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Could clustering of comorbidities be useful for better defining the internal medicine patients’ complexity?

Flavio Tangianu, Paola Gnerre, Fabrizio Colombo, Roberto Frediani, Giuliano Pinna, Franco Berti, Giovanni Mathieu, Micaela La Regina, Francesco Orlandini, Antonino Mazzone, Clelia Canale, Daniele Borioni, Roberto Nardi
  • Flavio Tangianu
    Internal Medicine, S. Martino Hospital, Oristano, Italy
  • Paola Gnerre
    Internal Medicine, San Paolo Hospital, Savona, Italy
  • Fabrizio Colombo
    Internal Medicine, Niguarda Ca’ Granda Hospital, Milano, Italy
  • Roberto Frediani
    Internal Medicine, Maggiore Hospital, Chieri (TO), Italy
  • Giuliano Pinna
    Internal Medicine, Cardinal Massaia Hospital, Asti, Italy
  • Franco Berti
    Internal Medicine 2 Department, S. Camillo Forlanini Hospital, Roma, Italy
  • Giovanni Mathieu
    Internal Medicine, E. Agnelli Hospital, Pinerolo (TO), Italy
  • Micaela La Regina
    Internal Medicine, Clinical Risk Manager, La Spezia, Italy
  • Francesco Orlandini
    Health Director, ASL 4 Regione Liguria, Italy
  • Antonino Mazzone
    Medical Department, Internal Medicine, ASST Ovest-Milanese, Legnano (MI), Italy
  • Clelia Canale
    Internal Medicine, S.S. Annunziata Hospital, Savigliano (CN), Italy
  • Daniele Borioni
    Internal Medicine, Maggiore Hospital, Bologna, Italy

Abstract

Internal medicine patients are mostly elderly with multiple comorbidities, usually chronic. The high prevalence of comorbidity and multimorbidity has a significant impact on both positive responses to treatment and the occurrence of adverse events. Clustering is the process of nosography grouping into meaningful associations with some index disease, so that the objects within a cluster have high similarity in comparison with one another. In the decision-making process it is imperative that, in addition to understanding the immediate clinical problems, we are able to explicit all the contextual factors that have to be taken into account for the best outcome of care. Cluster analysis could be leveraged in developing better interventions targeted to improve health outcomes in subgroups of patients.

Keywords

Internal medicine patients; multi/comorbidity; complexity; cluster analysis.

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Submitted: 2017-10-20 15:24:55
Published: 2018-06-20 12:31:20
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Copyright (c) 2018 Flavio Tangianu, Paola Gnerre, Fabrizio Colombo, Roberto Frediani, Giuliano Pinna, Franco Berti, Giovanni Mathieu, Micaela La Regina, Francesco Orlandini, Antonino Mazzone, Clelia Canale, Daniele Borioni, Roberto Nardi

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