A graph-grammar approach to represent causal, temporal and other contexts in an oncological patient record.
The data of a patient undergoing complex diagnostic and therapeutic procedures do not only form a simple chronology of events, but are closely related in many ways. Such data contexts include causal or temporal relationships, they express inconsistencies and revision processes, or describe patient-specific heuristics. The knowledge of data contexts supports the retrospective understanding of the medical decision-making process and is a valuable base for further treatment. Conventional data models usually neglect the problem of context knowledge, or simply use free text which is not processed by the program. In connection with the development of the knowledge-based system THEMPO (Therapy Management in Pediatric Oncology), which supports therapy and monitoring in pediatric oncology, a graph-grammar approach has been used to design and implement a graph-oriented patient model which allows the representation of non-trivial (causal, temporal, etc.) clinical contexts. For context acquisition a mouse-based tool has been developed allowing the physician to specify contexts in a comfortable graphical manner. Furthermore, the retrieval of contexts is realized with graphical tools as well.
Müller
R
R
Institut für Medizinische Statistik und Dokumentation, Universität Mainz, Germany.
Thews
O
O
Rohrbach
C
C
Sergl
M
M
Pommerening
K
K
D016907:Adverse Drug Reaction Reporting Systems; D001185:Artificial Intelligence; D002648:Child; D003196:Computer Graphics; D003661:Decision Support Techniques; D004282:Documentation / Q000379:methods*; D005103:Expert Systems; D006801:Humans; D016247:Information Storage and Retrieval; D016347:Medical Records Systems, Computerized; D009369:Neoplasms / Q000628:therapy*; D012984:Software; D013813:Therapy, Computer-Assisted; D018875:Vocabulary, Controlled