Size demands for outpatient waiting areas in the context of smart healthcare services in China

Smart technology is revolutionizing Chinese healthcare, yet how medical spaces adapt remains underexplored. The size of outpatient waiting areas (OWAs) exemplify this challenge. Although OWA size prediction models exist, the impact of smart healthcare services (SHSs) has not been fully assessed. This study, utilizing field data from 40 Chinese OWAs, confirmed that the smartness levels (quality and adoption levels of SHSs) significantly affect peak waiting numbers in OWA and revealed their influence pathways. On this basis, existing models were refined through two key modifications: converting static constants (“peak ratio” and “waiting ratio”) into the radial basis function (RBF) neural network-driven dynamic parameter, and recalibrating the recommended value of constant “per-capita area” for modern OWAs via empirical data with membership function fitting. This enhanced model, accepting inputs including smartness level, daily outpatient volume, and consultation duration, demonstrates superior adaptability to evolving SHS implementations and inter-departmental variability compared to existing single-variable models. This study highlights the need to align SHS development with spatial optimization in outpatient constructions, offering tools to precisely allocate OWA size and a transferable framework for similar medical space planning. It also provides foundational insights and data for establishing tailored hospital design standards matching SHS development.