Patient expectations of AI-based computerized clinical decision support system for improving continuity of care after hospitalization: a cross-sectional study on rehabilitation after total hip or knee replacement for osteoarthritis, with pilot questionnaire - Federico Pennestrì; Catia Pelosi; Annalisa Orenti; Petros Patias; Charalampos Georgiadis; Themistocles Roustanis; Giuseppe Banfi; The Prepare Project Group (Recenti Progressi in Medicina, 2026)
Summary. Continuity of care after hospital discharge is a common issue for patients who underwent major surgery. Computerized clinical Decision Support Systems (CDSSs) can help physicians stratify patients based on clinical and social characteristics, make predictions about relevant care milestones and outcomes, and make personalized decisions as early as possible, including safe discharge planning, based on timely activation of the relevant services. To enhance the clinical uptake and effectiveness of these technologies, it is crucial to determine whether patients feel that their personal priorities for their health, recovery and discharge are taken into account. However, there is a significant gap in empirical research regarding patient perspectives on CDSS utilization. As a part of the PREPARE Rehab Project, a) a CDSS to support continuity of care after hospital discharge, and b) two questionnaires investigating physicians’ and patients’ expectations towards its use, are being developed by a group of researchers, clinicians, computer scientists and technicians. This brief report describes how a pilot questionnaire on patient expectations of AI-based CDSS was developed, administered and analyzed in a musculoskeletal research hospital, based on a pilot population of twenty patients, as a part of the nine clinical partners involved in whole project. These preliminary results show a degree of consistency between answers, confirming some hypotheses from the few literature available. The results are discussed in light of expert clinician insight and limitations to overcome. These results provide empirical background to fine-tune a final version of a patient questionnaire, and address CDSS improvements before introduction into routine clinical use.