Methods for studying medical device technology and practitioner cognition: The case of user-interface issues with infusion pumps
Purpose : The aims of this study were to investigate how a variety of research methods is commonly employed to study technology and practitioner cognition. User-interface issues with infusion pumps were selected as a case because of its relevance to patient safety. Methods : Starting from a Cognitive Systems Engineering perspective, we developed an Impact Flow Diagram showing the relationship of computer technology, cognition, practitioner behavior, and system failure in the area of medical infusion devices. We subsequently conducted a systematic literature review on user-interface issues with infusion pumps, categorized the studies in terms of methods employed, and noted the usability problems found with particular methods. Next, we assigned usability problems and related methods to the levels in the Impact Flow Diagram. Results : Most study methods used to find user interface issues with infusion pumps focused on observable behavior rather than on how artifacts shape cognition and collaboration. A concerted and theory-driven application of these methods when testing infusion pumps is lacking in the literature. Detailed analysis of one case study provided an illustration of how to apply the Impact Flow Diagram, as well as how the scope of analysis may be broadened to include organizational and regulatory factors. Conclusion : Research methods to uncover use problems with technology may be used in many ways, with many different foci. We advocate the adoption of an Impact Flow Diagram perspective rather than merely focusing on usability issues in isolation. Truly advancing patient safety requires the systematic adoption of a systems perspective viewing people and technology as an ensemble, also in the design of medical device technology. © 2012 Elsevier Inc. All rights reserved.
To reference this document use:
HOI - Human Behaviour & Organisational Innovations
BSS - Behavioural and Societal Sciences
Cognitive Systems Engineering
Journal of Biomedical Informatics, 46 (1), 181-195