Honigman B, Light P, Pulling R M, Bates D W
Division of Emergency Medicine, University of Colorado School of Medicine, 4200 East 9th Avenue, #B-215, Denver, CO 80262, USA.
Int J Med Inform. 2001 Apr;61(1):21-32. doi: 10.1016/s1386-5056(00)00131-3.
In inpatients, computer monitors have been used to improve the detection of adverse drug events (ADEs). However, similar programs have not been available in outpatients.
To describe an approach for detecting incidents suggesting that an ADE may have occurred in outpatients by adapting methods from inpatient computer monitoring and developing terminology searches of electronic medical records.
One year of information from the outpatient electronic medical record (EMR) at one hospital and its clinics was reviewed. Altogether, 23064 patients and 88514 visits were identified. Patient demographics, medical problem lists, ICD-9 claims, patient allergies, medication history and all clinic visit notes were extracted and merged. We then searched for incidents suggesting that an ADE might be present using four methods: ICD-9 claims, new allergies, computer rules linking laboratory data to known medication exposures, and a medical terminology lexicon (M2D2). In this report, we describe how these search methods were developed to allow for ADE identification.
The ability to carry out such quality-related work is an example of the benefits of the outpatient EMR that may not be apparent to those institutions considering adopting it.
在住院患者中,计算机监测已被用于改善不良药物事件(ADEs)的检测。然而,门诊患者中尚未有类似的项目。
通过采用住院患者计算机监测方法并开发电子病历术语搜索,描述一种检测门诊患者中可能发生ADEs事件的方法。
回顾了一家医院及其诊所一年的门诊电子病历(EMR)信息。共识别出23064名患者和88514次就诊。提取并合并了患者人口统计学信息、医疗问题清单、ICD-9编码、患者过敏史、用药史以及所有门诊就诊记录。然后,我们使用四种方法搜索可能存在ADEs的事件:ICD-9编码、新出现的过敏反应、将实验室数据与已知药物暴露相关联的计算机规则以及医学术语词典(M2D2)。在本报告中,我们描述了如何开发这些搜索方法以实现ADEs的识别。
开展此类质量相关工作的能力是门诊EMR优势的一个例证,对于那些考虑采用它的机构来说可能并不明显。