在大流行期间加强基于自发报告的信号检测,使用电子健康记录中的病例使用自然语言处理工具
W van der Weg1, G von Kreijfelt1, L Davidson2
1The Netherlands Pharmacovigilance Centre Lareb, 's-Hertogenbosch, the Netherlands; Department of Clinical Pharmacology and Toxicology, Leiden University Medical Centre, Leiden, the Netherlands.
Vaccine
|July 27, 2025
概括
电子健康记录不良事件 (EHR-AE) 搜索增强了COVID-19疫苗安全信号的检测. 这种方法确定了额外的不良药物反应病例,可能会将信号发现速度加速至多18个月.
科学领域:
- 药物监督 药物监督 药物监督
- 疫苗安全监测 疫苗安全监测
- 医疗信息学 医疗信息学
背景情况:
- 随着COVID-19疫苗的快速发展,潜在的不良药物反应 (ADRs) 需要在授权后持续监测.
- 自发报告系统 (SRS) 对于ADR检测至关重要,但依赖于自愿报告,造成局限性.
- 电子健康记录 (EHR) 提供了一个补充数据源,以加强检测疫苗相关的不良反应.
研究的目的:
- 评估电子健康记录不良事件 (EHR-AE) 搜索方法在检测COVID-19疫苗潜在的不良反应方面的附加值.
- 通过将EHR数据与自发报告相结合,加强和加快安全信号检测.
主要方法:
- 开发并应用了使用自然语言处理 (NLP) 和文本挖掘功能的EHR-AE搜索方法.
- 在荷兰两家医院的EHR中对潜在的COVID-19疫苗ADR进行了有针对性的搜索.
- 分析识别的病例与自发报告一起用于安全信号检测.
主要成果:
- 13次搜索确定了6个协会的41个潜在的ADR病例,报告给Lareb.
- 这些病例有助于检测COVID-19疫苗的两个安全信号.
- 通过EHR-AE方法,有可能在18个月和2个月前检测到这些信号.
结论:
- EHR-AE搜索方法有效地加强和加速检测与COVID-19疫苗接种相关的潜在副作用.
- 建议在更多医院进行进一步的研究,以充分评估该方法的附加值和适用性.
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