开发电子健康记录,作为兽医药物学和流行病学现实数据的来源
Heather Davies1, Peter-John Noble1, Ivo S Fins1
1Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, United Kingdom.
Frontiers in veterinary science
|April 16, 2025
概括
兽医电子医疗记录可以改善药物安全监测. 分析临床笔记有助于识别不良事件,增强超越自发报告的药物监测.
科学领域:
- 兽医医学 兽医医学 兽医医学
- 药物监督 药物监督 药物监督
- 大数据分析大数据分析.
背景情况:
- 自发报告对于兽药安全至关重要,但往往不完整.
- 大多数兽医不良事件 (AEs) 没有报告,限制了营销后监测.
- 监管机构正在探索大数据,以加强药物监管.
研究的目的:
- 应用兽医电子医疗记录 (EHR) 进行药物流行病学分析.
- 调查非结构化临床叙述对于AE检测的有用性.
- 展示一种新的方法来加强兽医药监督.
主要方法:
- 利用SAVSNET兽医第一意见EHR数据进行概念验证研究.
- 从半结构化治疗数据中确定药物暴露.
- 从非结构化的自由文本临床叙述中提取了AE,使用开发的词典,通过单词矢量化和专家输入进行细化.
主要成果:
- 证明了使用EHR自由文本来识别AE的可行性.
- 为准确的AE识别开发和完善字典.
- 展示了使用EHR数据进行队列研究和风险计算的潜力.
结论:
- 兽医电子健康记录中的非结构化临床叙述可以有效地识别药物流行病学研究的副作用.
- 这种方法显著支持和扩展了传统的自发AE报告.
- 兽医EHR数据提供了一个强大的工具来加强药物安全监测.
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