Collaborative and Cooperative Hospital “In-House” Medical Device Development and Implementation in the AI Age: The European Responsible AI Development (EURAID) Framework Compatible With European Values
The last years have seen an acceleration in the development and uptake of artificial intelligence (AI) systems by "early adopter" hospitals, caught between the pressures to "perform" and "transform" in a struggling health care system. This transformation has raised concerns among health care providers as their voices and location-specific workflows have often been overlooked, resulting in technologies that fail to integrate meaningfully into routine care and worsen rather than improve care processes. How can positive AI implementation be carried out in health care, aligned with European values? Based on a perspective that spans all stakeholders, we have created EURAID (European Responsible AI Development), a practical, human-centric framework for AI development and implementation based on agreed goals and values. We illustrate this approach through the co-development of a narrow-purpose "in-house" AI system, designed to help bridge the AI implementation gap in real-world clinical settings. This example is then expanded to address the broader challenges associated with complex, multiagent AI systems. By portraying all key stakeholders across the AI development life cycle and highlighting their roles and contributions within the process, real use cases, and methods for achieving iterative consensus, we offer a unique practical approach for safe and fast progress in hospital digital transformation in the AI age.
Authors
- Hannes Schlieter (ORCID: https://orcid.org/0000-0002-6513-9017)
- Magdalena Wekenborg (ORCID: https://orcid.org/0000-0002-4498-107X)
- Moritz Schneider (ORCID: https://orcid.org/0000-0003-1789-8593)
- Maria Eberlein-Gonska
- Myriam Lipprandt (ORCID: https://orcid.org/0000-0001-9371-0551)
- Florian Jovy-Klein
- Katharina Weitz (ORCID: https://orcid.org/0000-0003-1001-2278)
- Anke Diehl
- Malte L Schmieding (ORCID: https://orcid.org/0000-0002-5844-7791)
- Manfred Hülsken-Giesler (ORCID: https://orcid.org/0000-0002-3912-9093)
- Stephen Gilbert (ORCID: https://orcid.org/0000-0003-3868-8202)
- Reinhard Strametz (ORCID: https://orcid.org/0000-0002-9920-8674)
- Hannah Sophie Muti
- Larissa Schlicht (ORCID: https://orcid.org/0000-0002-2170-386X)
- Eva Weicken
- Martin Sedlmayr (ORCID: https://orcid.org/0000-0002-9888-8460)
- Ulrike Rösler
- Thomas Reibel (ORCID: https://orcid.org/0000-0001-5053-309X)
- Jakob Nikolas Kather
- Rebecca Mathias (ORCID: https://orcid.org/0000-0002-3906-2415)
- Anett Schönfelder (ORCID: https://orcid.org/0009-0007-7064-1611)
- Elisabeth Liebert
- Julius Obergassel
- Nils Schweingruber
- Barbara Susec
- Elisabeth Kohoutek
- Thomas Lennefer
Institutions
- Karlsruhe Institute of Technology (DE)
- University of Leeds (GB)
- Universität Hamburg (DE)
- Osnabrück University (DE)
- Heidelberg University (DE)
- Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute (DE)
- German Medical Association (DE)
- University Hospital Heidelberg (DE)
- German United Services Trade Union (DE)
- University Medical Center Hamburg-Eppendorf (DE)
- National Center for Tumor Diseases (DE)
- Respiratory Research Institute (DE)
- Essen University Hospital (DE)
- Institut für Arbeitsschutz der Deutschen Gesetzlichen Unfallversicherung (DE)
- Hochschule Osnabrück (DE)
- Bergmann und Partner Rechtsanwälte (DE)
- University Hospital Carl Gustav Carus (DE)
- Federal Ministry of Health (DE)
- Technische Universität Dresden (DE)
- RWTH Aachen University (DE)
- Federal Institute for Occupational Safety and Health (DE)
Publication Details
- Journal
- Journal of Medical Internet Research
- Published
- 2025-11-06
- DOI
- https://doi.org/10.2196/80754
- Citations
- 1
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.65