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IE University Center for the Governance of Change (CGC) launches report on “Innovation, Sustainability and the Future of Healthcare”

Innovation, Sustainability and the Future of Healthcare | IE University

The current health crisis has triggered an unprecedented surge in the development and demand of digital and AI technologies worldwide.

New research by the Center for the Governance of Change (CGC) of IE University, in conjunction with global healthcare leader Eli Lilly & Co. shows how the integration of AI technologies in the field of healthcare present a set of unique challenges which require international and intersectoral collaboration to be overcome.

The report, “Innovation, Sustainability and the Future of Healthcare” led by researchers Dr Mireia Crispin and Dr. Marcos Gallego, is based on a series of studies made by a European team of interdisciplinary experts. It examines the adoption and implementation of new AI technologies in healthcare systems across Europe, the challenges, opportunities and potential solutions. The findings of the report are particularly poignant in the context of COVID-19, which has exposed weaknesses in national healthcare systems across the world and highlighted the importance of a technologically robust and sustainable healthcare system.

“The opportunities to improve the quality of care for patients using AI are immense, and while huge progress has been made in recent years, we’re beginning to see the structural, technological as well as the cultural and political hurdles in Europe that are slowing the pace of progress,” Dr. Mireia Crispin commented. “Our research highlights some of these hurdles, with the aim of raising awareness of them among healthcare professionals, policymakers and AI specialists, to drive a more connected approach to healthcare in Europe. We hope to see a more collective, pan-European effort to resolving these issues, particularly since COVID-19, which is likely to expedite the development of AI-based technologies,” she added.

Key findings of the report

The research conducted by the CGC identified structural barriers that need to be overcome to ensure the effective integration of AI in existing healthcare systems:

  1. The overall experience of healthcare – how it is delivered to and experienced by patients – can be improved and enhanced using AI. To date, advancements in the use of AI in healthcare has focused mainly on improving or accelerating specific moments in care using AI, such as the reading of scans or improving diagnostics. Designing the healthcare systems of the future will require healthcare professionals and patients to collaborate further in the design and development process of new technologies and systems.
  2. Faced with the use of new technologies, an entirely new policy landscape that protects patients, needs to be introduced. While discussions around risks associated with certain technologies and potential policies are beginning, they are taking place in isolated spheres of influence. A broader, more inclusive cross-border and cross-profession effort is required, involving national and international policymakers, clinicians, digital health and machine learning leads from industry and academia, and representatives from patient communities and the general public. These efforts need to happen urgently, as the rate of technological innovation is only increasing.

Additional challenges facing the development of health AI applications in Europe include:

  • The sharing, standardization, anonymization and treatment of data across national health services remain some of the biggest hurdles for the development of health AI applications in Europe.
  • To combat staff shortages and the current skills gap, a proactive approach to address the education and training of the healthcare workforce is needed. This should be linked with the development of attractive career pathways and higher specialist training for data scientists.
  • Integrating new AI-based technologies into a healthcare system must be carried out in controlled way, with continuous monitoring and adjustment. A series of case studies, ranging from symptom checkers to fertility applications, suggest that rigorous studies of clinical effectiveness of AI technology are often lacking. In general, healthcare funding schemes have not been optimised for AI technologies. They may need to be re-evaluated to ensure high-quality care for everyone, particularly the most vulnerable.