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Methodological framework for evaluating clinical processes: A cognitive informatics perspective
Affiliation:1. Department of Family Medicine, College of Medicine, University of Illinois at Chicago, Chicago, IL, United States;2. Department of Biomedical and Health Information Sciences, College of Applied Health Sciences, University of Illinois at Chicago, Chicago, IL, United States;3. Center for Cognitive Studies in Medicine and Public Health, The New York Academy of Medicine, New York, NY, United States
Abstract:We propose a methodological framework for evaluating clinical cognitive activities in complex real-world environments that provides a guiding framework for characterizing the patterns of activities. This approach, which we refer to as a process-based approach, is particularly relevant to cognitive informatics (CI) research—an interdisciplinary domain utilizing cognitive approaches in the study of computing systems and applications—as it provides new ways for understanding human information processing, interactions, and behaviors. Using this approach involves the identification of a process of interest (e.g., a clinical workflow), and the contributing sequences of activities in that process (e.g., medication ordering). A variety of analytical approaches can then be used to characterize the inherent dependencies and relations within the contributing activities within the considered process. Using examples drawn from our own research and the extant research literature, we describe the theoretical foundations of the process-based approach, relevant practical and pragmatic considerations for using such an approach, and a generic framework for applying this approach for evaluation studies in clinical settings. We also discuss the potential for this approach in future evaluations of interactive clinical systems, given the need for new approaches for evaluation, and significant opportunities for automated, unobtrusive data collection.
Keywords:Cognitive informatics  Interactive clinical systems  Process  Process-based approach  Naturalistic environments  Complexity
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