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药物警戒的自动化支持:一个提议的系统。

Automated support for pharmacovigilance: a proposed system.

作者信息

Bright Roselie A, Nelson Robert C

机构信息

Center for Devices and Radiological Health, Food and Drug Administration, 1350 Piccard Drive, HFZ-541, Rockville, MD 20850, USA.

出版信息

Pharmacoepidemiol Drug Saf. 2002 Mar;11(2):121-5. doi: 10.1002/pds.684.

Abstract

Governments, manufacturers, and other entities are interested in adverse event surveillance of marketed medical products. FDA's Center for Drug Evaluation and Research redesigned the post-marketing adverse reaction surveillance process to use the advantages of new technology. As part of this effort, a 'Pharmacovigilance Working Group' designed a new strategy for the review and analyses of adverse event reports received by FDA. It created requirements which divided signal detection into five tiers: (1) Single 'urgent' reports would be sent to reviewers' workstations nightly for immediate attention. Reviewers would be able to customize definitions of 'urgent' (events that should not wait for aggregate review). (2) Single urgent reports would be placed in a context matrix containing historical counts of similar events to aid in initial interpretation. (3) In this first level of aggregate review, graphical displays would highlight patterns within all the reports, both urgent and non-urgent, and (4) periodic drug-specific tabled-based reports would display the newly received reports across a pre-defined variety of displays. These four tiers would produce passive and criteria-based results which would be presented to safety reviewers' electronic workstations. (5) Active query capabilities (routine, such as age, sex, and year distributions, as well as ad hoc) would be available for exploring alerted issues. The historical database would be migrated into the new format. All historical and new reaction data would be coded with the new MedDRA (Medical Dictionary for Regulatory Activities) scheme. The strategy was to design a full data capture system which effectively exploits current computing advances and technical performance to automate many aspects of initial adverse event review, supporting more efficient and effective clinical assessment of safety signals.

摘要

政府、制造商及其他实体对已上市医疗产品的不良事件监测颇感兴趣。美国食品药品监督管理局(FDA)药品评价与研究中心重新设计了上市后不良反应监测流程,以利用新技术的优势。作为这项工作的一部分,一个“药物警戒工作组”为FDA收到的不良事件报告的审查和分析设计了一项新策略。它制定了要求,将信号检测分为五个层级:(1)单一“紧急”报告每晚将被发送至审评员的工作站以便立即关注。审评员能够定制“紧急”(不应等待汇总审查的事件)的定义。(2)单一紧急报告将被置于一个包含类似事件历史计数的背景矩阵中,以辅助初步解读。(3)在这一级别的汇总审查中,图形显示将突出所有报告(紧急和非紧急)中的模式,并且(4)定期的特定药物表格报告将在预先定义的各种显示中展示新收到的报告。这四个层级将产生被动的和基于标准的结果,这些结果将呈现给安全审评员的电子工作站。(5)将具备主动查询功能(常规的,如年龄、性别和年份分布,以及临时的)用于探究警报问题。历史数据库将被迁移到新格式。所有历史和新的反应数据将采用新的《监管活动医学词典》(MedDRA)方案进行编码。该策略旨在设计一个完整的数据捕获系统,有效利用当前的计算进展和技术性能,使初始不良事件审查的许多方面自动化,支持对安全信号进行更高效和有效的临床评估。

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