Frontiers in Robotics and AI (Dec 2021)
A Multi-Directional and Agile Academic Knowledge Transfer Strategy for Healthcare Technology
Abstract
Technology, especially cognitive agents and robots, has significant potential to improve the healthcare system and patient care. However, innovation within academia seldomly finds its way into practice. At least in Germany, there is still a digitalization gap between academia and healthcare practice and little understanding of how healthcare facilities can successfully purchase, implement, and adopt new knowledge and technology. Therefore, the aim of this study is to develop a successful academic knowledge transfer strategy for healthcare technology. We conducted a qualitative study with academic staff working in higher education in Germany and professionals in their practice partner organizations. In 15 semi-structured interviews, we aimed to assess interviewees experiences with knowledge transfer, to identify perceived influencing factors, and to understand the key aspects of a successful knowledge transfer strategy. The Dynamic Knowledge Transfer Model by Wehn and Montalvo, 2018 was used for data analysis. Based on our findings, we suggest that a successful transfer strategy between academia and practice needs to be multi-directional and agile. Moreover, partners within the transfer need to be on equal terms about expected knowledge transfer project outcomes. Our proposed measures focus particularly on regular consultations and communication during and after the project proposal phase.
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