首页 > 资讯 > EvGen意味着什么II：构建证据生成国家体系

出自识林

2016-05-04 FDA Voice

（译自FDA Voice “What We Mean When We Talk About EvGen Part II: Building Out a National System for Evidence Generation” 2016年5月3日，作者：Robert Califf，医师，FDA局长；Rachel Sherman，医师，FDA医药产品和烟草助理副局长。）

在之前的博文中，我们讨论了两个概念 — 互操作性（interoperability）和连通性（connectivity）— 是打造成功的证据生成（EvGen）国家体系的基本前提。在这篇博文中，我们来看看如何应用这些结构构建这一体系。

构建EvGen

创造知识需要应用对生物医学数据行之有效的分析方法和技术以产生可靠的结论。直到最近，这样的分析通常是由在限制数据访问的中心工作的专家来完成。这种“围墙花园”方式的发展有以下几个原因：必须保护敏感医疗数据的隐私和机密性；对不适当、有偏见或不称职分析的负面结果的担心；将数据作为竞争性资产的趋势。不论具体原因如何，结果是相同的：对数据共享的广泛而系统的壁垒。

如果我们要扭转这样的趋势，并鼓励打造所设想的EvGen证据的新方法，我们必须牢记几个关键原则：
1. 对于数据如何呈现、报告和分析必须有通用方法，以及严格的方法确保患者隐私和数据安全。
2. 参与原则必须透明，并通过在整个相关生态系统及其利益攸关者中建立共识的程序制定。
3. 为确保对通常包括竞争优先事项和激励机制的多样化生态系统的支持，体系的输出必须用于公益事业，并易于所有利益攸关者获取。

实践中的EvGen会是什么样子？

稳健的证据生成国家平台会是什么样子？可以将EvGen设想为帮助告知所有利益攸关者做出治疗决策的所有活动的一把伞。

评价药品、生物制品或器械的任务包括不同的数据需求和方法。然而，所有数据和方法都有一个共同属性：个体和群体以及其经历诊断或预后测试或暴露于治疗干预之后的相关临床结果表征。

此外，当医疗实践本身是评估的一部分，交付系统的组织和功能表征是重要的。换而言之，一种证据需要评估医疗产品的安全性和有效性，另一种证据需要指导大量重叠医疗实践。

过去十年中，“二次利用”领域出现了巨大进展，即用于一个目的（例如，作为常规临床护理的一部分）收集的数据，可以再次用于其它目的（例如研究、安全监测或质量改善）。

为响应国会授权制定主动上市后风险识别和分析系统而推出的哨兵行动就是一个例子。以成功的项目（例如美国疾病控制和预防中心的疫苗安全数据链）为蓝本的哨兵系统允许FDA通过主动查询不同数据源开展安全监测，主要是行政管理和保险理赔数据库，还包括来自电子健康记录（EHR）系统的数据，快速和安全地评估可能的医疗产品安全问题。

再如，国家以患者为中心的临床研究网络（PCORnet）是一个全国性系统，包括许多EvGen所需的属性。PCORnet包括来自政府、工业界、学术界和患者及其倡导者的参与。FDA的哨兵系统主要建立在理赔数据之上重新用于安全监测，PCORnet被设计为利用EHR数据支持实用性临床研究。

美国国家卫生研究院（NIH）的卫生保健系统研究合作实验室已通过其分布式研究网络证明二次数据使用的概念可以扩展到前瞻性实用性干预试验领域。NIH合作实验室计划包括哨兵系统和PCORnet中所涉及的许多相同的医疗保健系统，拥有10个正在开展的活跃试验。

此外，Reagan-Udall基金会医学证据开发和监测创新（IMEDS）评估计划正在探索管理机制以确保私营部门，特别是受监管行业，可以与哨兵数据合作伙伴合作发起上市医疗产品的安全查询。这些措施有可能在超出方法学领域之外扩大私营伙伴的参与，进一步帮助确保哨兵系统继续扩展成为全国性资源。

同样，正在努力建立国家器械评估系统（NDES）。按照目前设想，NDES将通过战略联盟和共同治理建立。该系统将建立于并利用来自电子现实世界的数据源信息，例如通过器械登记、理赔数据和EHR方面的日常临床实践收集数据，具体数据源之间的激活链接可以适当解决具体问题。

由于大量工作已经在所有这些领域中完成，宝贵的经验正在积累。下一步是确保这些开拓性的努力凝聚成真正的全国性资源。更多内容请关注后续博文。

编译：识林-椒
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What We Mean When We Talk About EvGen Part II: Building Out a National System for Evidence Generation
Posted on May 3, 2016 by FDA Voice
By: Rachel E. Sherman, M.D., M.P.H., and Robert M. Califf, M.D.

