Mapping the Evolving AI Preferences and Care Needs in Orthopedic Transitional Care From Hospitals to Home: Cross-Sectional Study
Abstract
Abstract Background Enhanced recovery after surgery protocols have shortened orthopedic hospital stays but have shifted rehabilitation and safety-monitoring tasks to patients and families after discharge. In this study, AI refers to patient-facing digital systems for orthopedic transitional care, including large language model chatbots, computer vision or platform-based monitoring tools, and wearable sensor–enabled systems for education, rehabilitation guidance, motion correction, and risk alerts. However, patient-reported preferences for different AI-supported functions across the hospital-to-home transition remain underexplored. Objective This study aimed to map the evolution of care needs from hospital to home recovery and to identify specific preferences and factors associated with the willingness to use AI systems in orthopedic transitional care. Methods We conducted a multicenter cross-sectional survey among patients recovering from orthopedic surgery in 33 Guangdong hospitals, China. Of the 860 submitted questionnaires, 752 responses were included after prespecified quality control, including exclusion of responses completed in 180 seconds or less based on pilot-informed screening. Participants rated standardized function-based AI descriptions rather than a specific prototype or live tool. The data covered demographic and clinical characteristics, task priorities across care phases, perceived transitional care challenges, and stated willingness to use AI. The survey…
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