ScholarWorks@성균관대학교

초록

Purpose To evaluate radiologists' perceived value, readiness, and early experiential signals regarding artificial intelligence (AI) in radiology within a value-based healthcare framework, and to identify determinants of higher perceived value. Materials and methods A cross-sectional survey was conducted between June and September 2024 using a 30-item questionnaire translated into 13 languages. The survey assessed AI exposure, institutional readiness, trust, understanding, perceived alignment with healthcare needs, and perceived clinical value. Analyses were restricted to radiologists from 25 countries (n = 305). Multivariable ordinal logistic regression was performed to identify factors associated with higher perceived value. Results Among 305 radiologists from 25 countries, 31.5% (96/305) reported using AI tools and 21.9% (67/305) worked in institutions that had purchased AI products. Overall, 48.5% (148/305) reported moderate-to-extreme perceived improvement in practice attributable to AI, whereas 51.5% (157/305) reported no or only slight improvement. In the full sample, multivariable analysis showed that higher trust in AI (adjusted OR = 1.99, 95% CI [1.21, 3.27], p = 0.007), greater understanding of AI (adjusted OR = 1.54, 95% CI [1.09, 2.17], p = 0.015), perceived tailoring to local clinical needs (adjusted OR = 2.07, 95% CI [1.40, 3.05], p < 0.001), and stronger alignment with healthcare priorities (adjusted OR = 1.86, 95% CI [1.15, 3.00], p = 0.012) were independently associated with higher perceived value, while institutional purchase of AI products was associated with lower perceived value (adjusted OR = 0.47, 95% CI [0.30, 0.73], p = 0.001). Conclusion Radiologists report a substantial gap between the anticipated benefits of AI and its perceived contribution to value-based radiology practice. Perceived value is shaped primarily by trust, understanding, and local relevance rather than adoption or procurement alone, underscoring the importance of clinician-centred, context-aware implementation strategies.

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