Increasing Adoptive Capacities of Innovative Health Technologies in the Global Health Care System
DOI:
https://doi.org/10.52320/dav.v22i1.381Keywords:
Data quality assessment, socio-technical system, champions, funding mechanism, organization alignmentsAbstract
AI usage in healthcare is still in its infancy and has not yet reached its potential to make the global healthcare system more equitable and safe. There is a substantial gap between AI promises and its actual delivery in healthcare settings. AI is a social-technical system and AI technology alone cannot solve our health equity issue. This is the research question: What social, political, and economic elements in the global health system must be addressed such that the capacities of AI can be optimized? The paper employs qualitative research to seek expert opinions, investigate the success cases of implementing particular AI devices in Hong Kong and Singapore, and integrate the lessons learned from the adoption of 87 AI-technology initiatives in a large Canadian hospital. The author recommends how the supply side increases their trustworthiness and the demand side grows trust. The supply side includes technology providers, legal, policy, and professional organizations, venture capitalists, and academic research institutions need to provide responsible AI and govern AI for long-term benefits. Increasing trust from healthcare organizations, including the presence of champions, organization alignments, funding mechanisms, new professional identities, patients' digital and health literacy capabilities, and supportive organization culture, is recommended. The same AI devices should be interoperable among the healthcare systems in and outside their countries. Standardized data quality assessment, benchmarking datasets, funding mechanisms, and agreement on model and clinical performance measures need to be used to facilitate comparison across products and settings. Investment in supporting digital infrastructure in low and middle-income countries is essential for the effective operation of AI devices. Various stakeholders must continuously demystify AI and participate in the collaborative work with those who have less power in the system.
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Copyright (c) 2025 Maria Lai-Ling Lam

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