Project Lead:

Prof. Dr. Karin Wolf-Ostermann

Project Team Members:

Alessia Nowak (Charité), Dominik Domhoff (University of Bremen), Dr. Jörg Pohle (HIIG Berlin), Dr. Kathi Beier (University of Bremen), Dr. Kathrin Seibert (University of Bremen), Dr. Margret Fischer (vediso e.V.), Dr. Miriam Wolf (vediso e.V.), Janissa Altona (University of Bremen), Lea Bergmann (vediso e.V.), Martin Hähnel (University of Bremen), Matthias Schulte-Althoff (Charité), Prof. Dr. Dagmar Borchers (University of Bremen), Prof. Dr. Daniel Fürstenau (FU Berlin & Charité), Prof. Dr. Felix Biessmann (BHT & ECDF), Prof. Dr. Max von Grafenstein (HIIG Berlin), Rahel Gubser (Charité), Sebastian Jäger (BHT)

Project Duration:

12/2021 - 04/2025

Project Description:

The overarching goal of ProKIP is to support the integration of AI solutions into nursing practice. This goal is pursued on two levels: On the one hand, ProKIP provides a support, advisory and networking process for eight collaborative projects. On the other hand, ProKIP explores the success factors for the use of AI in nursing care through its own research.
This website presents the ProKIP project and the eight collaborative projects and provides information on current findings and exciting events.

In ProKIP, we investigate how AI solutions can be successfully integrated into nursing practice.
To this end, we draw on existing findings from previous national and international research as well as from our other projects. However, we also collect new data. For this purpose, we repeatedly survey employees involved in the eight projects funded under the BMBF programme “Making Repositories and AI Systems Usable in Everyday Nursing Care”. Through online surveys, interviews and workshops, we identify success factors and barriers in nursing and AI projects.
The result is an AI Nursing Readiness Assessment for evaluating research projects. In the future, research projects will thus be able to reflect on and successfully address important aspects such as the benefits of AI systems in nursing care, data representativeness, approaches to data sharing, the design of participation, as well as ethical and professional implications.

For further information, please visit the ProKIP website.