OBJECTIVES: To investigate the issues raised in applying a preliminary version of the GALEN compositional concept reference (CORE) model to a series of radiographic reports, and to demonstrate that the same underlying concept model could be used in conjunction with both a detailed, fine-grained model of medical records based on that used in the PEN&PAD project and with other more conventional medical-record models. DESIGN: Following analysis and representation of concepts from a set of reports, a single report was taken as a "case study." This report was analyzed in detail in its entirety and represented using each of the medical-record models. RESULTS: The reports were successfully represented within the limits of the study, but a number of significant issues were raised. CONCLUSION: The compositional approach plus the PEN&PAD medical-record model allowed detailed information in the radiographic report to be represented, including information about the inferences and the clinical process. The resulting representation was large, and more compact representations may be necessary for some systems. Alternative encapsulations of the information as might be used in such systems were successfully prepared. The compositional approach avoided many issues that often cause controversy in the design of traditional coding and classification systems, but it raised other issues, including the handling of ambiguity and underspecification, linkage to information not explicitly present in the report, and questions concerning the focus of individual concepts. All work is preliminary and definitive conclusions await further studies and systematic evaluation.

It is argued that current clinical information systems incorporate oversimplistic, prescriptive data models that are not faithful to clinicians' observations. A non-prescriptive descriptive semantic formalism, Structured Meta Knowledge (SMK), which unifies a terminological knowledge base with controlled assertional capabilities with the medical record and supports the semantic control necessitated by such an approach, is proposed. The three-layer model of categories, individuals, and occurrences described is more appropriate to medical applications than the two layers of classes and instances. The application of SMK in predictive data entry is considered.>

An approach that accommodates classical decision theory within a framework of first-order logic with nonmonotonic extensions is described. Among the benefits offered by the approach are the potential: to express qualitative arguments about the desirability of decision options in the absence of probability or utility parameters; to automate techniques for generating decision options; and to initiate, control, and terminate a decision process autonomously. The rationality of a logical decision framework is discussed. A particular benefit of implementing decision procedures in a nonmonotonic logic is that decision systems can adapt automatically as beliefs change, contradictions are encountered, or new knowledge is acquired. A general conclusion is that metaknowledge and metalevel reasoning must be integral elements of a decision theory because of the versatility and operating flexibility they offer.>