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

• We provide a framework encapsulating patient's preferences elicitation and decision models.
• We define a shared decision-making framework to be used by physicians and patients together.
• We use as a case study the prevention of thromboembolism in atrial fibrillation patients.
• Using personalized utility coefficients allows taking into account the features of the population.
• We show how to integrate shared decision-making into a guideline-based decision support tool.

ObjectiveTaking 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.MethodsWe 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.ResultsWe 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.ConclusionsThis 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.