Effect of Therapeutic Class on Generic Drug Substitutions

项目摘要 使用非专利药品代替品牌药品，降低了保险公司和患者的价格。 美国食品和药物管理局（FDA）确保批准的仿制药提供 与相应品牌的质量、安全性和有效性相同。尽管如此，一些临床医生和患者 不愿意使用仿制药。有时，这是基于一种担忧，即即使是很小的差异， 吸收或代谢影响结果[如治疗指数（NTI）非常窄的药物]。在 然而，在其他情况下，“一般性不情愿”的原因是模糊的。如果社会的目标是允许 患者获得有价值的药物，同时控制医疗保健系统内的成本，我们需要 理解为什么对仿制药的接受程度不同。 根据FDA的要求，我们建议签订一项合作协议， 关于仿制药的使用，仿制药替代名牌药，以及 在患者、处方者和卫生系统层面使用仿制药。我们假设， 影响仿制药使用因治疗类别而异。我们建议：1）量化仿制药的使用， 美国按治疗类别和评估通用替代的预测因素; 2）量化患者报告的问题 关于仿制药，按治疗类别，并确定患者报告的风险因素， 3）制定评估计划，优先考虑需要仿制药的药物 开发和投资，并应用评估计划来确定优先药物。 为了实现这个项目的目标，我们提出了三个活动，使用数据集， 补充信息。第一个是来自综合卫生系统（Sutter Health）的数据， 重要的是，除了药剂师开具的处方外，还能让我们看到书面处方。这些 然后，使用的预测因素将在Truven Health Analytics（MarketScan Commercial Claims）的一个单独的非常大的数据集中得到确认。这些数据包括来自具有代表性的患者的药房填充数据 商业保险患者的数量在这两个来源之间，我们将能够列举出 哪些治疗类有很多和很少的通用用法，并使用广义层次模型，看 在通用用法的预测。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，特别是那些在切换到 通用产品。我们将主要分析可访问的编码数据，但将使用 提交案例报告以验证我们的方法。最后，利用获得的知识，我们将开发一个 优先考虑需要仿制药开发和投资的药物并进行评估的计划 确定优先药物的计划。我们将使用一个有专家和主要利益相关者参与的结构化流程， 为制定可应用于目前具有市场独占性的药物的分类法提供信息。

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.