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    Clinical decision support tools (DSTs) are computational systems that aid healthcare decision-making. While effective in labs, almost all these systems failed when they moved into clinical practice. Healthcare researchers speculated it is most likely due to a lack of user-centered HCI considerations in the design of these systems. This paper describes a field study investigating how clinicians make a heart pump implant decision with a focus on how to best integrate an intelligent DST into their work process. Our findings reveal a lack of perceived need for and trust of machine intelligence, as well as many barriers to computer use at the point of clinical decision-making. These findings suggest an alternative perspective to the traditional use models, in which clinicians engage with DSTs at the point of making a decision. We identify situations across patients' healthcare trajectories when decision supports would help, and we discuss new forms it might take in these situations.

    Citation

    Qian Yang, John Zimmerman, Aaron Steinfeld, Lisa Carey, James F Antaki. Investigating the Heart Pump Implant Decision Process: Opportunities for Decision Support Tools to Help. ACM transactions on computer-human interaction : a publication of the Association for Computing Machinery. 2016 May;2016:4477-4488


    PMID: 27833397

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