Improving Methods for Comparative Effectiveness Research in Cardiovascular Care

改进心血管护理比较有效性研究的方法

• 批准号: 7929895
• 负责人: Soko Setoguchi Iwata
• 金额: $ 14.57万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-30 至 2013-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7929895
• 关键词: Improving; Methods; Comparative; Effectiveness; Research

DESCRIPTION (provided by the applicant): Rising cost of healthcare fostered the demand for mechanisms to ensure money being spent wisely and the need for good comparative effectiveness (CE) information. The applicant who was trained in cardiology and advanced epidemiologic methods with a wealth of experience in CE studies aspires to improve methods of CE research for cardiovascular disease (CVD) using large databases that can potentially produce highly generalizable and directly applicable CE evidence. Specifically, the applicant will 1) develop new databases to study CE of therapies in patients with heart failure (HF) and coronary artery disease (CAD) by linking large claims databases from Medicaid, state pharmacy assistance programs, and Medicare with large clinical registries of CAD and HF and 2) develop and evaluate models for 3 analytic techniques A) high dimensional propensity score using data mining techniques, B) instrumental variable analysis, and C) propensity score calibration to combat bias due to lack of detailed clinical information in claims data research assessing CE of therapies in HF and CAD. When evaluating the validity of these analytic techniques in claims data analyses, the new databases linking claims and registries will be used as the gold standard. CAD will serve as an example when claims data lack information on potential confounders (e.g., disease severity) and HF will serve as an example when claims data also lack potential effect modifiers (e.g., ejection fraction). These proposed methods will be assessed using 4 clinically relevant CE questions: 1) angiotensin-converting enzyme inhibitors (ACEIs) vs. angiotensin II receptor blockers (ARBs) after myocardial infarction, 2) atorvastatin vs. other statins after acute coronary syndrome, 3) ACEIs vs. ARBs for HF, and 4) implantable cardioverter-defibrillators vs. medical therapy for HF. The applicant will have a full access to the aforementioned data sources and full support from collaborators, Drs. Sebastian Schneeweiss (epidemiology method), Robert Glynn (statistics), Lynne Stevenson (cardiovascular care), Francis Cook (data mining) and Richard Gliklich (registries). The applicant will enroll in coursework and attend seminars for statistics to hone skills in advanced analytic methods. She will also attend local and national seminars/conferences for CVD to update relevant clinical knowledge. This award would play an important role in the applicant's development as an outstanding researcher who can provide leadership in CE research for CVD, especially in large database methods.

描述（由申请人提供）：医疗保健成本的上升促进了对确保资金明智使用的机制的需求以及对良好的比较有效性（CE）信息的需求。申请人接受过心脏病学和高级流行病学方法方面的培训，在 CE 研究方面拥有丰富的经验，渴望使用大型数据库来改进心血管疾病 (CVD) 的 CE 研究方法，这些数据库可能会产生高度通用和直接适用的 CE 证据。具体来说，申请人将 1) 开发新的数据库，通过将医疗补助、州药房援助计划和医疗保险的大型索赔数据库与大型临床登记数据库联系起来，研究心力衰竭 (HF) 和冠状动脉疾病 (CAD) 患者治疗的 CE CAD 和 HF 以及 2) 开发和评估 3 种分析技术的模型 A) 使用数据挖掘技术的高维倾向评分，B) 工具变量分析，以及 C) 倾向评分校准，以消除由于缺乏而产生的偏差索赔数据研究中评估 HF 和 CAD 治疗的 CE 的详细临床信息。在评估这些分析技术在索赔数据分析中的有效性时，连接索赔和登记的新数据库将被用作黄金标准。当索赔数据缺乏潜在混杂因素（例如疾病严重程度）的信息时，CAD 将作为示例；当索赔数据也缺乏潜在影响因素（例如射血分数）时，HF 将作为示例。这些提议的方法将使用 4 个临床相关的 CE 问题进行评估：1) 心肌梗死后血管紧张素转换酶抑制剂 (ACEI) 与血管紧张素 II 受体阻滞剂 (ARB) 比较，2) 急性冠状动脉综合征后阿托伐他汀与其他他汀类药物比较，3) ACEI 与 ARB 治疗心力衰竭，以及 4) 植入式心律转复除颤器与心力衰竭药物治疗。申请人将可以完全访问上述数据源，并得到合作者 Drs. 的全力支持。 Sebastian Schneeweiss（流行病学方法）、Robert Glynn（统计学）、Lynne Stevenson（心血管护理）、Francis Cook（数据挖掘）和 Richard Gliklich（登记）。申请人将报名参加统计课程并参加统计研讨会，以磨练高级分析方法的技能。她还将参加当地和国家心血管疾病研讨会/会议，以更新相关的临床知识。该奖项将对申请人作为一名杰出的研究人员的发展发挥重要作用，他们可以在 CVD 的 CE 研究中发挥领导作用，特别是在大型数据库方法方面。