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Toward a global ecosystem for health professions education: harnessing open educational resources and generative AI
Charles G Prober1, David Atchoarena2,3, Tao Le4,5
1Stanford Center for Health Education, Stanford University School of Medicine, Stanford, CA, United States.
Abstract:
The global health workforce faces a projected shortage of more than 11 million health workers by 2030, with the most severe shortfalls in low- and middle-income countries (LMICs). Traditional training models are resource-intensive, rigid, and slow to evolve. These models cannot meet the scale or diversity of workforce needs, nor adapt quickly enough to shifting epidemiology, system demands, or local contexts. Building on previous proposals for shared digital curricula and competency-based ecosystems, this Commentary outlines how the convergence of rapidly growing Open Educational Resources (OER), interoperable digital learning platforms, advances in generative artificial intelligence (AI), and a global governance model creates new opportunities to develop a global, modular, openly licensed curricular ecosystem aligned with regional, national, and global competency frameworks. The authors propose a global initiative to co-create, validate, and disseminate multilingual, adaptable, and competency-aligned training assets across diverse cadres of health workers. Through partnerships among Ministries of Health, academic institutions, professional organizations, and the World Health Organization (WHO), this initiative would strengthen local capacity building, ensure quality and equity, and promote the responsible use of AI in health professions education.
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