Supporting Multi-level User-driven Detection of Guideline Interactions

Abstract

Clinical practice guidelines are widely used to support physicians, but only on individual pathologies. The treatment of patients affected by multiple diseases (comorbid patients) requires the development of new approaches, supporting physicians in the detection of interactions between guidelines. We propose a new methodology, supporting flexible and physician-driven search and detection. In particular, we provide a flexible and interactive mechanism to navigate guidelines and our ontology of interactions (between drugs, or between actions' goals) at multiple levels of detail, focusing on specific parts of it (e.g., on a specific pair of actions, or of drugs) to look for interactions. We introduce the notion of "navigation tree", as the basic data structure to support multiple-level interaction analysis, and describe navigation and focusing algorithms operating on it. We also introduce a visualization tool that is based on the "navigation tree", and further enhances the user-friendliness of our approach.

Towards an “Operational” Educational Model in Healthcare: Exploiting Computer-Interpretable Guidelines

“…GLARE's architecture is open. In the latest years, several new modules and\or methodologies have been added to cope with automatic resource-based contextualization (ADAPT module, (Terenziani et al, 2004)), temporal reasoning (TR, (Anselma et al, 2006)), decision making support (DECIDE_HELP, (Montani et al, 2005)), model-based verification (VERIFY, (Bottrighi et al, 2010)), and comorbidities (COMORBID, (Piovesan et al, 2014) (Piovesan et al, 2015).…”

Temporal detection and analysis of guideline interactions

“…The output would contain too many elements, most of which would be irrelevant since interactions cannot effectively happen (e.g., in a specific patient some actions cannot be executed, thus all the interactions involving such actions are not relevant). For this reason, in [30] we detailed our mixedinitiative approach to the detection of relevant interactions between CIGs. Our approach allows physicians to navigate CIGs at different levels of abstraction, allowing them to focus on relevant parts of the CIGs and to compare only those actions considered important and potentially interacting.…”

Temporal reasoning techniques for the analysis of interactions in the treatment of comorbid patients

“…The output would contain too many elements, most of which would be irrelevant. For such a reason, in [9] we proposed a tool to support physicians to navigate CIGs at different levels of abstraction, allowing them to focus on relevant parts of the CIGs and to compare only those actions considered important and potentially interacting.…”