[RHEUMexpert: a documentation and expert system for rheumatic diseases]

A computer assisted documentation of signs and findings in rheumatic diseases is described. This documentation was developed by the Austrian Society for Rheumatology and thought to be a minimal standard for the use by general practitioners. In addition, a knowledge-based basic differential diagnosis support was developed, which differentiates between major groups of rheumatic diseases as inflammatory spine diseases, mechanical or metabolic reasons for spine disorders, inflammatory joint diseases, degenerative or metabolic joint diseases, soft tissue diseases. This presentation describes the results of an evaluation of 75 typical case histories and a second study where 252 case histories were documented retrospectively in this new system. The results of the first showed a pretty good discrimination between the described groups of different diagnoses (sensitivity between 71 and 100 percent for all groups with the exception of metabolic joint diseases, specificity between 75 and 94 percent). The second--retrospective--documentation and diagnostic support showed much weaker results (sensitivity for major groups 74-76 percent). The reasons for the different outcomes are discussed: On the one hand, signs and symptoms from case reports could not be transferred completely in the new documentation, as some findings retrospectively could not be defined sharp enough. On the other hand the study showed, that the sensitivity of well defined disorders as inflammatory joint diseases (exp. rheumatoid arthritis) reaches almost 100 percent, whereas it is as low as 50 percent in some other diseases (e.g. gout) whose characteristic findings and symptoms are suppressed by treatment (drug medication) in many cases. The results show that computer based documentation of rheumatic diseases facilitates the systematized and standardised documentation of patient data. However, a few modifications of the knowledge base as well as the knowledge representation formalisms are necessary to achieve a better performance in differential diagnostic support.