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

Akio Kanazawa (), Kazutoshi Fujibayashi, Yu Watanabe, Seiko Kushiro, Naotake Yanagisawa, Yasuko Fukataki, Sakiko Kitamura, Wakako Hayashi, Masashi Nagao, Yuji Nishizaki, Takenori Inomata, Eri Arikawa-Hirasawa and Toshio Naito
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Akio Kanazawa: Department of General Medicine, Faculty of Medicine, Juntendo University, Tokyo 113-8421, Japan
Kazutoshi Fujibayashi: Department of General Medicine, Faculty of Medicine, Juntendo University, 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
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
Yuji Nishizaki: Department of General Medicine, Faculty of Medicine, Juntendo University, Tokyo 113-8421, Japan
Takenori Inomata: Department of Ophthalmology, 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

IJERPH, 2023, vol. 20, issue 12, 1-11

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.

Keywords: decision-making; resident physician; artificial intelligence (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2023
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