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Comprehensive Analysis of a Medication Dosing Error Related to CPOE: Table 1
Author(s) -
J Horský,
Gilad J. Kuperman,
Vimla L. Patel
Publication year - 2005
Publication title -
journal of the american medical informatics association
Language(s) - English
Resource type - Journals
eISSN - 1527-974X
pISSN - 1067-5027
DOI - 10.1197/jamia.m1740
Subject(s) - usability , computer science , dosing , interdependence , scope (computer science) , process (computing) , interface (matter) , human error , table (database) , user interface , data mining , risk analysis (engineering) , human–computer interaction , medicine , programming language , bubble , maximum bubble pressure method , parallel computing , political science , law , pharmacology
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.

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