Use of Regression Models in Cost-effectiveness Analysis

回归模型在成本效益分析中的应用

• 批准号: 7027704
• 负责人: Joseph C Gardiner
• 金额: $ 33.37万
• 依托单位: MICHIGAN STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-05-01 至 2007-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7027704
• 关键词: behavioral /social science research tag; breast neoplasms; breast surgery; colorectal neoplasms; comorbidity; cost effectiveness; decision making; health care cost /financing; health care quality; health care service evaluation; health care service utilization; health services research tag; heart surgery; human data; mathematical model; model design /development; myocardial infarction; neoplasm /cancer surgery; quality of life; socioeconomics; statistics /biometry

DESCRIPTION (PROVIDED BY APPLICANT): In an era of economic constraints, methods for assessing costs and outcomes of health care programs, and comparing costs with outcomes of competing interventions have come to the forefront in the pursuit of optimizing health benefits from a specified budget, or in finding the lowest cost strategy for a specified health effect. The objective of this research is to develop, test, and apply innovative statistical methods for analyses of health care costs, utilization, and outcomes with the goal of informing decision-making in the allocation of health care resources. We propose a unified stochastic framework in which costs of an intervention are incurred dynamically through resource use as a patient's health history unfolds over time. Our models recognize limitations in data that are typically present in epidemiologic and clinical studies. We incorporate observable characteristics of patients, such as demographics and comorbid conditions, and account for unmeasured variables that might influence both cost and health outcomes. We estimate summary measures commonly used in economic evaluations (e.g., life expectancy, quality-adjusted life years, net present value, net health benefit, and cost-effectiveness ratios) and derive the basis for statistical inference on these measures. We then test the performance and sensitivity of our procedures with both real and simulated data. We propose applications of our methods using national state databases and ongoing clinical studies. 1) Using the Nationwide Inpatient Sample (NIS), we will estimate inpatient costs in relation to comorbidity, patient demographics, and clinical attributes: (a) for patients with acute myocardial infarction (AMI) undergoing cardiac procedures (coronary artery bypass surgery, percutaneous coronary intervention); (b) for women with breast cancer, undergoing mastectomy or lumpectomy; (c) for patients with colorectal cancer undergoing colectomy. 2) Using the Michigan Medicaid and Medicare claims database for 1996 to 2000, we examine the impact of treatments, cancer stage at diagnosis, patient demographics, and comorbid illnesses on cost and survival in patients with breast, colorectal, lung, and prostate cancer. 3) In a trial of a nurse-managed protocol emphasizing strong patient-provider relationships in high-utilizing patients with no evidence of organic disease, we will estimate costs and cost-effectiveness in relation to improvements in quality of life (QOL), mental and physical health functioning and patient satisfaction. 4) In a trial of an intervention in women undergoing surgery for breast cancer, we assess costs, health care utilization, QOL, and return to presurgery physical and mental health functioning. 5) In the Heart After Hospital Recovery Planner study of patients after AMI, we examine the impact on QOL of an intervention aimed at efficient use of resources in health education and management. This application contributes to an international research effort to develop rigorous methods for analyses of health care costs and outcomes, and, applied to clinical and epidemiologic studies, it directly translates research into practice.

描述（由申请人提供）：在经济限制的时代，评估成本和医疗保健计划结果的方法，以及将成本与竞争干预措施的结果进行比较，以追求从指定预算中优化健康福利的最前沿，或者在为指定的健康效果中找到最低的成本策略。 这项研究的目的是开发，测试和应用创新的统计方法，以分析医疗费用，利用和结果，目的是为卫生保健资源分配的决策提供信息。 我们提出了一个统一的随机框架，其中一项干预成本通过资源使用而动态地发生，因为患者的健康病史随着时间的流逝而不断发展。 我们的模型确定了通常存在于流行病学和临床研究中的数据的局限性。 我们结合了患者的可观察特征，例如人口统计学和合并症，并考虑了可能影响成本和健康结果的未衡量变量。 我们估计经济评估中常用的摘要措施（例如，预期寿命，质量调整后的寿命，净现现代价值，净健康收益和成本效益比），并得出了对这些措施的统计推断的基础。 然后，我们使用真实数据和模拟数据测试程序的性能和灵敏度。 我们建议使用国家状态数据库和正在进行的临床研究的方法应用。 1）使用全国住院样本（NIS），我们将估计与合并症，患者人口统计和临床属性有关的住院费用：（a）对于患有心脏手术（冠状动脉旁路手术，经皮性冠状动脉培训）的急性心肌梗塞（AMI）患者； （b）对于乳腺癌女性，进行乳房切除术或肿块切除术； （c）针对结肠切除术的结直肠癌患者。 2）使用1996年至2000年的密歇根州医疗补助和医疗保险索赔数据库，我们研究了治疗，诊断时的癌症阶段，患者人口统计学和合并症对乳腺癌，结直肠癌，肺和前列腺癌患者成本和生存的影响。 3）在一项由护士管理的方案的试验中，强调没有有机疾病证据的高度利用患者的牢固患者关系，我们将估计成本和成本效益与改善生活质量（QOL），精神和身体健康功能和患者满意度有关。 4）在对接受乳腺癌手术的妇女进行干预的试验中，我们评估成本，医疗保健利用，QOL以及返回前身体和心理健康功能。 5）在医院恢复后的心脏恢复计划者对AMI后的患者研究后，我们研究了旨在有效利用资源在健康教育和管理中的干预措施的影响。 该申请有助于国际研究工作，以开发严格的医疗保健成本和结果分析的方法，并应用于临床和流行病学研究，它直接将研究直接转化为实践。