Abstract
The development of software tools supporting physicians in the treatment of comorbid patients is a challenging goal and a “hot topic” in medical informatics and artificial intelligence. Computer interpretable guidelines (CIGs) are consolidated tools to support physicians with evidence-based recommendations in the treatment of patients affected by a specific disease. However, the application of two or more CIGs on comorbid patients is critical, since dangerous interactions between actions from different CIGs may arise. GLARE-SSCPM is the first tool supporting, in an integrated way, the knowledge-based detection of interactions, the management of the interactions, and the final “merge” of (part of) the CIGs operating on the patient. GLARE-SSCPM is characterized by being very supportive to physicians, providing them support for focusing, interaction detection, and for a “hypothesize and test” approach to manage the detected interactions. To achieve such goals, it provides advanced artificial intelligence techniques. Preliminary tests in the educational context, within the RoPHS project, have provided encouraging results.
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