Effect of Therapeutic Class on Generic Drug Substitutions

项目摘要 使用仿制药取代品牌药品导致保险公司和患者的价格更低。 美国食品和药物管理局(FDA)确保获得批准的仿制药提供 与相应品牌相同的质量、安全和功效。尽管如此，一些临床医生和患者 不愿使用仿制药。有时，这是基于一种担忧，即即使是微小的差异 吸收或新陈代谢影响结果[例如治疗指数(NTI)非常窄的药物]。在……里面 然而，在其他情况下，“普遍不情愿”的原因是模棱两可的。如果社会目标是允许 让患者获得有价值的药物，同时在医疗保健系统内控制成本，我们需要 理解为什么对仿制药有不同的接受。 根据FDA的要求，我们提议签订一项合作协议，以促进知识 关于仿制药的用法，仿制药替代品牌药，以及仿制药的修饰 患者、处方者和卫生系统层面的仿制药使用。我们假设这些因素 对仿制药使用的影响因治疗类别而异。我们建议：1)量化仿制药的使用 美国按治疗类别分类并评估仿制药替代的预测因素；2)量化患者报告的担忧 关于仿制药，按治疗类别分类，并确定患者报告的反应担忧的风险因素 到仿制药替代；以及3)制定评估方案，对需要仿制药的药物进行优先排序 开发和投资，并应用评价计划来确定优先药物。 为了解决这个项目的目标，我们提出了三个活动，使用高度集中的数据集 补充信息。第一个是来自综合健康系统(Sutter Health)的数据， 重要的是，这将使我们能够查看书面处方，除了药剂师填写的处方。这些 然后，将在Truven Health Analytics(MarketScan Commercial Claims)的一个单独的、非常大的数据集中确认使用情况的预测因素。这些数据包括具有代表性的患者的药房填写数据 全国范围内商业保险患者的数量。在这两个来源之间，我们将能够列举 哪些治疗类有很多和很少的通用用法，并使用广义分层模型，看看 一般用法的预测者。我们还将分析FDA不良事件报告系统数据(FAERS)。 我们将隔离患者生成的报告，特别是那些提到难以切换到 非专利产品。我们将主要分析公共可访问的编码数据，但将使用 提交了案例报告以验证我们的方法。最后，有了所获得的知识，我们将制定一个 对需要仿制药开发和投资的药物进行优先排序并应用评估的计划 确定优先药物的计划。我们将与专家和主要利益相关者一起使用结构化流程来 告知可应用于目前具有市场排他性的药品的分类法的发展。

Project Summary The use of generic drugs in place of branded drug products results in lower prices to insurers and patients. The U.S. Food and Drug Administration (FDA) assures that an approved generic product provides the same quality, safety, and efficacy as the corresponding brand. Despite this, some clinicians and patients are reluctant to use generic medications. Sometimes, this is based on a concern that even a small difference in absorption or metabolism impacts outcomes [such as drugs with very narrow therapeutic indices (NTI)]. In other cases, however, the reasons for “generic reluctance” are ambiguous. If the societal goal is to allow patients to access worthy medications while containing costs within the health care system, we need to understand why there is differential acceptance of generic drugs. As requested by the FDA, we propose to enter into a cooperative agreement to advance knowledge about usage of generic drugs, substitution of generic drugs for brand-name drugs, and the modifiers of generic drug use at the patient, prescriber, and health system level. We hypothesize that the factors which influence generic drug use vary by therapeutic class. We propose to: 1) quantify generic drug usage in the U.S. by therapeutic classes and assess predictors of generic substitution; 2) quantify patient-reported concerns about generic drugs, by therapeutic class, and to identify risk factors for patient-reported concerns in response to generic substitution; and 3) develop an evaluation scheme to prioritize drugs requiring generic product development and investment and to apply the evaluation scheme to identify priority drugs. To address the aims of this project, we propose three activities using datasets with highly complementary information. The first is data from an integrated health system (Sutter Health) that, importantly, will allow us to look at written prescriptions, in addition to pharmacist-filled prescriptions. These predictors of usage will then be confirmed in a separate, very large dataset from Truven Health Analytics(MarketScan Commercial Claims). These data include pharmacy fill data from patients who are representative of commercially-insured patients across the country. Between these two sources, we will be able enumerate which therapeutic classes have much and little generic usage, and using generalized hierarchical models, look at predictors of generic usage. We will also analyze the FDA Adverse Event Reporting System data (FAERS). We will isolate patient-generated reports and, specifically, those with mention difficulties with switching to a generic product. We will primarily analyze the publically accessible coded data but will use a subset of the submitted case reports to validate our methodology. Finally, with the knowledge gained, we will develop a scheme to prioritize drugs requiring generic product development and investment and apply the evaluation scheme to identify priority drugs. We will use a structured process with experts and key stakeholders to inform the development of a taxonomy that can be applied to drugs currently with market exclusivity.