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手术数据科学在识别择期肝脏手术术中人为失误和不良事件中的作用:一项初步研究。

The contribution of surgical data science to identifying intraoperative human errors and adverse events in elective liver surgery: A preliminary study.

作者信息

Mekhenane Nesrine, Cormi Clement, Allemang-Trivalle Arnaud, Acidi Belkacem, Cherqui Daniel, Vibert Eric, Allard Marc-Antoine

机构信息

Centre Hépatobiliaire, Paul Brousse Hospital, Villejuif, France.

Chaire Innovation du Bloc Opératoire Augmenté (BOPA), AP-HP, Institut Mines-Telecom, Université Paris Saclay, Villejuif, France.

出版信息

Ann Hepatobiliary Pancreat Surg. 2025 Aug 31;29(3):279-285. doi: 10.14701/ahbps.25-089. Epub 2025 Jul 24.

DOI:10.14701/ahbps.25-089
PMID:40701645
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12377990/
Abstract

BACKGROUNDS/AIMS: Surgical data science (SDS) is an emerging discipline that aims to enhance the quality of interventional healthcare by capturing and analyzing intraoperative data. Our study focused on identifying human errors (HEs) and adverse events (AEs) during elective liver surgery using an SDS-based approach.

METHODS

Intraoperative data from 15 patients undergoing elective open liver resection were collected using an operating room data system (audio, room, and operative field videos) over a 6-month period in a tertiary hepatobiliary surgical center. Two independent researchers analyzed the data to identify HEs and AEs according to two distinct classifications.

RESULTS

A total of 154 HEs (median number per intervention: 7) and 42 AEs (33 minor, 9 major) were identified. All except one major AE were associated with HEs, while 15 minor AEs had no identifiable underlying HEs. The type of HEs significantly varied depending on the presence or absence of AEs. The majority of HEs (n = 128, 83.1%), which did not result in any AEs, primarily involved lapses in attention, whereas approximately half of the AEs were linked to failures in recognition.

CONCLUSIONS

This preliminary study indicates that failures in recognition were frequently associated with major AEs during elective liver resection, as per the SDS approach. Larger multicenter studies are necessary to confirm these findings and develop preventive strategies.

摘要

背景/目的:手术数据科学(SDS)是一门新兴学科,旨在通过收集和分析术中数据来提高介入性医疗保健的质量。我们的研究聚焦于采用基于SDS的方法识别择期肝脏手术期间的人为失误(HEs)和不良事件(AEs)。

方法

在一家三级肝胆外科中心,使用手术室数据系统(音频、手术室和手术视野视频)在6个月期间收集了15例行择期开放性肝切除术患者的术中数据。两名独立研究人员根据两种不同分类分析数据以识别HEs和AEs。

结果

共识别出154次人为失误(每次干预的中位数:7次)和42起不良事件(33起轻微,9起严重)。除1起严重不良事件外,所有不良事件均与人为失误相关,而15起轻微不良事件没有可识别的潜在人为失误。人为失误的类型根据不良事件的有无而有显著差异。大多数未导致任何不良事件的人为失误(n = 128,83.1%)主要涉及注意力不集中,而约一半的不良事件与识别失误有关。

结论

这项初步研究表明,根据SDS方法,在择期肝切除术中,识别失误经常与严重不良事件相关。需要更大规模的多中心研究来证实这些发现并制定预防策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/abc8/12377990/1eb4b24759ec/ahbps-29-3-279-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/abc8/12377990/1eb4b24759ec/ahbps-29-3-279-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/abc8/12377990/1eb4b24759ec/ahbps-29-3-279-f1.jpg

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