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）：医疗保健成本的上涨促进了对机制的需求，以确保钱被明智地花费，并需要良好的比较效率（CE）信息。接受过丰富经验的CE研究经验的心脏病学和高级流行病学方法培训的申请人渴望使用大型数据库改善心血管疾病研究方法（CVD）的方法，这些数据库有可能产生高度可推广且直接适用的CE证据。具体而言，申请人将1）开发新数据库，通过将Medicaid，State Pharmacy援助计划的大量索赔数据联系起来，将心力衰竭（HF）和冠状动脉疾病（HF）和冠状动脉疾病（CAD）的CE进行研究，以及Medicare的大量数据库，Medicare与CAD和HF的大型临床注册和HF的大量临床注册和2）使用3分析技术的仪器和评估模型，并开发了3个分析技术的仪器，该模型是高度差异的，A） C）由于缺乏索赔数据研究评估HF和CAD疗法的索赔数据研究中缺乏详细的临床信息，因此倾向得分校准了。在评估索赔数据分析中这些分析技术的有效性时，将索赔和注册表联系起来的新数据库将被用作黄金标准。当索赔数据缺乏潜在的混杂因素（例如疾病严重程度）的信息时，CAD将作为一个例子，而当索赔数据还缺乏潜在效应修饰符（例如，射血分数）时，HF将作为一个例子。这些提出的方法将使用4个临床相关的CE问题评估：1）血管紧张素转化酶抑制剂（ACEIS）与血管紧张素II受体阻滞剂（ARB）（ARB）在心肌梗死后，2）atorvastatin atorvastatin atorvastatin vs.其他statins vs.急性冠状动脉综合综合症后的其他Statins，3） HF的医疗疗法。申请人将完全访问上述数据源，并得到合作者DRS的全部支持。 Sebastian Schneeweiss（流行病学方法），Robert Glynn（统计），Lynne Stevenson（心血管护理），Francis Cook（数据挖掘）和Richard Gliklich（注册表）。申请人将参加课程工作，并参加统计的研讨会，以磨练高级分析方法的技能。她还将参加CVD的本地和国家研讨会/会议，以更新相关的临床知识。该奖项将在申请人的发展中发挥重要作用，作为杰出的研究人员，可以在CVD中提供领导力，尤其是在大型数据库方法中。