical techniques that fill methodological gaps in current CEA models. When a health care intervention is deployed, cost are engendered though the use of resources. These occur in random amounts at random times that might differ by patient attributes, clinical and intervention characteristics. Study design and sampling may lead to incomplete observation of key outcomes in some patients. Incorporating these components into statistical models that accurately reflect the experience of patients as their health histories manifest over time permits consideration of health outcomes and costs jointly. This study proposes statistical models of costs and patient outcomes that incorporate the temporal dynamics that generate these data and the availability of concomitant exogenous information. They propose to use a Markovian regime to model the dynamics of movement of patients through different health states, with costs incurred at transitions between states and sojourns within states. Applying a constant discount rate where appropriate, they will estimate summary health outcome measures (e.g. life expectancy, quality-adjusted life years, net present value, net health cost and benefit, cost-effectiveness ratios). They will assess the impact of exogenous factors on these parameters and provide a unified framework for statistical inference and then test the performance and sensitivity of the procedures with real and simulated data. They propose applications of the methods to several peer-reviewed investigations. 1) They will assess the determinants of total health care costs and the use and cost of pharmacologic treatments in a longitudinal study of quality and continuity of care to 9,000 Medicaid recipients with a diagnosis of attention deficit hyperactivity disorder. 2) They will estimate cost of hospitalization in relation to co-morbidity, patient demographic, and clinical attributes in a retrospective study of cardiac procedures performed in two cohorts of patients with myocardial infarction. 3) From the MADIT they will assess resource utilization and and survival in patients at high risk for ventricular arrhythmia, and re-examine the cost-effectiveness of the defibrillator compared to conventional therapy. 4) They will assess (relative to usual care) incremental costs, net health benefit and net cost measures in a trial of an intervention designed to improve mental health and physical health functioning and life course development in low-income pregnant women. 5) They will assess the determinants of cost by providing treatment in a study of stage of diagnosis, treatment, and survival in patients with cancer in Medicaid In summary, by developing and testing new methods for cost-effectiveness studies, and demonstrating their application in several ongoing clinical studies, this study not only offers an array of promising techniques, but also bridges the gap between methodological development and implementation.

由于需要新技术来分析健康的动机 临床和流行病学研究的护理费用，这项研究的目标 是开发统计技术，以填补当前的方法论空白 CEA模型。 当部署医疗保健干预时，会产生成本 虽然使用资源。 这些在随机时间随机发生 这可能因患者属性，临床和干预而有所不同 特征。 研究设计和采样可能导致观察不完整 某些患者的关键结果。 将这些组件纳入 统计模型准确地反映了患者的经验 随着时间的流逝，健康历史允许考虑健康结果 并共同成本。 这项研究提出了成本的统计模型和 结合了产生这些的时间动力的患者结果 数据和伴随外源信息的可用性。 他们建议 使用马尔可夫政权对患者运动的动力进行建模 通过不同的健康状况，在过渡之间产生的成本 各州内的国家和搬家。 应用恒定的折现率 他们将估计简易健康结果指标（例如生命 预期，质量调整后的寿命，净现值，净健康成本 和好处，成本效益比）。 他们将评估 这些参数上的外源性因素，并为 统计推断，然后测试 具有真实和模拟数据的过程。 他们提出了这些方法的应用程序对几个同行评审 调查。 1）他们将评估全卫生保健的决定因素 在纵向研究中，成本以及药理治疗的使用和成本 9,000名医疗补助接收者的护理质量和连续性 注意力缺陷多动障碍的诊断。 2）他们将估计 与同人物，患者人群和相关的住院费用 在进行心脏手术的回顾性研究中的临床属性 在两名患有心肌梗塞的患者中。 3）他们来自 将评估具有高风险的患者的资源利用和生存 心室心律不齐，并重新检查 与常规疗法相比，除颤器。 4）他们将评估（相对 在通常的护理中）逐步成本，净健康福利和净成本度量 旨在改善心理健康和身体的干预措施的试验 低收入孕妇的健康功能和生活过程发展。 5）他们将通过在研究中提供治疗来评估成本的决定因素 诊断，治疗和生存阶段的癌症患者 医疗补助 总而言之，通过开发和测试新方法的成本效益 研究，并证明它们在几个正在进行的临床中的应用 研究，这项研究不仅提供了一系列有希望的技术，还提供 弥合方法论发展与实施之间的差距。