Cost-Effectiveness of Dabigatran and Warfarin for Veterans with Afib

 描述（由申请人提供）： 对退伍军人医疗保健的预期影响：美国估计有270万人被诊断患有房颤（AF）。据估计，这些人患缺血性中风的风险增加了五倍。靶向特异性口服抗凝剂（TSOAC）的出现为临床医生提供了抗凝治疗的替代方案。目前尚不清楚在临床试验中观察到的TSOAC的获益是否会在非试验VHA人群中保持，如果是这样，改善的结局是否会平衡药物的显着更高的成本。拟议的成本效益研究比较了华法林和TSOAC在退伍军人人群中的应用。研究结果将增加退伍军人获得最有效治疗的机会，并帮助退伍军人事务部政策制定者制定基于证据的房颤治疗指南。项目背景：房颤治疗的重点是预防血栓形成，以降低卒中风险。维生素K拮抗剂（如华法林）已成功降低卒中风险，但这些方法的有效性受到狭窄治疗范围和每月实验室监测剂量调整以防止过度抗凝和随后出血的需要的阻碍。自2010年以来，两类新的TSOAC，凝血酶抑制剂（例如达比加群）和Xa抑制剂进入市场。临床试验提供了很好的证据，证明TSOAC在各种结局方面优于或不劣于华法林。基于这些临床试验结果的初步成本效益研究得出结论，这些药物可能具有成本效益。目前尚不清楚临床试验中发现的TSOAC的健康和成本优势是否会在临床实践中保持，因为这些试验招募了更健康的患者并保持了更好的依从性。项目目标：我们将推断房颤治疗、结局和成本之间的因果关系。目的1.估计供应商或机构级处方变化与控制过程质量的AF治疗选择之间的关系。目标2.估计工具变量（IV）和倾向评分统计模型的结果，作为处方华法林与TSOAC相比的函数。目标3.使用目标2中IV或倾向评分模型之间的首选规范，预测相关亚群（例如，年龄> 75岁）中与TSOAC相比，作为处方华法林的函数的健康结局。目标4.估计整个研究期间接受华法林治疗的患者与接受TSOAC治疗的患者相比的VA、Medicare和VA + Medicare总成本。项目方法：拟议的项目是一项回顾性观察性研究的二级数据，从病人一级的行政和索赔数据从退伍军人事务部，医疗保险和医疗补助。VA药房数据将用于确定2011年至2015年期间新诊断为AF的患者是否开始华法林或TSOAC。患者将被分配给最初开具抗凝治疗处方的提供者。供应商处方模式将用作预测个体开始华法林或TSOAC的可能性的工具变量，控制过程质量（目标1）。将从目标1中估计的剩余目标的方程中获取恢复力。目标2和3将使用两阶段残留纳入工具变量或倾向评分模型来确定开始华法林治疗与 或TSOAC和健康结果。目标4将使用类似的模型来预测VA和Medicare成本，并确定最具成本效益的治疗。

 DESCRIPTION (provided by applicant): Anticipated Impact on Veterans Health Care: An estimated 2.7 million individuals in the United States were diagnosed with atrial fibrillation (AF). These individuals are estimated to have a five-fold increased risk of ischemic stroke. The emergence of target specific oral anticoagulants (TSOAC) has provided clinicians with alternatives for anticoagulation therapy. It is unknown whether the benefits of TSOACs seen in clinical trials will be maintained in a non-trial VHA population and if so, whether the improved outcomes balance the significantly higher cost of the drugs. The proposed cost-effectiveness study compares warfarin to TSOACs for a veteran population. Results will increase access to the most effective treatments for veterans and help VA policymakers develop evidence-based guidelines for AF treatment. Project Background: AF treatment focuses on the prevention of blood clots to reduce the risk of stroke. Vitamin K antagonists (e.g. warfarin) have successfully reduced the risk of stroke but the effectiveness of these methods are hampered by narrow therapeutic ranges and the need for monthly laboratory monitoring for dose adjustment to prevent over-anticoagulation and subsequent hemorrhage. Since 2010, two new classes of TSOACs, thrombin inhibitors (e.g. dabigatran) and Xa inihibitors, entered the market. Clinical trials provide good evidence that the TSOACs are either superior or not inferior to warfarin on a variety of outcomes. Initial cost-effectiveness studies based on these clinical trial results have concluded these drugs may be cost- effective. It is unknown whether the health and cost advantages of TSOACs found in clinical trials will be maintained in clinical practice since these trials enroll healthier patients and maintain better adherence. Project Objectives: We will infer causal relationships between treatments for AF, outcomes and cost. Objective 1. Estimate relationships between provider or facility-level prescribing variation and AF treatment selection controlling for process quality. Objective 2. Estimate instrumental variable (IV) and propensity score statistical models of outcomes as a function of being prescribed warfarin compared to TSOACs. Objective 3. Using the preferred specification between IV or propensity score models in Objective 2, predict health outcomes as a function of being prescribed warfarin compared to TSOACs among relevant sub- populations (e.g. age>75). Objective 4. Estimate total VA, Medicare, and VA+Medicare costs over the entire study period for patients receiving warfarin compared to TSOACs. Project Methods: The proposed project is a retrospective observational study of secondary data from patient- level administrative and claims data from VA, Medicare and Medicaid. VA pharmacy data will be used to determine whether patients with a new diagnosis of AF between 2011 and 2015 initiate warfarin or a TSOAC. Patients will be assigned to the provider that initially prescribes anticoagulation therapy. Provider prescribing patterns will be used as an instrumental variable to predict the likelihood of an individual initiating warfarin or a TSOAC, controlling for process quality (Objective 1). Residuals will be captured from the equations estimated in Objective 1 for the remaining objectives. Objectives 2 and 3 will use two-stage residual inclusion instrumental variable or propensity score models to identify the causal relationship between initiating warfarin or a TSOAC and health outcomes. Objective 4 will use similar models to predict VA and Medicare costs and determine the most cost-effective treatment.