The Framework for Age-Friendly Voice Medical Information Service Platform Based on Field Dynamic Theory

In the context of increasing digitization and aging population, the medical information service platform influences the experience of the elderly during medical treatment. This study aims to improve the age-friendly medical process by optimizing the AI-driven Voice User Interface (VUI) service platform. By introducing the Field Dynamic Theory, we analyzed the behavior of the elderly in the medical field from a systemic perspective. Through study interviews on medical pain points, the Analytic Hierarchy Process (AHP) is used to calculate the top three weighted needs that urgently need to be addressed. We refined three platform functionalities: efficient interaction guidance, personalized pre-diagnosis and empathetic medical accompaniment. The platform establishes a framework through guided flow, interaction flow, and feedback flow, implemented with using Medical GPT-based Voice User Interface (VUI). This study is applied from online to offline VUI service touchpoints, achieved the linkage from homes to hospitals and from front-end to back-end. This study constructs a AI-driven sustainable iterative medical process service platform to enhance the medical efficiency and experience of the elderly, providing strategies and references for building an age-friendly voice medical information service platform.