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.