Abstract
Clinical practice guidelines (CPGs) play an important role in medical practice, and computerized support to CPGs is now one of the most central areas of research in Artificial Intelligence in medicine. In recent years, many groups have developed different computer-assisted management systems of Computer Interpretable Guidelines (CIGs). From one side, there are several commonalities between different approaches; from the other side, each approach has its own peculiarities and is geared towards the treatment of specific phenomena. In our work, we propose a form of generalization: instead of defining “yet another CIG system”, we propose a META-GLARE, a “meta”-system (or, in other words, a shell) to define new CIG systems. From one side, we try to capture the commonalities, by providing (i) a general tool for the acquisition, consultation and execution of hierarchical directed graphs (representing the control flow of actions in CIGs), parameterized over the types of nodes and of arcs constituting it, and (ii) a library of different elementary components of guidelines nodes (actions) and arcs, in which each type definition involves the specification of how objects of this type can be acquired, consulted and executed. From the other side, we provide generality and flexibility, by allowing free aggregations of such elementary components to define new primitive node and arc types. In this paper, we first propose META-GLARE general architecture and then, for the sake of brevity, we will focus only on the acquisition issue.
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Notes
- 1.
The guideline for ischemic ictus has been developed by Azienda Ospedaliera S. Giovanni Battista in Turin, one of the largest hospitals in Italy.
- 2.
The treatment of versioning is outside the goals of our present work. However, we are planning to face this issue in the future, also taking advantage of the formal approach we already devised [24].
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The research described in this paper has been partially supported by Compagnia San Paolo, within the GINSENG project.
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Terenziani, P., Bottrighi, A., Lovotti, I., Rubrichi, S. (2014). META-GLARE: A Meta-System for Defining Your Own CIG System: Architecture and Acquisition. In: Miksch, S., Riaño, D., ten Teije, A. (eds) Knowledge Representation for Health Care. KR4HC 2014. Lecture Notes in Computer Science(), vol 8903. Springer, Cham. https://doi.org/10.1007/978-3-319-13281-5_7
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