Conference Paper

An Analytical Approach for Predicting and Identifying Use Error and Usability Problem.

DOI: 10.1007/978-3-540-76805-0_38 Conference: HCI and Usability for Medicine and Health Care, Third Symposium of the Workgroup Human-Computer Interaction and Usability Engineering of the Austrian Computer Society, USAB 2007, Graz, Austria, November, 22, 2007, Proceedings
Source: DBLP

ABSTRACT In health care, the use of technical equipment plays a central part. To achieve high patient safety and efficient use, it
is important to avoid use errors and usability problems when handling the medical equipment. This can be achieved by performing
different types of usability evaluations on prototypes during the product development process of medical equipment. This paper
describes an analytical approach for predicting and identifying use error and usability problems. The approach consists of
four phases; (1) Definition of Evaluation, (2) System Description, (3) Interaction Analysis, and (4) Result Compilation and
Reflection. The approach is based on the methods Hierarchical Task Analysis (HTA), Enhanced Cognitive Walkthrough (ECW) and
Predictive Use Error Analysis (PUEA).

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    ABSTRACT: To avoid use errors when handling medical equipment, it is important to develop products with a high degree of usability. This can be achieved by performing usability evaluations in the product development process to detect and mitigate potential usability problems. A commonly used method is cognitive walkthrough (CW), but this method shows three weaknesses: poor high-level perspective, insufficient categorisation of detected usability problems, and difficulties in overviewing the analytical results. This paper presents a further development of CW with the aim of overcoming its weaknesses. The new method is called enhanced cognitive walkthrough (ECW). ECW is a proactive analytical method for analysis of potential usability problems. The ECW method has been employed to evaluate user interface designs of medical equipment such as home-care ventilators, infusion pumps, dialysis machines, and insulin pumps. The method has proved capable of identifying several potential use problems in designs.
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