Grant, Natalie VictoriaBejan, AlexanderKunze, ChristopheBurkhardt, Heinrich2024-10-082024-10-082024https://dl.gi.de/handle/20.500.12116/44895Ensuring optimal care post-hospitalization is a significant challenge for healthcare systems. Discharge management (DM) is crucial for continuing care, yet process-related issues persist. Artificial Intelligence (AI)-supported systems may address DM-related issues, but research on the needs of hospital staff is limited. This paper presents results from the first phase of a multicenter project aimed at developing an AI-supported system to predict aftercare needs and improve DM processes in German hospitals. We conducted an exploratory needs analysis using participatory methods (workshops, questionnaires and interviews) and defined suitable use cases. We observed a high level of interest in the proposed AI-supported system. However, participants expressed doubts about the effective implementation due to the current state of their hospital’s digital infrastructure. The resulting use cases focused on the reception, processing and interpretation of plausible" data. These outcomes form the basis for the further research and development with hospital staff and external developers."enAI-supported SystemsArtificial IntelligenceDischarge ManagementParticipatory DesignText/Conference Paper10.1145/3670653.3677483