背景:手术从每个程序中生成大量数据。特别是视频数据为外科研究提供了重要的价值,临床结果评估,质量控制,和教育。数据生命周期受各种因素的影响,包括数据结构,收购,storage,和共享;数据使用和探索,最后是数据治理,其中包括与数据相关的所有道德和法律法规。手术数据科学的利益相关者普遍需要建立标准化框架,以解决此生命周期的各个方面,以确保数据质量和目的。
方法:成立了工作组,在来自学术界和工业界的48名代表中,包括临床医生,计算机科学家和行业代表。这些工作组的重点是:数据使用,数据结构,数据探索,和数据治理。经过工作组和小组讨论,进行了修改的Delphi过程。
结果:由此产生的Delphi共识为与手术视频数据相关的每个领域提供了概念化和结构化的建议。我们确定了数据生命周期中的关键利益相关者,并制定了全面的、容易理解,和广泛适用的数据利用指南。数据结构的标准化应包括格式和质量,数据源,文档,元数据,并说明数据中的偏见。为了促进科学数据探索,数据集应反映多样性,并保持适应未来的应用。数据治理必须对所有利益相关者透明,解决围绕数据的法律和道德考虑。
结论:这一共识提出了关于生成标准化和多样化手术视频数据库的基本建议。考虑参与数据生成和整个生命周期使用的多个利益相关者。遵循SAGES注释框架,我们为数据使用的标准化奠定了基础,结构,和探索。随后将详细探讨适当数据管理的要求。
Surgery generates a vast amount of data from each procedure. Particularly video data provides significant value for surgical research, clinical outcome assessment, quality control, and education. The data lifecycle is influenced by various factors, including data structure, acquisition, storage, and sharing; data use and exploration, and finally data governance, which encompasses all ethical and legal regulations associated with the data. There is a universal need among stakeholders in surgical data science to establish standardized frameworks that address all aspects of this lifecycle to ensure data quality and purpose.
Working groups were formed, among 48 representatives from academia and industry, including clinicians, computer scientists and industry representatives. These working groups focused on: Data Use, Data Structure, Data Exploration, and Data Governance. After working group and panel discussions, a modified Delphi process was conducted.
The resulting Delphi
consensus provides conceptualized and structured recommendations for each domain related to surgical video data. We identified the key stakeholders within the data lifecycle and formulated comprehensive, easily understandable, and widely applicable
guidelines for data utilization. Standardization of data structure should encompass format and quality, data sources, documentation, metadata, and account for biases within the data. To foster scientific data exploration, datasets should reflect diversity and remain adaptable to future applications. Data governance must be transparent to all stakeholders, addressing legal and ethical considerations surrounding the data.
This
consensus presents essential recommendations around the generation of standardized and diverse surgical video databanks, accounting for multiple stakeholders involved in data generation and use throughout its lifecycle. Following the SAGES annotation framework, we lay the foundation for standardization of data use, structure, and exploration. A detailed exploration of requirements for adequate data governance will follow.