An Extended Hierarchical Task Analysis for Error Prediction in Medical Devices

Authors

Phillip H. Chung, School of Health Information Sciences, University of Texas, Houston TX; Department of Psychology, Rice University, Houston TX
Jiajie Zhang, School of Health Information Sciences, University of Texas, Houston TX
Todd R. Johnson, School of Health Information Sciences, University of Texas, Houston TX
Vimla L. Patel, Department of Medical Informatics, Columbia University, New York NY

Publication Date

2003

Journal

AMIA Annu Symp Proc. 2003; 2003: 165–169.

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.

Keywords

Infusion Pumps, Medical Errors/prevention and control, Task Performance and Analysis

Comments

PMCID: PMC1479951