DaDriv-StAC

DaDriv-StAC develops and tests a digital platform for data-driven decision support in post-stroke care. A stroke is often not a single acute event, but the beginning of a long-term care process. Many patients need continuous treatment, rehabilitation and monitoring to reduce the risk of another stroke. Care needs to also address long-term impairments such as mobility limitations, speech problems, depression, anxiety or spasticity. This involves several sectors, including acute hospitals, rehabilitation centres, general practitioners and specialist practices, among others.

Today, relevant information is often distributed across different providers and IT systems. As a result, deviations from the recommended care pathway may not always be detected early enough. DaDriv-StAC addresses this gap by combining patient data, clinical recommendations and AI-based analysis in a virtual medical twin. This twin represents the individual patient journey and helps compare the planned care pathway with the actual course of treatment.

Work has focused on defining clinical and technical requirements, outlining the system architecture and preparing the concept for virtual medical twins in stroke aftercare. Initial work also covers data models, synthetic data, analysis methods and decision-support functions. In parallel, ethical, regulatory and practical questions for later testing are being clarified. The main expected results are a functional platform prototype, decision-support components for clinicians, suitable user interfaces and a feasibility study to assess the concept in a real care setting.