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Patient experience is a key quality indicator driven by various patient- and provider-related factors in healthcare systems. While several studies provided different insights on patient experience factors, limited research investigates the interdependencies between provider-related factors and patient experience. This study aims to develop a data-driven Bayesian belief network (BBN) model that explores the role and relative importance of provider-related factors influencing patient experience. A BBN model was developed using structural learning algorithms such as tree augmented Naïve Bayes. We used hospital-level aggregated survey data from the British National Health Service to explore the impact of eight provider-related factors on overall patient experience. Moreover, sensitivity and scenario-based analyses were performed on the model. Our results showed that the most influential factors that lead to a high …