Cost-effectiveness of AI-based diabetic retinopathy screening in nationwide health checkups and diabetes management in Japan: A modeling study.

Journal: Diabetes research and clinical practice
PMID: 39892817

Abstract

AIMS: We evaluated the cost-effectiveness of artificial intelligence (AI)-based diabetic retinopathy (DR) screening in Japan. This evaluation compared the simultaneous introduction of AI in nationwide health checkups, namely "specific health check-ups in Japan" (SHC), and diabetes complication management (AI-case) with the current situation where AI is not being introduced (conventional-case) from the healthcare payer's perspective.

Authors

  • Yoko Akune
    Graduate School of Health Management, Keio University, Tokyo, Japan. Electronic address: yoko.akune@keio.jp.
  • Ryo Kawasaki
    Department of Vision Informatics, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan.
  • Rei Goto
    Graduate School of Health Management, Keio University, Tokyo, Japan; Graduate School of Business Administration, Keio University, Tokyo, Japan.
  • Hiroshi Tamura
    Cognitive Neuroscience Group, Graduate School of Frontier Biosciences, The University of Osaka, 1-4 Yamadaoka, Suita, Osaka, 565-0871, Japan. tamura.hiroshi.fbs@osaka-u.ac.jp.
  • Yoshimune Hiratsuka
    Department of Ophthalmology, Juntendo University School of Medicine, Tokyo, Japan.
  • Masakazu Yamada
    Kyorin Eye Center, School of Medicine, Kyorin University, Tokyo, Japan.

Keywords

External Resources

Popular Topics
Recent Journals