A computerized method for identifying incidents associated with adverse drug events in outpatients
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- 作者：Honigman ; Benjamin ; Light ; Patrice ; Pulling ; Russel M. ; Bates ; David W.
- 关键词：Electronic medical record ; Data mining ; Medical lexicon ; Adverse drug events ; Outpatients
- 刊名：International Journal of Medical Informatics
- 出版年：2001
- 出版时间：April, 2001
- 年：2001
- 卷：61
- 期：1
- 页码：21-32
- 全文大小：635 K
文摘
Introduction: 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. Objective: 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. Methods: One year of information from the outpatient electronic medical record (EMR) at one hospital and its clinics was reviewed. Altogether, 23 064 patients and 88 514 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. Conclusion: 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.