Tufts University Center for the Study of Drug Development, Boston, Massachusetts 02111, USA.
Appl Health Econ Health Policy. 2009;7(4):219-24. doi: 10.1007/BF03256155.
With the inclusion of $US1.1 billion earmarked for comparative effectiveness research (CER) in the recently enacted stimulus package, the US government indicated it will play an important role in informing prescribing and reimbursement decisions. However, this sizable investment does beg four important questions: what is the nature of CER data; what methods are suitable for collecting CER data; who is (should be) responsible for collecting CER data; and how will (should) CER data be used by the federal government? Using three recent high-profile cases of drugs and drug classes, we assess the current state of federal- and state-funded CER in the US. From these cases we observe that evidence is gradually emerging as a filter for certain prescribing and coverage decisions. The first case indicates evidence should not be gathered and applied in a post hoc fashion after a reimbursement decision has already been reached. Case 2 suggests limitations associated with making inferences from systematic reviews when applying the evidence to the treatment of individual patients. Case 3 points to a comprehensive, but more costly and time-consuming, way of gathering data to inform prescribing and reimbursement decisions. Despite caveats, we argue that there is room for building a more systematic and better coordinated evidence base in the US, so that all stakeholders are better equipped to understand variation in clinical outcomes while promoting appropriate prescribing patterns. Accordingly, CER could help close the gap between what we know and what we do in pharmaceutical care. For the majority of cases in which CER is carried out, we favour a pluralistic system of CER analyses with a clearing-house for systematic reviews conducted by multiple evidence-based practice centres, each uniquely suited to its constituency.
随着最近颁布的经济刺激方案中纳入了 11 亿美元用于比较疗效研究（CER），美国政府表示将在为处方和报销决策提供信息方面发挥重要作用。然而，这一大笔投资确实引发了四个重要问题：CER 数据的性质是什么；收集 CER 数据的合适方法是什么；谁（应该）负责收集 CER 数据；联邦政府将如何（应该）使用 CER 数据？我们使用最近三个备受瞩目的药物和药物类别案例，评估了美国目前联邦和州资助的 CER 状况。从这些案例中，我们观察到证据逐渐成为某些处方和覆盖决策的筛选器。第一个案例表明，在报销决定已经做出之后，不应该以事后的方式收集和应用证据。第二个案例表明，在将证据应用于个体患者的治疗时，从系统评价中得出推论存在局限性。第三个案例指向一种全面但成本更高、耗时更长的数据收集方法，以告知处方和报销决策。尽管存在警告，但我们认为，在美国建立一个更系统、更好协调的证据基础是有空间的，以便所有利益相关者都能更好地理解临床结果的变化，同时促进适当的处方模式。因此，CER 可以帮助缩小我们所知与在药物治疗中所做之间的差距。对于进行 CER 的大多数情况，我们赞成采用 CER 分析的多元化系统，并为多个循证实践中心进行的系统评价建立一个信息交换所，每个中心都适合其受众。
