A knowledge-based, concept-oriented view generation system for clinical data.
Information overload is a well-known problem for clinicians who must review large amounts of data in patient records. Concept-oriented views, which organize patient data around clinical concepts such as diagnostic strategies and therapeutic goals, may offer a solution to the problem of information overload. However, although concept-oriented views are desirable, they are difficult to create and maintain. We have developed a general-purpose, knowledge-based approach to the generation of concept-oriented views and have developed a system to test our approach. The system creates concept-oriented views through automated identification of relevant patient data. The knowledge in the system is represented by both a semantic network and rules. The key relevant data identification function is accomplished by a rule-based traversal of the semantic network. This paper focuses on the design and implementation of the system; an evaluation of the system is reported separately.
Zeng
Q
Q
Decision Systems Group, Harvard Medical School, Brigham and Women's Hospital, 75 Francis Street, Boston, MA 02115, USA. Qzeng@dsg.harvard.edu
Cimino
J J
JJ
D001185:Artificial Intelligence; D019295:Computational Biology; D003196:Computer Graphics; D003199:Computer Systems; D003627:Data Interpretation, Statistical; D001330:Electronic Data Processing; D006801:Humans; D007257:Information Theory; D016347:Medical Records Systems, Computerized