Early Experiences of Integrating an Artificial Intelligence-Based Diagnostic Decision Support System into Radiology Settings: A Qualitative Study

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

Artificial Intelligence (AI) based clinical decision support systems to aid diagnosis are increasingly being developed and implemented but with limited understanding of how such systems integrate with existing clinical work and organizational practices. We explored the early experiences of stakeholders using an AI-based e-learning imaging software tool Veye Lung Nodules (VLN) aiding the detection, classification, and measurement of pulmonary nodules in computed tomography scans of the chest. We performed semi-structured interviews and observations across early adopter deployment sites with clinicians, strategic decision-makers, suppliers, patients with long-term chest conditions, and academics with expertise in the use of diagnostic AI in radiology settings. We coded the data using the Technology, People, Organizations and Macro-environmental factors framework (TPOM). We conducted 39 interviews. Clinicians reported VLN to be easy to use with little disruption to the workflow. There were differences in patterns of use between experts and novice users with experts critically evaluating system recommendations and actively compensating for system limitations to achieve more reliable performance. Patients also viewed the tool positively. There were contextual variations in tool performance and use between different hospital sites and different use cases. Implementation challenges included integration with existing information systems, data protection, and perceived issues surrounding wider and sustained adoption, including procurement costs. Tool performance was variable, affected by integration into workflows and divisions of labor and knowledge, as well as technical configuration and infrastructure. These under-researched factors require attention and further research.
Original languageEnglish
Title of host publicationStudies in Health Technology and Informatics
Subtitle of host publicationTelehealth Ecosystems in Practice. Proceedings of the EFMI Special Topic Conference 2023
EditorsMauro Giacomini, Lăcrămioara Stoicu-Tivadar, Gabriella Balestra, Arriel Benis, Stefano Bonacina, Alessio Bottrighi, Thomas M. Deserno, Parisis Gallos, Lenka Lhotska, Sara Marceglia, Alejandro C. Pazos Sierra, Samanta Rosati, Lucia Sacchi
Place of PublicationAmsterdam
PublisherIOS Press
Number of pages2
ISBN (Electronic)978-1-64368-451-2
ISBN (Print) 978-1-64368-450-5
Publication statusPublished - 24 Oct 2023
EventEuropean Federation of Medical Informatics Special Topic Conference 2023 - Torino, Italy
Duration: 25 Oct 202327 Oct 2023

Publication series

NameStudies in Health Technology and Informatics
PublisherIOS Press
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365


ConferenceEuropean Federation of Medical Informatics Special Topic Conference 2023
Abbreviated titleEFMI STC 2023
Internet address

Keywords / Materials (for Non-textual outputs)

  • Artificial intelligence
  • Decision support
  • Radiology
  • Clinical decision support system
  • Diagnostic
  • Qualitative Research
  • hospital information systems


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