Mental models and model mentality
Tasks, errors, and mental models
Human factors in alarm design
Technology in Action
The Vision of Autonomic Computing
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Lost in menuspace: user interactions with complex medical devices
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Guest editorial: human-centered computing in health information systems. Part 1: Analysis and design
Journal of Biomedical Informatics - Special issue: Human-centered computing in health information systems. Part 1: Analysis and design
Hiding in plain sight: what Koppel et al. tell us about healthcare IT
Journal of Biomedical Informatics - Special section: JAMA commentaries
User-designed information tools to support communication and care coordination in a trauma hospital
Journal of Biomedical Informatics
Development and evaluation of nursing user interface screens using multiple methods
Journal of Biomedical Informatics
"Remain Faithful to the Earth!"*: Reporting Experiences of Artifact-Centered Design in Healthcare
Computer Supported Cooperative Work
Understanding infusion administration in the ICU through Distributed Cognition
Journal of Biomedical Informatics
Distributed cognition for evaluating healthcare technology
BCS-HCI '11 Proceedings of the 25th BCS Conference on Human-Computer Interaction
Resource management activities in healthcare information systems: A process perspective
Information Systems Frontiers
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Healthcare demonstrates the same properties of risk, complexity, uncertainty, dynamic change, and time-pressure as other high hazard sectors including aviation, nuclear power generation, the military, and transportation. Unlike those sectors, healthcare has particular traits that make it unique such as wide variability, ad hoc configuration, evanescence, resource constraints, and governmental and professional regulation. While healthcare's blunt (management) end is more easily understood, the sharp (operator) end is more difficult to research the closer one gets to the sharp end's point. Understanding sharp end practice and cognitive work can improve computer-based systems resilience, which is the ability to perform despite change and challenges. Research into actual practice at the sharp end of healthcare will provide the basis to understand how IT can support clinical practice. That understanding can be used to develop computer-based systems that will act as team players, able to support both individual and distributed cognitive work at healthcare's sharp end.