Temporal similarity measures for querying clinical workflows

• Authors: Carlo Combi;Matteo Gozzi;Barbara Oliboni;Jose M. Juarez;Roque Marin
• Venue: Artificial Intelligence in Medicine
• Year: 2009

Objective: In this paper, we extend a preliminary proposal and discuss in a deeper and more formal way an approach to evaluate temporal similarity between clinical workflow cases (i.e., executions of clinical processes). More precisely, we focus on (i) the representation of clinical processes by using a temporal conceptual workflow model; (ii) the definition of ad hoc temporal constraint networks to formally represent clinical workflow cases; (iii) the definition of temporal similarity for clinical workflow cases based on the comparison of temporal constraint networks; (iv) the management of the similarity of clinical processes related to the Italian guideline for stroke prevention and management (SPREAD). Background: Clinical processes are composed by clinical activities to be done by given actors in a given order satisfying given temporal constraints. This description means that clinical processes can be seen as organizational processes, and modeled by workflow schemata. When a workflow schema represents a clinical process, its cases represent different instances derived from dealing with different patients in different situations. With respect to all the cases related to a workflow schema, each clinical case can be different with respect to its structure and to its temporal aspects. Clinical cases can be stored in clinical databases and information retrieval can be done evaluating the similarity between workflow cases. Methodology: We first describe a possible approach to the conceptual modeling of a clinical process, by using a temporally extended workflow model. Then, we define how a workflow case can be represented as a set of activities, and show how to express them through temporal constraint networks. Once we have built temporal constraint networks related to the cases to compare, we propose a similarity function able to evaluate the differences between the considered cases with respect to the order and duration of corresponding activities, and with respect to the presence/absence of some activities. Results: In this work, we propose an approach to evaluate temporal similarity between workflow cases. The proposed approach can be used (i) to query clinical databases storing clinical cases representing activities related to the management of different patients in different situations; (ii) to evaluate the quality of the service comparing the similarity between a (possibly synthetic) case, perceived as the good one with respect to a given clinical situation, and the other clinical cases; and (iii) to retrieve a particular class of cases similar to an interesting one.