BMC Series blog Why AI-nursing-care projects succeed – or don‘t

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BMC Series blog Why AI-nursing-care projects succeed – or don‘t
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In a BMC_series blog post, Kathrin Seibert and Dominik Domhoff discuss the challenges around complex AI-nursing projects and the barriers to them succeeding.

Complex AI-nursing-care projects as a challenge Artificial intelligence already supports medical diagnostics, optimizes clinical processes or indicates complex risk constellations for individual patients and suggests healthcare interventions. Nursing could also benefit from increased use of AI in the future. Research & Development projects, however, often encounter hurdles.

Our study In preparation for a new, large-scale German public funding program for AI in nursing, we conducted a mixed-methods study to explore needs, use cases, requirements, facilitators, and barriers to R&D. We invited nurses, nursing directors, digitization officers, informal caregivers, and researchers with backgrounds in nursing science or education, informatics and AI research, or ethics to discuss and prioritize needs and challenges for AI in nursing care.

We summarized requirements and characteristics of successful research projects and identified five overarching topics. Regulatory requirements addressed data analysis and models of data sharing in compliance with privacy regulations. Process and translational requirements included aspects of project planning, execution, and management.

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