Center for Medical Informatics, Yale University School of Medicine, New Haven, CT 06511, USA.
J Am Med Inform Assoc. 2010 Nov-Dec;17(6):671-4. doi: 10.1136/jamia.2010.008607.
The author discusses the challenges of pharmacovigilance using electronic medical record and claims data. Use of ICD-9 encoded data has low sensitivity for detection of adverse drug events (ADEs), because it requires that an ADE escalate to major-complaint level before it can be identified, and because clinical symptomatology is relatively under-represented in ICD-9. A more appropriate vocabulary for ADE identification, SNOMED CT, awaits wider deployment. The narrative-text record of progress notes can potentially be used for more sensitive ADE detection. More effective surveillance will require the ability to grade ADEs by severity. Finally, access to online drug information that includes both a reliable hierarchy of drug families as well as structured information on existing ADEs can improve the focus and predictive ability of surveillance efforts.
作者讨论了使用电子病历和理赔数据进行药物警戒所面临的挑战。使用 ICD-9 编码数据对药物不良事件(ADE)的检测灵敏度较低,因为它要求 ADE 上升到主要投诉级别才能被识别,而且 ICD-9 中相对较少地体现了临床症状。更适合 ADE 识别的词汇表 SNOMED CT 尚待更广泛的部署。进度记录的叙述文本记录有可能用于更敏感的 ADE 检测。更有效的监测需要能够根据严重程度对 ADE 进行分级。最后,访问包括可靠的药物家族层次结构以及现有 ADE 结构化信息的在线药物信息可以提高监测工作的重点和预测能力。