Horsky Jan, Kuperman Gilad J, Patel Vimla L
Laboratory of Decision Making and Cognition, Department of Biomedical Informatics, Columbia University, 622 West 168th Street, Vanderbilt Clinic, 5th Floor, New York, NY 10032-3720, USA.
J Am Med Inform Assoc. 2005 Jul-Aug;12(4):377-82. doi: 10.1197/jamia.M1740. Epub 2005 Mar 31.
This case study of a serious medication error demonstrates the necessity of a comprehensive methodology for the analysis of failures in interaction between humans and information systems. The authors used a novel approach to analyze a dosing error related to computer-based ordering of potassium chloride (KCl). The method included a chronological reconstruction of events and their interdependencies from provider order entry usage logs, semistructured interviews with involved clinicians, and interface usability inspection of the ordering system. Information collected from all sources was compared and evaluated to understand how the error evolved and propagated through the system. In this case, the error was the product of faults in interaction among human and system agents that methods limited in scope to their distinct analytical domains would not identify. The authors characterized errors in several converging aspects of the drug ordering process: confusing on-screen laboratory results review, system usability difficulties, user training problems, and suboptimal clinical system safeguards that all contributed to a serious dosing error. The results of the authors' analysis were used to formulate specific recommendations for interface layout and functionality modifications, suggest new user alerts, propose changes to user training, and address error-prone steps of the KCl ordering process to reduce the risk of future medication dosing errors.
这个关于严重用药错误的案例研究表明，需要一种全面的方法来分析人与信息系统交互中的故障。作者采用了一种新颖的方法来分析与基于计算机的氯化钾（KCl）医嘱相关的剂量错误。该方法包括根据医嘱录入使用日志按时间顺序重建事件及其相互依存关系，对相关临床医生进行半结构化访谈，以及对医嘱系统进行界面可用性检查。对从所有来源收集的信息进行比较和评估，以了解错误是如何在系统中演变和传播的。在这个案例中，该错误是人和系统主体之间交互故障的产物，而范围局限于各自不同分析领域的方法无法识别这些故障。作者从药物医嘱流程的几个趋同方面对错误进行了描述：屏幕上实验室结果审查混乱、系统可用性困难、用户培训问题以及临床系统保障措施欠佳，所有这些都导致了严重的剂量错误。作者的分析结果被用于制定有关界面布局和功能修改的具体建议，提出新的用户警报，建议改变用户培训方式，并解决KCl医嘱流程中容易出错的步骤，以降低未来用药剂量错误的风险。
