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Evaluation of a Medical Interview-Assistance System Using Artificial Intelligence for Resident Physicians Interviewing Simulated Patients: A Crossover, Randomized, Controlled Trial

Author

Listed:
  • Akio Kanazawa

    (Department of General Medicine, Faculty of Medicine, Juntendo University, Tokyo 113-8421, Japan
    Department of General Internal Medicine and Infectious Disease, Saitama Medical Center, Saitama Medical University, Saitama 350-8550, Japan)

  • Kazutoshi Fujibayashi

    (Department of General Medicine, Faculty of Medicine, Juntendo University, Tokyo 113-8421, Japan
    Medical Technology Innovation Center, Juntendo University, Tokyo 113-8421, Japan
    Clinical Research and Trial Center, Juntendo University Hospital, Tokyo 113-8421, Japan)

  • Yu Watanabe

    (Department of General Medicine, Faculty of Medicine, Juntendo University, Tokyo 113-8421, Japan)

  • Seiko Kushiro

    (Department of General Medicine, Faculty of Medicine, Juntendo University, Tokyo 113-8421, Japan)

  • Naotake Yanagisawa

    (Medical Technology Innovation Center, Juntendo University, Tokyo 113-8421, Japan
    Clinical Research and Trial Center, Juntendo University Hospital, Tokyo 113-8421, Japan)

  • Yasuko Fukataki

    (Clinical Research and Trial Center, Juntendo University Hospital, Tokyo 113-8421, Japan)

  • Sakiko Kitamura

    (Clinical Research and Trial Center, Juntendo University Hospital, Tokyo 113-8421, Japan)

  • Wakako Hayashi

    (Clinical Research and Trial Center, Juntendo University Hospital, Tokyo 113-8421, Japan)

  • Masashi Nagao

    (Medical Technology Innovation Center, Juntendo University, Tokyo 113-8421, Japan
    Clinical Research and Trial Center, Juntendo University Hospital, Tokyo 113-8421, Japan)

  • Yuji Nishizaki

    (Department of General Medicine, Faculty of Medicine, Juntendo University, Tokyo 113-8421, Japan
    Medical Technology Innovation Center, Juntendo University, Tokyo 113-8421, Japan
    Clinical Research and Trial Center, Juntendo University Hospital, Tokyo 113-8421, Japan)

  • Takenori Inomata

    (Department of Ophthalmology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan
    Department of Digital Medicine, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan
    Department of Hospital Administration, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan
    AI Incubation Farm, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan)

  • Eri Arikawa-Hirasawa

    (Department of Neurology, Faculty of Medicine, Juntendo University, Tokyo 113-8421, Japan)

  • Toshio Naito

    (Department of General Medicine, Faculty of Medicine, Juntendo University, Tokyo 113-8421, Japan)

Abstract

Medical interviews are expected to undergo a major transformation through the use of artificial intelligence. However, artificial intelligence-based systems that support medical interviews are not yet widespread in Japan, and their usefulness is unclear. A randomized, controlled trial to determine the usefulness of a commercial medical interview support system using a question flow chart-type application based on a Bayesian model was conducted. Ten resident physicians were allocated to two groups with or without information from an artificial intelligence-based support system. The rate of correct diagnoses, amount of time to complete the interviews, and number of questions they asked were compared between the two groups. Two trials were conducted on different dates, with a total of 20 resident physicians participating. Data for 192 differential diagnoses were obtained. There was a significant difference in the rate of correct diagnosis between the two groups for two cases and for overall cases (0.561 vs. 0.393; p = 0.02). There was a significant difference in the time required between the two groups for overall cases (370 s (352–387) vs. 390 s (373–406), p = 0.04). Artificial intelligence-assisted medical interviews helped resident physicians make more accurate diagnoses and reduced consultation time. The widespread use of artificial intelligence systems in clinical settings could contribute to improving the quality of medical care.

Suggested Citation

  • Akio Kanazawa & Kazutoshi Fujibayashi & Yu Watanabe & Seiko Kushiro & Naotake Yanagisawa & Yasuko Fukataki & Sakiko Kitamura & Wakako Hayashi & Masashi Nagao & Yuji Nishizaki & Takenori Inomata & Eri , 2023. "Evaluation of a Medical Interview-Assistance System Using Artificial Intelligence for Resident Physicians Interviewing Simulated Patients: A Crossover, Randomized, Controlled Trial," IJERPH, MDPI, vol. 20(12), pages 1-11, June.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:12:p:6176-:d:1174430
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    1. Moja, L. & Kwag, K.H. & Lytras, T. & Bertizzolo, L. & Brandt, L. & Pecoraro, V. & Rigon, G. & Vaona, A. & Ruggiero, F. & Mangia, M. & Iorio, A. & Kunnamo, I. & Bonovas, S., 2014. "Effectiveness of computerized decision support systems linked to electronic health records: A systematic review and meta-analysis," American Journal of Public Health, American Public Health Association, vol. 104(12), pages 12-22.
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