Reference: Patel VL, Arocha JF, DiermeierM, Shortliffe EH, and Greenes R, Methods of Cognitive Analysis to Support the Design and Evaluation of Biomedical Systems: The Case of Clinical Practice Guidelines. Journal of Biomedical Informatics 34(1)52-66, 2001.
Abstract: This article provides a theoretical and methodological
framework for the use of cognitive analysis to support the representation
of biomedical knowledge and the design of clinical systems, using clinical-practice
guidelines (CPGs) as an example. We propose that propositional and semantic
analyses, when used as part of the system-development process, can improve
the validity, usability, and comprehension of the resulting biomedical
applications. The framework we propose is based on a large body of research
on the study of how people mentally represent information and subsequently
use it for problem solving. This research encompasses many areas of psychology,
but the more important ones are the study of memory and the study of comprehension.
Of particular relevance is research devoted to investigating the comprehension
and memory of language, expressed verbally or in text. In addition, research
on how contextual variables affect performance is informative because these
psychological processes are influenced by situational variables (e.g.,
setting, culture). One important factor limiting the acceptance and use
of clinical-practice guidelines (CPGs) may be the mismatch between a guideline’s
recommended actions and the physician–user’s mental models of what seems
appropriate in a given case. Furthermore, CPGs can be semantically complex,
often composed of elaborate collections of prescribed procedures with logical
gaps or contradictions that can promote ambiguity and hence frustration
on the part of those who attempt to use them. An improved understanding
of the semantics and structure of CPGs may help to improve such matching,
and ultimately the comprehensibility and usability of CPGs. Cognitive methods
of analysis can help guideline designers and system builders throughout
the development process, from the conceptual design of a computer-based
system to its implementation phases. By studying how guideline creators
and developers represent guidelines, both mentally and in text, and how
end-users understand and make decisions with such guidelines, we can inform
the development of technologies that seek to improve the match between
the representations of experts and practitioners. We urge informaticians
to recognize the potential relevance of cognitive analysis methods and
to begin more
extensive experimentation with the their use in biomedical informatics
research.
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