ProKIP
Process support and development for the use of AI in nursing care
The overall goal of the ProKIP project is to support the integration of AI solutions into nursing practice. For this purpose, the project designs a participatory and interdisciplinary, iterative monitoring and networking process for collaborative projects of the funding program "Making repositories and AI systems usable in everyday nursing care". In addition, success factors for research and development and the use of AI in nursing are explored, so that a contribution is made to the scientific and practical foundation of the topic of AI in nursing.
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Motivation
The use of artificial intelligence (AI), algorithms that learn based on data to enable intelligent, goal-oriented actions, represents a promising solution to the myriad challenges in the nursing context. AI solutions in the form of machine learning can support nursing clinical and case-based decision making, identify patterns and risks - such as in the care process or health status - through algorithm-guided data analysis, and make administrative processes more efficient. Despite increasing scientific findings and publications on the use of AI in care, there has been a lack of insights into the practical relevance and suitability of AI systems in care - especially with regard to setting-specific requirements or needs in hospitals, outpatient and inpatient long-term care, rehabilitation facilities and prevention. The results of the exploratory project AI in care, which was carried out in 2020, show that there are a variety of challenges for the implementation of research projects in the topic area, but also design opportunities, which can contribute to the success and project success, but whose interaction and interaction has not yet been conclusively investigated.
Innovations and perspectives
The project provides innovative support to existing funding projects in the funding line in the form of labs and methods, tools, frameworks and theories developed and offered therein, and on the other hand develops theoretically-founded explanations and implementation frameworks for AI projects in nursing. A key milestone is the creation of a scientifically based AI readiness assessment.
