{
  "abstract": "Introduction Artificial intelligence (AI)-powered chatbots are increasingly integrated into healthcare to support administrative processes, health education and chronic disease management. These systems simulate human dialogue through natural language processing and machine learning, enabling dynamic and context-aware interactions. Despite their rapid adoption, there is limited synthesis of existing research describing how these technologies are applied across different healthcare contexts and what outcomes have been reported. This scoping review aims to map and describe the existing literature on the use of AI-powered chatbots in healthcare with a focus on clinical outcomes, patient satisfaction and operational efficiency. It will identify the types of studies conducted, their key characteristics and existing research gaps to guide future research.Methods and analysis Following the Joanna Briggs Institute methodology and Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines, a comprehensive search will be conducted across Medline (PubMed), CINAHL, Embase, Web of Science, The Cochrane Library and MedRxiv from database inception to 10 September 2025. Studies published in English, French, Dutch or German, involving AI-powered chatbots in any healthcare context reporting on clinical outcomes and/or patient satisfaction and/or operational efficiency will be included. Studies without full-text availability, protocols, trial registrations, reviews and studies conducted solely in educational settings will be excluded. Title and abstract screening will be supported by ASReview LAB, an AI-based active learning tool to enhance efficiency. Screening and data extraction will be conducted independently by two reviewers with disagreements resolved by a third reviewer. Findings will be synthesised narratively and presented using structured evidence tables categorised by chatbot type, clinical healthcare context and reported outcomes.Ethics and dissemination Ethical approval is not required, as this study involves the analysis of published data only. The results of this scoping review will be disseminated through publication in a peer-reviewed journal, presentations at academic conferences and established professional networks.Trial registration number Open Science Framework (OSF), https://doi.org/10.17605/OSF.IO/8UE3B.",
  "authors": [
    {
      "affiliations": [
        "University Centre for Nursing and Midwifery, Department of Public Health and Primary Care, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium",
        "Research Centre 360° Care and Well-being, HOGENT University of Applied Sciences and Arts, Ghent, Belgium",
        "School of Healthcare, HOGENT University of Applied Sciences and Arts, Ghent, Belgium"
      ],
      "name": "Ellen Goossens"
    },
    {
      "affiliations": [
        "Unit of Medical Informatics and Statistics, Department of Public Health and Primary Care, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium"
      ],
      "name": "Pamela Mfouth Kemajou"
    },
    {
      "affiliations": [
        "Unit of Medical Informatics and Statistics, Department of Public Health and Primary Care, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium"
      ],
      "name": "Pascal Coorevits"
    },
    {
      "affiliations": [
        "Geneva School of Health Science, HES-SO University of Applied Sciences and Arts, Geneva, Western Switserland, Switzerland",
        "Care Directorate, Geneva University Hospitals, Geneva, Switzerland",
        "Faculty of Medicine, University of Geneva, Geneva, Switzerland",
        "Faculty of Medicine Nursing and Health Sciences, Monash University, Melbourne, Victoria, Australia"
      ],
      "name": "Sebastian Probst"
    },
    {
      "affiliations": [
        "University Centre for Nursing and Midwifery, Department of Public Health and Primary Care, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium",
        "Swedish Centre for Skin and Wound Research (SCENTR), School of Health Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden"
      ],
      "name": "Dimitri Beeckman"
    }
  ],
  "title": "Clinical outcomes, patient satisfaction and operational efficiency of AI-powered chatbots in medicine and healthcare: protocol for an AI-aided scoping review",
  "uid": "f195e166-21a7-5ec5-8dd8-48b105b8f690"
}