使用社会技术模型来了解危重婴儿败血症识别的挑战

ACI open Pub Date : 2022-07-01 DOI:10.1055/s-0042-1749318
D. Karavite, M. Harris, R. Grundmeier, L. Srinivasan, Gerald P. Shaeffer, Naveen Muthu
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摘要

客观的 本研究的目的是将社会技术模型应用于实现基于机器学习算法的系统的需求阶段,以支持新生儿重症监护室中的败血症识别。方法 我们在三个需求阶段活动中纳入了社会技术模型“患者安全工程2.0的安全性”中的组件:(1)半结构化访谈,(2)用户档案,和(3)系统用例。后果 31名新生儿重症监护室临床医生参加了半结构化访谈(11名护士、10名一线订购临床医生、5名研究员和5名主治医师)。访谈记录被编码,然后根据社会技术模型的组成部分(人员、环境、组织、任务、工具和技术、协作和结果)演绎地汇编成主题。访谈分析用于创建四个用户档案,定义败血症识别的责任、团队合作以及与败血症识别相关的属性。两个用户档案(护士、一线医嘱临床医生)包括基于败血症识别相关经验的变体。访谈分析用于开发代表临床败血症场景的三个系统用例。每个用例定义了前提条件、参与者和高级行动序列,并包括基于社会技术工作系统因素的变体,这些因素可能会使败血症识别复杂化。面试分析、用户档案和用例是支持社会技术设计的基础,支持所有后续以人为中心的设计方法,包括主题招聘、形成性设计、总结性用户测试和模拟测试。结论 社会技术模型的集成通过构建一系列社会技术组成部分以及这些组成部分在更广泛的工作系统中的相互联系来指导需求收集活动、分析和可交付成果。应用社会技术模型可以发现工作系统、过程和结果需求,否则使用传统的需求收集方法或临床决策支持设计方法很难捕捉或完全错过这些需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using a Sociotechnical Model to Understand Challenges with Sepsis Recognition among Critically Ill Infants
Objective The aim of the study is to apply a sociotechnical model to the requirements phase of implementing a machine learning algorithm-based system to support sepsis recognition in the neonatal intensive care unit. Methods We incorporated components from the sociotechnical model, Safety in Engineering for Patient Safety 2.0, in three requirements phase activities: (1) semi-structured interviews, (2) user profiles, and (3) system use cases. Results Thirty-one neonatal intensive care unit clinicians participated in semi-structured interviews (11 nurses, 10 front line ordering clinician, five fellows, and five attending physician). Interview transcripts were coded and then compiled into themes deductively based on components from the sociotechnical model (persons, environment, organization, tasks, tools and technology, collaboration, and outcomes). The interview analysis was used to create four user profiles defining responsibilities in sepsis recognition, team collaboration, and attributes relevant to sepsis recognition. Two user profiles (nurse, front line ordering clinician) included variants based on experience relevant to sepsis recognition. The interview analysis was used to develop three system use cases representing clinical sepsis scenarios. Each use case defines the precondition, actors, and high-level sequence of actions, and includes variants based on sociotechnical works system factors that can complicate sepsis recognition. The interview analysis, user profiles, and use cases serve as the foundation for supporting sociotechnical design to all subsequent human-centered design methods including subject recruitment, formative design, summative user testing, and simulation testing. Conclusion Integration of the sociotechnical model-guided requirements gathering activities, analysis, and deliverables by framing a range of sociotechnical components and the interconnectedness of these components in the broader work system. Applying the sociotechnical model resulted in discovering work system, process, and outcome requirements that would otherwise be difficult to capture, or missed entirely, using traditional requirements gathering methods or approaches to clinical decision support design.
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