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: 6889318
• 负责人: Joseph C Gardiner
• 金额: $ 33.23万
• 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 2007-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6889318
• 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）：在经济拮据的时代，评估医疗保健计划的成本和结果以及将成本与竞争性干预措施的结果进行比较的方法已成为追求从特定预算中优化健康效益的最前沿，或者寻找针对特定健康影响的最低成本策略。 本研究的目的是开发、测试和应用创新的统计方法来分析医疗保健成本、利用率和结果，以期为医疗保健资源分配决策提供信息。 我们提出了一个统一的随机框架，其中干预成本是随着患者健康史随时间的推移而通过资源使用动态产生的。 我们的模型认识到流行病学和临床研究中通常存在的数据的局限性。 我们纳入了患者的可观察特征，例如人口统计和合并症，并考虑了可能影响成本和健康结果的未测量变量。 我们估计了经济评估中常用的汇总指标（例如预期寿命、质量调整生命年、净现值、净健康效益和成本效益比），并得出对这些指标进行统计推断的基础。 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。 我们建议使用国家数据库和正在进行的临床研究来应用我们的方法。 1) 使用全国住院患者样本 (NIS)，我们将估计与合并症、患者人口统计数据和临床特征相关的住院费用： (a) 对于接受心脏手术（冠状动脉搭桥手术、经皮心脏手术）的急性心肌梗死 (AMI) 患者冠状动脉介入治疗）； (b) 对于患有乳腺癌、接受乳房切除术或肿瘤切除术的妇女； (c) 对于接受结肠切除术的结直肠癌患者。 2) 使用 1996 年至 2000 年密歇根州医疗补助和医疗保险索赔数据库，我们研究了治疗方法、诊断时的癌症分期、患者人口统计数据以及合并症对乳腺癌、结直肠癌、肺癌和前列腺癌患者的费用和生存的影响。 3) 在护士管理方案的试验中，强调在没有器质性疾病证据的高利用率患者中建立牢固的患者-提供者关系，我们将估计与生活质量（QOL）、精神疾病改善相关的成本和成本效益。以及身体健康功能和患者满意度。 4) 在对接受乳腺癌手术的女性进行干预试验中，我们评估了费用、医疗保健利用率、生活质量以及术前身心健康功能的恢复情况。 5) 在针对 AMI 后患者的 Heart After Hospital Recovery Planner 研究中，我们研究了旨在有效利用健康教育和管理资源的干预措施对生活质量的影响。 该应用程序有助于国际研究工作，以开发分析医疗保健成本和结果的严格方法，并且应用于临床和流行病学研究，它直接将研究转化为实践。