A bibliometric analysis of the application trends of information technology in antimicrobial stewardship within hospitals.

Journal: European journal of hospital pharmacy : science and practice
Published Date: Jun 23, 2026

Abstract

OBJECTIVES: This study uses bibliometric analysis to systematically map research trends, knowledge structure and evolution of information technology (IT) in hospital antimicrobial stewardship (AMS) over the last 20 years. METHODS: A Web of Science Core Collection search (2000-2025) yielded 258 English-language publications on IT applications in hospital AMS. A bibliometric analysis, utilising CiteSpace and Bibliometrix, quantitatively evaluated domain evolution through temporal analysis, network mapping, keyword clustering, burst detection and examination of highly cited publications. RESULTS: The bibliometric analysis reveals a fluctuating yet overall increasing trend in annual publications, peaking at 49 articles in 2024. The US (131 publications) and European nations demonstrate significant research output (centrality >0.2), with major collaborative networks coalescing around institutions including Harvard University and Imperial College London. Keyword analysis identifies 'AMS' as a core theme, closely associated with technological keywords such as 'machine learning (ML)', 'clinical decision support systems (CDSS)', 'electronic health records (EHR)' and 'artificial intelligence (AI)'. Emerging trends suggest a shift in research focus from foundational strategies to data-driven prediction of antimicrobial resistance (AMR) and precision interventions. Highly cited literature emphasises the integration of EHR and ML technologies for optimising prescriptions and predicting resistance patterns. CONCLUSIONS: IT-driven AMS research has shifted from empirical management to data science. Despite EHR integration, and ML and CDSS support, challenges remain in data standardisation, technical deployment and ethics. Future work must emphasise global collaboration, standardisation, design refinement and ethical guidelines, and provide clear algorithm explanations to enhance AMR mitigation.

Authors

  • Yannan Ding
    Department of Pharmacy, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China.
  • Ming Lei
    Department of Radiology, Zhuhai Hospital, Guangdong Provincial Hospital of Traditional Chinese Medicine, 53 Jingle Road, Zhuhai City, Guangdong Province, China.
  • Gang Yuan
    School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230022, China; Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China. Electronic address: [email protected].
  • Jinzhong Yu
    Department of Pharmacy, Kweichow Moutai Hospital, Renhuai, Guizhou, China.
  • Lili Wu
    Research Center for Integrative Medicine of Guangzhou University of Chinese Medicine, Guangzhou, 510006, P. R. China.
  • Jianwen Yang
    School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin, 300193, China.
  • Hong Zhang
    Department of Anesthesiology and Operation, The First Hospital of Lanzhou University, Lanzhou, Gansu, China.

Keywords

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