A third session supported by the DigitalHealthUptake project focused on the implementation challenges of artificial intelligence (AI) in healthcare. The session was designed as an engagement exercise to follow up an “executive digest” prepared by the project.
AI has many applications in the healthcare field, but its implementation relies strongly on how health systems’ and health providers’ infrastructures can support the development of AI-based services. These context-specific implementation challenges were showcased through three presentations. The first two featured how some health systems are AI-ready, and how they are approaching the implementation of AI-intensive services. The third focused on the readiness of European hospitals to handle emerging technologies.
Systemising the adoption of Artificial Intelligence in public healthcare systems: the Catalan approach
Maria Bretones Vallejo, Fundació Tic Salut Social, Catalonia, Spain
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First to take the stage was Maria Bretones, biomedical engineer at TIC Salut Social from Catalonia, Spain who presented “Systemising the adoption of Artificial Intelligence in public healthcare systems: the Catalan approach”. Maria introduced the Catalan Health AI Programme which embraces the entire lifecycle of AI tools, from conceptualisation to implementation. The main programme objective is to implement AI tools that bring systemic value, i.e. improving the care provided to citizens and supporting healthcare professionals.
The programme also ensures that these tools follow the FUTURE criteria for trustworthy AI, which will make AI lawful, ethical, and robust. Among the programme ‘s activities are the publication of a guideline on good practices for code development in AI for health, and the launch of a Health AI Observatory that maintains a registry of AI tools (145 tools from 79 different sources) . In addition, it scans the field in search of the latest innovations in AI. Last but not least, support to implementation is a key activity of the Catalan Health AI programme that includes data governance, technological integration, training of health professionals and communication activities.
Artificial Intelligence for Health Maturity in Germany: Current State and Prospects
Georgi Chaltikyan, MD, PhD, Deggendorf Institute of Technology, Germany
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Georgi Chaltikyan, professor at the Deggendorf Institute of Technology, contributed insights into Germany’s AI for Health maturity. His presentation outlined the current state of digital health in Germany and the prospects for secondary use of health data and AI. Georgi emphasised the regulatory efforts that have materialised in legislation that encourages digital health implementation in Germany. The legislative acts include the 2019 Digital Care Act, the 2020 Hospital Future Act, and the 2021 the Digital Supply Care Modernisation Act. These regulations have led to the deployment of a Digital Radar to measure the IT maturity in German hospitals, the electronic health record and ePrescription system, and Germany’s DiGA programme. In the secondary use and AI field, trust remains an issue despite the growth of German AI startups. Two new national legislative packages (the Digital Act and the Health Data Use Act) are currently being discussed in the Bundestag (Germany’s Parliament). They are aimed at reshaping the digital health landscape, demonstrating significant efforts underway to boost adoption, and preparing the health system for digital transformation.
Challenges deploying the ODIN AI framework in European hospitals
Alejandro Medrano Gil, Universidad Politécnica de Madrid, Spain
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Alejandro Medrano, researcher at Universidad Politécnica de Madrid in Spain, was the third speaker in the session. He focused on the challenges of deploying AI in European hospitals. He drew on the work of the ODIN project. This project developed a framework to deploy a data-driven and evidence-based management approach in hospitals. The approach includes emerging technologies such as AI, robotics, and the Internet of Things. It has been piloted in five European hospitals, with three reference use cases, and seven specific use cases.
Key implementation challenges are related to data and change management. Indeed, data frequently resides in silos and it is often not well identified or linked. Moreover, the need to ensure data privacy adds another layer of complexity and may thus exclude the use of data for AI. In co-creation sessions held in ODIN, hospitals declared that change management is a critical challenge to the adoption of new technologies.
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Nathan Lea, Data Protection Officer & Information Governance Lead at I-HD, chaired the session and moderated the debate. Online commentators remarked on the interest of the European Health Data Space e.g., for AI, and made associations between the experiences presented and other, ongoing, European AI-related projects and initiatives.
