手术室多模态数据管理共识:确定数据驱动手术的研究重点

A. García Vázquez, J. Verde, Hernandez Lara Ariosto, D. Mutter, L. Swanstrom
{"title":"手术室多模态数据管理共识:确定数据驱动手术的研究重点","authors":"A. García Vázquez, J. Verde, Hernandez Lara Ariosto, D. Mutter, L. Swanstrom","doi":"10.1097/as9.0000000000000459","DOIUrl":null,"url":null,"abstract":"\n \n This study aimed to identify research areas that demand attention in multimodal data-driven surgery for improving data management in minimally invasive surgery.\n \n \n \n New surgical procedures, high-tech equipment, and digital tools are increasingly being introduced, potentially benefiting patients and surgical teams. These innovations have resulted in operating rooms evolving into data-rich environments, which, in turn, requires a thorough understanding of the data pipeline for improved and more intelligent real-time data usage. As this new domain is vast, it is necessary to identify where efforts should be focused on developing seamless and practical data usage.\n \n \n \n A modified electronic Delphi approach was used; 53 investigators were divided into the following groups: a research group (n=9) for problem identification and a narrative literature review, a medical and technical expert group (n=14) for validation, and an invited panel (n=30) for two electronic survey rounds. Round 1 focused on a consensus regarding bottlenecks in surgical data science areas and research gaps, while round 2 prioritized the statements from round 1, and a roadmap was created based on the identified essential and very important research gaps.\n \n \n \n Consensus panelists have identified key research areas, including digitizing operating room (OR) activities, improving data streaming through advanced technologies, uniform protocols for handling multimodal data, and integrating AI for efficiency and safety. The roadmap prioritizes standardizing OR data formats, integrating OR data with patient information, ensuring regulatory compliance, standardizing surgical AI models, and securing data transfers in the next generation of wireless networks.\n \n \n \n This work is an international expert consensus regarding the current issues and key research targets in the promising field of data-driven surgery, highlighting the research needs of many operating room stakeholders with the aim of facilitating the implementation of novel patient care strategies in minimally invasive surgery.\n","PeriodicalId":503165,"journal":{"name":"Annals of Surgery Open","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Consensus for Operating Room Multimodal Data Management: Identifying Research Priorities for Data-Driven Surgery\",\"authors\":\"A. García Vázquez, J. Verde, Hernandez Lara Ariosto, D. Mutter, L. Swanstrom\",\"doi\":\"10.1097/as9.0000000000000459\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n \\n This study aimed to identify research areas that demand attention in multimodal data-driven surgery for improving data management in minimally invasive surgery.\\n \\n \\n \\n New surgical procedures, high-tech equipment, and digital tools are increasingly being introduced, potentially benefiting patients and surgical teams. These innovations have resulted in operating rooms evolving into data-rich environments, which, in turn, requires a thorough understanding of the data pipeline for improved and more intelligent real-time data usage. As this new domain is vast, it is necessary to identify where efforts should be focused on developing seamless and practical data usage.\\n \\n \\n \\n A modified electronic Delphi approach was used; 53 investigators were divided into the following groups: a research group (n=9) for problem identification and a narrative literature review, a medical and technical expert group (n=14) for validation, and an invited panel (n=30) for two electronic survey rounds. Round 1 focused on a consensus regarding bottlenecks in surgical data science areas and research gaps, while round 2 prioritized the statements from round 1, and a roadmap was created based on the identified essential and very important research gaps.\\n \\n \\n \\n Consensus panelists have identified key research areas, including digitizing operating room (OR) activities, improving data streaming through advanced technologies, uniform protocols for handling multimodal data, and integrating AI for efficiency and safety. The roadmap prioritizes standardizing OR data formats, integrating OR data with patient information, ensuring regulatory compliance, standardizing surgical AI models, and securing data transfers in the next generation of wireless networks.\\n \\n \\n \\n This work is an international expert consensus regarding the current issues and key research targets in the promising field of data-driven surgery, highlighting the research needs of many operating room stakeholders with the aim of facilitating the implementation of novel patient care strategies in minimally invasive surgery.\\n\",\"PeriodicalId\":503165,\"journal\":{\"name\":\"Annals of Surgery Open\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Annals of Surgery Open\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1097/as9.0000000000000459\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Surgery Open","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1097/as9.0000000000000459","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本研究旨在确定多模态数据驱动手术中需要关注的研究领域,以改进微创手术中的数据管理。 新的外科手术程序、高科技设备和数字工具正被越来越多地引入,为患者和手术团队带来了潜在的益处。这些创新导致手术室演变为数据丰富的环境,这反过来又要求对数据管道有透彻的了解,以改进和更智能地实时使用数据。由于这一新领域十分广阔,因此有必要确定在开发无缝、实用的数据使用方面应重点关注哪些方面。 我们采用了一种改良的电子德尔菲方法;53 名调查人员被分为以下几组:一个研究小组(9 人)负责问题识别和叙述性文献回顾,一个医学和技术专家组(14 人)负责验证,一个特邀小组(30 人)负责两轮电子调查。第一轮的重点是就外科数据科学领域的瓶颈和研究缺口达成共识,第二轮则对第一轮的陈述进行了优先排序,并根据确定的基本和非常重要的研究缺口绘制了路线图。 共识小组成员确定了关键研究领域,包括手术室(OR)活动数字化、通过先进技术改进数据流、处理多模态数据的统一协议,以及整合人工智能以提高效率和安全性。路线图优先考虑手术室数据格式的标准化、手术室数据与患者信息的整合、确保监管合规、手术人工智能模型的标准化以及下一代无线网络数据传输的安全性。 这项工作是国际专家就数据驱动手术这一前景广阔的领域当前存在的问题和关键研究目标达成的共识,强调了许多手术室利益相关者的研究需求,旨在促进微创手术中新型患者护理策略的实施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Consensus for Operating Room Multimodal Data Management: Identifying Research Priorities for Data-Driven Surgery
This study aimed to identify research areas that demand attention in multimodal data-driven surgery for improving data management in minimally invasive surgery. New surgical procedures, high-tech equipment, and digital tools are increasingly being introduced, potentially benefiting patients and surgical teams. These innovations have resulted in operating rooms evolving into data-rich environments, which, in turn, requires a thorough understanding of the data pipeline for improved and more intelligent real-time data usage. As this new domain is vast, it is necessary to identify where efforts should be focused on developing seamless and practical data usage. A modified electronic Delphi approach was used; 53 investigators were divided into the following groups: a research group (n=9) for problem identification and a narrative literature review, a medical and technical expert group (n=14) for validation, and an invited panel (n=30) for two electronic survey rounds. Round 1 focused on a consensus regarding bottlenecks in surgical data science areas and research gaps, while round 2 prioritized the statements from round 1, and a roadmap was created based on the identified essential and very important research gaps. Consensus panelists have identified key research areas, including digitizing operating room (OR) activities, improving data streaming through advanced technologies, uniform protocols for handling multimodal data, and integrating AI for efficiency and safety. The roadmap prioritizes standardizing OR data formats, integrating OR data with patient information, ensuring regulatory compliance, standardizing surgical AI models, and securing data transfers in the next generation of wireless networks. This work is an international expert consensus regarding the current issues and key research targets in the promising field of data-driven surgery, highlighting the research needs of many operating room stakeholders with the aim of facilitating the implementation of novel patient care strategies in minimally invasive surgery.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信