Barriers and facilitators to implementing imaging-based diagnostic artificial intelligence-assisted decision-making software in hospitals in China: a qualitative study using the updated Consolidated Framework for Implementation Research

The study findings contributed to the ongoing exploration of AI integration in healthcare from the perspective of China, emphasising the need for a comprehensive approach considering both innovation-specific factors and the broader organisational and contextual dynamics. As China and other developing countries continue to advance in adopting AI technologies, the derived insights could further inform healthcare practitioners, industry stakeholders and policy-makers, guiding policies and practices that promote the successful implementation of imaging-based diagnostic AI-assisted decision-making software in healthcare for optimal patient care.

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Publication Details

Journal
BMJ Open
Published
2024-09-01
DOI
https://doi.org/10.1136/bmjopen-2024-084398
Citations
34
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
4.09
Controls
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article

Barriers and facilitators to implementing imaging-based diagnostic artificial intelligence-assisted decision-making software in hospitals in China: a qualitative study using the updated Consolidated Framework for Implementation Research

Feifei Jin, Larry Liu, Xiwen Liao, Chen Yao et al.
34 citations
BMJ Open
Artificial Intelligence in Healthcare and Education
4.09
article

Barriers and facilitators to implementing imaging-based diagnostic artificial intelligence-assisted decision-making software in hospitals in China: a qualitative study using the updated Consolidated Framework for Implementation Research

Feifei Jin, Larry Liu, Xiwen Liao, Chen Yao, Jun Zhang
article en
34 citations

Abstract

The study findings contributed to the ongoing exploration of AI integration in healthcare from the perspective of China, emphasising the need for a comprehensive approach considering both innovation-specific factors and the broader organisational and contextual dynamics. As China and other developing countries continue to advance in adopting AI technologies, the derived insights could further inform healthcare practitioners, industry stakeholders and policy-makers, guiding policies and practices that promote the successful implementation of imaging-based diagnostic AI-assisted decision-making software in healthcare for optimal patient care.

BMJ OpenVol. 14(9)
Merck & Co., Inc., Rahway, NJ, USA (United States) (US), Peking University (CN), Cornell University (US), Peking University People's Hospital (CN), Peking University First Hospital (CN)
Partnerships for the goals
Openalex Percentile: Top 6%
Artificial Intelligence in Healthcare and Education
4.09
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