Pharmacists’ perspectives on patient use of artificial intelligence-mediated medication consultation: a qualitative study at a tertiary hospital in Fujian Province of China
Year: 2026
Type: article
Abstract: The integration of artificial intelligence (AI) into healthcare has accelerated globally, with increasing numbers of patients using AI-mediated platforms for medication consultation. This study aims to explore the views of pharmacists on this practice, providing evidence for the integration of AI into pharmaceutical services. A qualitative study was conducted via semi-structured face-to-face interviews with 10 pharmacists from Zhongshan Hospital of Xiamen University in Fujian Province, China. Purposive sampling was employed to include pharmacists with diverse professional backgrounds and experience. Interviews were transcribed verbatim and data were analyzed using thematic analysis with NVivo 15. Seven core themes were identified. Pharmacists generally favored patients using AI for medication information, acknowledging its merits and recognized its value as an auxiliary tool for health education and efficiency improvement, while highlighting its limitations in complex clinical scenarios and information reliability. Patient-related factors also affected the application of AI. Pharmacists emphasized their irreplaceable advantages in personalized guidance, humanistic care, and risk identification, and noted that AI popularization may reshape consultation volumes, communication dynamics, and professional competence requirements for pharmacists, alongside proposing targeted usage recommendations. This study explored the perceptions of pharmacists on AI-mediated medication consultation, highlighting the auxiliary potential of AI and the irreplaceable role of pharmacists. The findings provide a basis for policy formulation, AI application training, and AI optimization to promote rational integration and medication safety.
Source: BMC Health Services Research
Institution: Zhongshan Hospital of Xiamen University
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,290
OpenAlex ID: W7223472930
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