Warnecke, MarenMarenWarneckeHolle, DanielaDanielaHolleBurmann, AnjaAnjaBurmann2024-09-252024-09-252023https://publica.fraunhofer.de/handle/publica/47565710.1515/cdbme-2023-10852-s2.0-85174242439The documentation landscape for nursing care data in Germany is predominantly heterogeneous and unstructured. Therefore, insightful methods such as Artificial Intelligence (AI) are difficult to implement. We propose a stepwiseapproach that identifies relevant information from nursing theory and practice and maps it to a standardized nursing core data set to enable data-based improvement of nursing care. This can be used for various use-cases in care, such as risk detection and prevention in diverse care contexts. Many care processes can benefit of a cross-facility and standardized repository and associated applications. We propose an approach that enables the use of AI while leveraging consensus and evidenced-based expert knowledge from nursing science.enopen accesscare data setcore data setcross-facility data setrisk detectionjournal article