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AMIA Annu Symp Proc. 2003; 2003: 165–169.
PMCID: PMC1479951
An Extended Hierarchical Task Analysis for Error Prediction in Medical Devices
Phillip H. Chung,1,2 Jiajie Zhang, PhD,1 Todd R. Johnson, PhD,1 and Vimla L. Patel, PhD3
1 School of Health Information Sciences, University of Texas, Houston TX
2 Department of Psychology, Rice University, Houston TX
3 Department of Medical Informatics, Columbia University, New York NY
Abstract
This paper introduces an extended hierarchical task analysis (HTA) methodology devised to evaluate and compare user interfaces on volumetric infusion pumps. The pumps were studied along the dimensions of overall usability and propensity for generating human error. With HTA as our framework, we analyzed six pumps on a variety of common tasks using Norman’s Action theory. The introduced method of evaluation divides the problem space between the external world of the device interface and the user’s internal cognitive world, allowing for predictions of potential user errors at the human-device level. In this paper, one detailed analysis is provided as an example, comparing two different pumps on two separate tasks. The results demonstrate the inherent variation, often the cause of usage errors, found with infusion pumps being used in hospitals today. The reported methodology is a useful tool for evaluating human performance and predicting potential user errors with infusion pumps and other simple medical devices.
Articles from AMIA Annual Symposium Proceedings are provided here courtesy of
American Medical Informatics Association