Personalized Fall Risk Assessment Tool by using the Data Treasure contained in Mobile Electronic Patient Records

This work presents a novel approach for combining multiple Electronic Patient Records (EPRs) to a self-learning fall risk assessment tool. This tool is used by a new type of home-visiting nurses to track the fall risk of their patients. In order to provide personalized healthcare for elderly people, we combine multiple EPRs using an agent-based architecture, where each patient is represented by an associated agent. The patient agents are enabled to negotiate about possible fallrisk indicators recognized in the specific patient population under care. We use distributed information fusion and opinion aggregation techniques to elaborate new fall-risk indicators and in consequence to adapt the fall risk assessment tool.