The use of artificial intelligence is an important part of the solution when resources need to be optimized and we need to think differently. But is our healthcare system ready to implement the new solutions, and what challenges will arise in the meeting between digital research and everyday life in a busy hospital?
“Artificial intelligence and machine learning can improve the ways we prevent and diagnose diseases, optimize treatments, increase quality and reduce errors. A huge number of technological innovations are emerging right now, many of which are promising research-based AI solutions, and yet it is a challenge to get them tested and implemented in the healthcare sector, says Thomas Riisgaard Hansen, director of Digital Research Centre Denmark (DIREC).
What is holding the development back and what are the actual challenges? Is it that technology is getting closer, but still too limited and full of errors to create actual value in the healthcare sector? Is it that data and legislation complicate the development of algorithms? Is it that the healthcare system has problems incorporating new technology and changing work processes? Is it a lack of resources and money? Or does the problem lie elsewhere? This hot topic was discussed in the session ‘How to navigate the challenges of implementing groundbreaking AI in the healthcare sector’ at this year’s Digital Tech Summit.
“It is a major task to use the technological opportunities in the healthcare system and it also requires us not to be deceived by dazzling promises about what the technology can do but, instead, we must work purposefully to exploit the actual opportunities and to remove or reduce the barriers that interfere,” says Thomas Riisgaard Hansen, who has worked with health innovation for 20 years and moderated the panel discussion.
He was accompanied by technology companies, researchers, innovators, and health professionals, who gave their own take on how we can jointly support the development and implementation of new solutions that will benefit patients and staff.
The session presented three concrete cases about implementation of AI in the Danish healthcare system:
Getting Access to Health Data and Ways to Leverage it in the Health Sector
Henrik Løvig, Enversion & Gitte Kjeldsen, Danish Life Science Cluster
Getting AI innovations implemented internationally
Mads Jarner Brevadt, Co-founder & CEO, Radiobotics & Janus Uhd Nybing, Ledende Forskningsradiograf, Bispebjerg og Frederiksberg Hospital samt Medstifter, Radiologisk AI Testcenter RAIT
Getting Research Implemented in the Daily Practices in a Hospital Setting
Mads Nielsen, Professor, KU andIlse Vejborg, Head of Department, Rigshospitalet
Each case is based on experiences with the implementation of artificial intelligence in the healthcare system and highlighted the challenges and best practices that have been identified from the perspective of the technology developers and not least of the healthcare professionals.
The session was organized by DIREC, Pioneer Centre for AI, CBS, DTU, and Danish Life Science Cluster.