Interactive AI assistance for predictive control in discharge and transition management
Ensuring optimal and continuous care for patients is a major challenge, particularly in the German healthcare system with its sectoral nature.
Discharge management plays a key role in the process because it is responsible for the continuity of care and communication between the various stakeholders involved.
In the KIAFlex project, researchers are developing an assistance system designed to improve clinical and administrative processes in hospital discharge management. The aim is to use AI to predict the need for follow-up care when patients are admitted to ensure flexible discharge.
Using data collected during diagnosis and treatment, the needs can be adjusted interactively by the staff and semi-automatically by the AI system. The project is also developing a virtual social worker and documentation assistant (chatbot), which takes over proactive communication with relatives and automated documentation. The aim is to enable more flexible transfer processes.