In an earlier FDA Voice blog post, we discussed a pair of concepts – interoperability and connectivity – that are essential prerequisites for the creation of a successful national system for evidence generation (or “EvGen”). In this post, we take a look at how we would apply these constructs as we go about building such a system.

Building EvGen

Creating knowledge requires the application of proven analytical methods and techniques to biomedical data in order to produce reliable conclusions. Until recently, such analysis was done by experts operating in centers that typically restricted access to data. This “walled garden” approach evolved for several reasons: the imperative to protect the privacy and confidentiality of sensitive medical data; concern about the negative consequences that could arise from inappropriate, biased, or incompetent analysis; and, the tendency to see data as a competitive asset. Regardless of the specific reason, the result has been the same: widespread and systemic barriers to data sharing.

If we are to reverse these tendencies and foster a new approach to creating evidence of the kind envisioned for EvGen, we must bear in mind several critical principles:

There must be a common approach to how data is presented, reported and analyzed and strict methods for ensuring patient privacy and data security. Rules of engagement must be transparent and developed through a process that builds consensus across the relevant ecosystem and its stakeholders. To ensure support across a diverse ecosystem that often includes competing priorities and incentives, the system’s output must be intended for the public good and be readily accessible to all stakeholders.

What Would EvGen Look Like in Practice?

What would a robust national platform for evidence generation look like? It may be helpful to envision EvGen as an umbrella for all activities that help inform all stakeholders about making treatment decisions.

The task of evaluating drugs, biologics, or devices encompasses different data needs and methods. However, all share a common attribute: the characterization of individuals and populations and their associated clinical outcomes after they have undergone diagnostic or prognostic testing or been exposed to a therapeutic intervention.

Moreover, when medical practice itself is part of the evaluation, characterization of the organization and function of delivery systems is critical. In other words, the kinds of evidence needed to evaluate medical products for safety and effectiveness and the kinds of evidence needed to guide medical practice overlap substantially.

Over the last decade, there has been enormous progress in the area of “secondary use,” in which data collected for one purpose (for instance, as part of routine clinical care) can be reused for another (such as research, safety monitoring, or quality improvement).

The Sentinel Initiative, launched in response to a Congressional mandate to develop an active postmarket risk identification and analysis system, is one example. Modeled after successful programs such as the Centers for Disease Control and Prevention's Vaccine Safety Datalink, Sentinel allows FDA to conduct safety surveillance by actively querying diverse data sources, primarily administrative and insurance claims databases but also data from electronic health record (EHR) systems, to evaluate possible medical product safety issues quickly and securely.

Another example, [the National Patient-Centered Clinical Research Network (PCORnet), is a national system that includes many of the attributes needed for EvGen. PCORnet includes participation from government, industry, academia, and patients and their advocates. Whereas FDA’s Sentinel system is built primarily on claims data repurposed for safety surveillance, PCORnet is designed to leverage EHR data in support of pragmatic clinical research.

The [NIH's Health Care Systems Research Collaboratory has demonstrated through its Distributed Research Network that the concept of secondary data use can be extended into the realm of prospective pragmatic interventional trials. The NIH Collaboratory program, which includes many of the same health care systems involved in Sentinel and PCORnet, has 10 active trials underway.

In addition, the Reagan-Udall Reagan-Udall Foundation Innovation in Medical Evidence Development and Surveillance (IMEDS) Evaluation Program is exploring governance mechanisms to ensure that private-sector entities, notably regulated industry, can collaborate with Sentinel data partners to sponsor safety queries about marketed medical products. Such measures have the potential to expand the involvement of private-sector partners beyond the arena of methodology, further helping to ensure that Sentinel continues its expansion into a national resource.

Similarly, efforts are underway to establish a National Device Evaluation System (NDES). As currently envisioned, the NDES would be established through strategic alliances and shared governance. The system would build upon and leverage information from electronic real-world data sources, such as data gathered through routine clinical practice in device registries, claims data, and EHRs, with linkages activated among specific data sources as appropriate to address specific questions.

As substantial work already is being done in all of these areas, valuable experience is being gained. The next step is to ensure that these pioneering efforts coalesce into a true national resource. More on that in future postings.