Large-scale observational study of AI-based patient and surgical material verification system in ophthalmology: real-world evaluation in 37 529 cases

The AI-based surgical safety system significantly increased near miss detection and showed potential economic benefits. However, errors in non-authenticated cases underscore the importance of consistent system use and integration with existing safety protocols. These findings emphasise that while AI can enhance surgical safety, its effectiveness depends on proper implementation and continuous refinement.

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Publication Details

Journal
BMJ Quality & Safety
Published
2024-11-29
DOI
https://doi.org/10.1136/bmjqs-2024-018018
Citations
3
Primary Topic
Intraocular Surgery and Lenses
Type
article
Field-Weighted Citation Impact
1.62

Funders

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article

Large-scale observational study of AI-based patient and surgical material verification system in ophthalmology: real-world evaluation in 37 529 cases

Naofumi Ishitobi, Masahiro Akada, Hayato Tanaka, Hitoshi Tabuchi et al.
3 citations
BMJ Quality & Safety
Intraocular Surgery and Lenses
1.62
article

Large-scale observational study of AI-based patient and surgical material verification system in ophthalmology: real-world evaluation in 37 529 cases

Naofumi Ishitobi, Masahiro Akada, Hayato Tanaka, Hitoshi Tabuchi, Hodaka Deguchi, Mao Tanabe, Yuta Nakaniida
article en
3 citations

Abstract

The AI-based surgical safety system significantly increased near miss detection and showed potential economic benefits. However, errors in non-authenticated cases underscore the importance of consistent system use and integration with existing safety protocols. These findings emphasise that while AI can enhance surgical safety, its effectiveness depends on proper implementation and continuous refinement.

BMJ Quality & SafetyVol. 34(7)
Hiroshima University (JP)
Japan Agency for Medical Research and Development
Partnerships for the goals
Openalex Percentile: Top 16%
Intraocular Surgery and Lenses
1.62
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