加拿大提高药物不良反应数据质量:用于药物名称标准化和缩的高精度管道
Niaz Chalabianloo1,2,3, Sheikh S Abdullah2,3,4,5, Mohammad Ali Omrani1
1Department of Physiology and Pharmacology, Western University, London, Ontario, Canada.
PloS one
|September 25, 2025
概括
我们开发了一个自动化管道,在加拿大药物不良反应数据库中标准化药物名称. 这提高了数据质量,并加强了关键药物安全信号的检测.
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
- 在医疗保健中的自然语言处理.
背景情况:
- 加拿大警不良反应数据库因药物命名的异质性而受到影响,这限制了其药物监测实用性.
- 大约36.8%的独特药物名称变体缺乏活性成分映射,造成了显著的数据质量差距.
- 这种数据缺口可能会掩盖关键的药物不良反应 (ADR) 信号,阻碍有效的药物安全监测.
研究的目的:
- 开发,验证和发布一个高精度的自动化管道,用于标准化和丰富药物名称.
- 为解决加拿大国家ADR数据库中因药物命名体系不一致而造成的关键数据质量差距.
- 提高药物不良反应信号检测的灵敏度和可靠性.
主要方法:
- 使用级联匹配策略开发了一个自动化管道.
- 利用RxNorm和观察健康数据科学和信息学 (OHDSI) 词汇进行标准化.
- 使用RxNav API进行与活性成分和解剖治疗化学品 (ATC) 分类的丰富.
- 通过两位独立专家对200个案例的严格评估,验证了管道的准确性.
主要成果:
- 该管道成功标准化了46,585种独特药物名称中的94.5%.
- 专家验证证实了高可靠性,精度为98.02%,特异性为97.22%.
- 标准化在案例研究中揭示了以前无法检测到的安全信号,如梅萨拉明和喘息.
结论:
- 开发的管道有效地解决了加拿大国家ADR数据库中的药物名称异质性.
- 标准化提高了数据质量,提高了ADR信号检测灵敏度,并促进了全球数据互操作性.
- 该公开可用的工具加强了加拿大和国际上对药物安全的监督.
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