From decision to shared-decision: Introducing patients' preferences into clinical decision analysis

Lucia Sacchi, Stefania Rubrichi, Carla Rognoni, Silvia Panzarasa, Enea Parimbelli, Andrea Mazzanti, Carlo Napolitano, Silvia G. Priori, Silvana Quaglini

Research output: Contribution to journalArticlepeer-review


Objective: Taking into account patients' preferences has become an essential requirement in health decision-making. Even in evidence-based settings where directions are summarized into clinical practice guidelines, there might exist situations where it is important for the care provider to involve the patient in the decision. In this paper we propose a unified framework to promote the shift from a traditional, physician-centered, clinical decision process to a more personalized, patient-oriented shared decision-making (SDM) environment. Methods: We present the theoretical, technological and architectural aspects of a framework that encapsulates decision models and instruments to elicit patients' preferences into a single tool, thus enabling physicians to exploit evidence-based medicine and shared decision-making in the same encounter. Results: We show the implementation of the framework in a specific case study related to the prevention and management of the risk of thromboembolism in atrial fibrillation. We describe the underlying decision model and how this can be personalized according to patients' preferences. The application of the framework is tested through a pilot clinical evaluation study carried out on 20 patients at the Rehabilitation Cardiology Unit at the IRCCS Fondazione Salvatore Maugeri hospital (Pavia, Italy). The results point out the importance of running personalized decision models, which can substantially differ from models quantified with population coefficients. Conclusions: This study shows that the tool is potentially able to overcome some of the main barriers perceived by physicians in the adoption of SDM. In parallel, the development of the framework increases the involvement of patients in the process of care focusing on the centrality of individual patients.

Original languageEnglish
Pages (from-to)19-28
Number of pages10
JournalArtificial Intelligence in Medicine
Issue number1
Publication statusPublished - Sep 1 2015


  • Atrial fibrillation
  • Decision trees
  • Patient preferences
  • Shared decision-making
  • Utility coefficients

ASJC Scopus subject areas

  • Artificial Intelligence
  • Medicine (miscellaneous)


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