通过分析常规收集的健康数据来支持药监信号验证和优先级:从EHDEN网络研究中吸取的经验教训
Oskar Gauffin1, Judith S Brand2, Sara Hedfors Vidlin1
1Uppsala Monitoring Centre, Uppsala, Sweden.
Drug safety
|October 7, 2023
概括
常规的健康数据分析是可行的,用于药监信号验证和优先级,在几个小时内做出决定. 需要进一步的研究来评估在信号管理的早期整合这些分析的成本效益.
科学领域:
- 药监和药物安全 药监和药物安全
- 医疗信息学 医疗信息学
- 药学流行病学 药学流行病学
背景情况:
- 个人病例报告对于药监信号管理至关重要.
- 信号验证确定了进一步评估的证据,优先级正在进行中.
- 常规收集的健康数据提供了上下文,但通常在药物流行病学研究中稍后使用.
研究的目的:
- 评估分析多国常规健康数据的可行性和实用性,以进行信号验证和优先排序.
- 确定用户对将例行健康数据分析整合到信号管理流程中的要求.
主要方法:
- 利用VigiBase (世卫组织全球数据库) 进行针对仿制药和不良事件的统计信号检测.
- 通过使用VigiBase,监管文件,文献和对来自五个国家的10个欧洲健康数据和证据网络 (EHDEN) 合作伙伴的例行健康数据的描述性分析,进行了为期5天的信号验证和优先级研究.
- 包括来自英国,西班牙,挪威,荷兰和塞尔维亚的初级保健和医院数据.
主要成果:
- 八十五个统计信号得到了验证,其中八个使用常规健康数据进行分析.
- 在几个小时内 (执行时间为15-60分钟) 对八个信号中的五个进行分析,做出了明智的决定.
- 洞察力影响了评估所选三个信号的决策,其中两个由常规健康数据支持. 标准化和数据治理被认为是未来发展的关键.
结论:
- 从分布式网络分析常规健康数据是可行的,以支持在时间限制下信号验证和优先级.
- 这些分析可以有效地告知药监决策.
- 早期整合的成本效益需要进一步研究.
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