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Understanding Human-Computer Interactions in Intensive Care Unit Clinical Communication

Understanding Human-Computer Interactions in Intensive Care Unit Clinical Communication

Saif Khairat, Catherine K. Craven, Yang Gong
Copyright: © 2012 |Volume: 3 |Issue: 1 |Pages: 18
ISSN: 1947-3133|EISSN: 1947-3141|EISBN13: 9781466611214|DOI: 10.4018/jcmam.2012010102
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MLA

Khairat, Saif, et al. "Understanding Human-Computer Interactions in Intensive Care Unit Clinical Communication." IJCMAM vol.3, no.1 2012: pp.14-31. http://doi.org/10.4018/jcmam.2012010102

APA

Khairat, S., Craven, C. K., & Gong, Y. (2012). Understanding Human-Computer Interactions in Intensive Care Unit Clinical Communication. International Journal of Computational Models and Algorithms in Medicine (IJCMAM), 3(1), 14-31. http://doi.org/10.4018/jcmam.2012010102

Chicago

Khairat, Saif, Catherine K. Craven, and Yang Gong. "Understanding Human-Computer Interactions in Intensive Care Unit Clinical Communication," International Journal of Computational Models and Algorithms in Medicine (IJCMAM) 3, no.1: 14-31. http://doi.org/10.4018/jcmam.2012010102

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Abstract

Clinical communication failures are considered the leading cause of medical errors (Bates et al., 1997). The complexity of the clinical culture and the significant variance in training and education levels form a challenge to enhancing communication within the clinical team. In order to improve communication, a comprehensive understanding of the overall communication process in health care is required. In an attempt to further understand clinical communication, the authors conducted a thorough methodology literature review to identify strengths and limitations of previous approaches. Their research proposes a new data collection method to study the clinical communication activities among Intensive Care Unit (ICU) clinical teams with a primary focus on the attending physician. In this paper, the authors present the first ICU communication instrument, they introduce the use of database management system to aid in discovering patterns and associations within our ICU communications data repository, and they present the authors’ Human-Computer Interaction observational study results. The authors have identified and analyzed key Human-Interaction behaviors and tools in the ICU in addition to refining the clinical communication model they previously proposed (Khairat & Gong, 2010b). their goal is to build an exhaustive knowledge representation of the clinical communication process through utilizing an ontological approach.

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