Evidence map›Paper›PMID 39432546›Full record

ArticleJournal of patient safety2025

Intelligent Verification Tool for Surgical Information of Ophthalmic Patients: A Study Based on Artificial Intelligence Technology.

Hui Lin, Xiaofang Huang, Yaying Sheng, Ning Tang, Hengli Lian, Wenjie Zhang, Lvjun Zhao, Hanqing Zhu, Pingjun Chang, Yingxuan Guo

Abstract read
In one paragraph

Article in Journal of patient safety, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Hui Lin
Xiaofang Huang
Yaying Sheng
Ning Tang
Hengli Lian
Wenjie Zhang
Lvjun Zhao
Hanqing Zhu
Pingjun Chang

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveWith the development of day surgery, the characteristics of "short, frequent and fast" ophthalmic surgery are becoming more prominent. However, nurses are not efficient in verifying patients' surgical information, and problems such as patient privacy leakage are becoming more prominent. To improve the situation, we developed a new augmented reality (AR)-based tool for visual recognition and artificial intelligent (AI) interpretation of the pattern and location of patient surgical skin markings for the verification of the correct surgical site and procedure. The tool can also display a variety of other verbally requested patient information. The purpose of this proposal is to evaluate its feasibility of use by surgical nurses in a real clinical setting.

methodsWe developed a tool with image recognition technologies to interpretation patient surgical skin markings and match the information obtained with the patients surgical records, thus, verify the patient's surgical information. Verification includes the proper surgical site and type of procedure to be performed. Nurses can interact with the device through its speech recognition capabilities and the device provides them with a variety of other requested patient information via a heads-up display. Three hundred patients in an outpatient ophthalmology clinic were divided into an AR intelligent verification experimental group and a manual verification control group. The accuracy of information verification, work time consumption, and economic cost data were compared between the 2 groups to evaluate the effectiveness of the AR Surgical Information Intelligent Verification Tool in clinical patient surgical information verification.

resultsThere was no statistically difference in the correct rates of patient surgical information review between the experimental group (95.33%) and the control group (98.67%) (χ 2  = 2.934, P  = 0.087). The median time for information verification was 10.00 (10.00, 11.00) seconds in the experimental group and 21.00 (20.00, 24.00) seconds in the control group, a statistically difference (Z = 0.000, P  < 0.001). The experimental group saved 11 seconds per patient per review compared with the control group. Considering 10,531 surgeries in 2023, printing 1 page of surgical information per 9 patients and requiring 4 copies, 4680 pages of printing paper could be saved.

conclusionsThe AR Surgical Information Intelligent Verification Tool has advantages in assisting medical staff in patient surgical information verification, improving nursing efficiency, preventing surgical mark errors or nonstandardization, protecting patient privacy, and saving costs. It has certain research and application value in the scenario of patient surgical information verification in ophthalmic day ward.

Indexed as

Artificial IntelligenceOphthalmologic Surgical ProceduresAdultAgedAugmented RealityFemaleHumansMaleMiddle Aged

Identifiers

PMID39432546
PMCPMC11832179

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.