ArticleBMC health services research2025
Physicians' perceptions and attitudes on artificial intelligence in hospital management: a qualitative study.
Article in BMC health services research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundArtificial intelligence has begun to find its way into hospital management, where it is used to ease tasks, such as allocating resources, coordinating workflows and handling data. For physicians, who directly experience effects of management systems, their perspectives are critical to whether AI tools can be meaningfully adopted and integrated. Yet research in this area has tended to remain on clinical side, with far less attention given to how physicians perceive and respond to AI in hospital management.
objectiveThis study aims to examine how physicians in China perceive, experience, evaluate use of artificial intelligence in hospital management. It seeks identify potential application scenarios, highlight factors that facilitate or hinder integration, explore differences across physician groups.
methodsThe study used qualitative approach, with semi-structured interviews involving 25 practicing physicians in China. Data were analysed in NVivo with reflexive thematic analysis, carried out in six steps.
resultsThe study identified four main themes about physicians’ views on artificial intelligence in hospital management: potential of AI applications, factors that drive use, barriers to use, and integration strategies, along with 12 related subthemes.
conclusionThis study points out both opportunities and challenges in bringing artificial intelligence into hospital management. AI shows clear potential to improve efficiency and support institutional and digital transformation, but its use is limited by weak infrastructure, financial constraints and cultural resistance. Physicians’ attitudes also differ by role, hospital level, age, experience and views on risk. Because this study uses purposive sampling, a cross-sectional design and includes only physicians, the generalizability of the findings is limited.
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