Abstract
The widespread adoption and use of Health Information Technology (HIT) in clinical environments has broadly corresponded with several reports of workflow and usability concerns and, in some cases, resulting in sentinel and adverse events. Recent reports from the Institute of Medicine (IOM) and other federal agencies have highlighted the crucial role of rigorous evaluation methods for the design and development of safer HIT. In this chapter, we describe various methods for evaluating HIT: the first section focuses on the usability methods related to the intrinsic aspects of human-computer interaction (HCI), both from an analytic and user-centered perspective; the second section focuses on the usability methods related to the external and situated aspects of human-computer interaction in complex clinical settings, both from a descriptive and contextual perspective of HIT use. Each of the evaluation methods is described with examples from recent empirical studies published in the biomedical informatics research. Finally, we conclude the chapter by highlighting the challenges of conducting HIT evaluation studies, and potential mechanisms for mitigating some of these methodological challenges.
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- 1.
While GOMS (See Sect. 5.2.1.3) is considered a task-analytic approach, we have categorized it as a model-based approach for predictions of task completion times. It is based on a task analytic decomposition of tasks.
Additional Readings
Johnson, C. M., Johnston, D., & Crowle, P. K. (2011). EHR usability toolkit: A background report on usability and electronic health records. Rockville: Agency for Healthcare Research and Quality.
Kushniruk, A. W., & Patel, V. L. (2004). Cognitive and usability engineering methods for the evaluation of clinical information systems. Journal of Biomedical Informatics, 37(1), 56–76.
Preece, J., et al. (1994). Human-computer interaction. Addison-Wesley Longman Ltd.
Shortliffe, E. H., & Patel, V. L. (2011). Generation and formulation of knowledge: Human-intensive techniques. In R. A. Greenes (Ed.), Clinical decision support: The road ahead. Academic.
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Kannampallil, T.G., Abraham, J. (2015). Evaluation of Health Information Technology: Methods, Frameworks and Challenges. In: Patel, V.L., Kannampallil, T.G., Kaufman, D.R. (eds) Cognitive Informatics for Biomedicine. Health Informatics. Springer, Cham. https://doi.org/10.1007/978-3-319-17272-9_5
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