Clinical Pathways (CPs) are evidence-based recommendation for treating a diagnosis and an effective instrument to decrease undesired practice variability and improve clinician performance. Deviations from CPs might just as well reduce quality of care. Moreover they can be associated to possible adverse events. In this perspective, we developed and tested a system for comparing a patient trajectory (PT) with the corresponding CP in order to recognize significant variations. To measure adherence, a Clinical Pathway Deviation Index (CPDI) was constructed as the weighted-sum of five indicators. To build the indicators three different tools for CPs modeling have been tested. Only two of them proved suitable for our system. A preliminary analysis has been carried out using data of 24 real PTs. The aim of this paper is to present the system and to characterize CPDI performances.
CPDI: an Index for Measuring Deviations in Clinical Pathways / Zema, Maddalena; Rosati, Samanta; Duran Carvajal, Jonathan Eliecer; Balestra, Gabriella. - ELETTRONICO. - (2015), pp. 1385-1388. (Intervento presentato al convegno 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC ’15) tenutosi a Milano, Italy nel 26-29 August, 2015) [10.1109/EMBC.2015.7318627].
CPDI: an Index for Measuring Deviations in Clinical Pathways
ZEMA, MADDALENA;ROSATI, SAMANTA;BALESTRA, Gabriella
2015
Abstract
Clinical Pathways (CPs) are evidence-based recommendation for treating a diagnosis and an effective instrument to decrease undesired practice variability and improve clinician performance. Deviations from CPs might just as well reduce quality of care. Moreover they can be associated to possible adverse events. In this perspective, we developed and tested a system for comparing a patient trajectory (PT) with the corresponding CP in order to recognize significant variations. To measure adherence, a Clinical Pathway Deviation Index (CPDI) was constructed as the weighted-sum of five indicators. To build the indicators three different tools for CPs modeling have been tested. Only two of them proved suitable for our system. A preliminary analysis has been carried out using data of 24 real PTs. The aim of this paper is to present the system and to characterize CPDI performances.Pubblicazioni consigliate
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https://hdl.handle.net/11583/2624571
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