Global Health Otherwise shared on LinkedIn:
“Healthcare AI ethics has focused too narrowly on algorithms alone, and this editorial argues that organizations must widen their lens. This shift matters for hospitals adopting new technology.
Yiadom (2026), writing in The American Journal of Bioethics, treats AI as an active participant embedded within hospital and research systems, not an isolated tool.
Drawing on three companion articles covering research recruitment, clinical summarization, and federated learning, the editorial shows that AI reshapes who gets contacted, how clinicians interpret patient histories, and how confidently predictions get trusted.
Prior research on sociotechnical systems supports this framing, showing that healthcare technologies succeed or fail based on surrounding workflows, not technical performance alone. The editorial recommends continuous monitoring after deployment, since many harms surface only once tools enter daily practice.
It calls for clear accountability, human oversight, and working feedback loops between AI systems and the people using them. It urges regulators and health systems to apply lessons from implementation science, evaluating AI the way they would evaluate any intervention that changes patient care delivery.
Yiadom (2026) argues healthcare AI ethics must extend beyond algorithms to workflow integration, urging continuous monitoring, clear accountability, and implementation science principles to govern AI’s real-world clinical impact over time.”
Title: The Ethics of Integration: Why Healthcare AI Must Be Evaluated Within Clinical and Research Workflows
Authors: Maame Yaa A. B. Yiadom.
Read The Full Article.
Luchuo Engelbert Bain, Senior Implementation Research Scientist and Deputy Director of MSc in Global Women’s Health at Nuffield Dept of Women’s and Reproductive Health, University of Oxford, added on LinkedIn:
“A timely reminder that responsible healthcare AI extends far beyond model performance.
Real-world value depends on how AI is integrated into clinical workflows, governed, monitored, and continuously improved.
Ethical AI requires accountability, human oversight, and implementation science to ensure technology strengthens patient care rather than simply adding algorithmic sophistication.
An important perspective for every healthcare leader navigating AI adoption.
Great piece from Maame Yaa ‘Maya’ A. B. Yiadom!”
