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关键对话:一种以用户为中心的儿科重症监护病房病史采集聊天机器人方法。

Critical conversations: a user-centric approach to chatbots for history taking in the pediatric intensive care unit.

作者信息

Collins Candace, Fackler James, Sacco Melissa Jerdonek, Jacobs Maia

机构信息

Department of Anesthesiology and Critical Care Medicine, Johns Hopkins Hospital, Baltimore, MD, United States.

Department of Pediatrics, University of Virginia Health Children's, Charlottesville, VA, United States.

出版信息

Front Pediatr. 2025 Aug 12;13:1646989. doi: 10.3389/fped.2025.1646989. eCollection 2025.

Abstract

In this article, we describe the potential utility and design of chatbots to improve history taking in the pediatric intensive care unit (PICU). The fast-paced, high-stakes environment of the PICU often forces clinicians to obtain only enough information to make immediate clinical decisions. Specific barriers to comprehensive history taking include insufficient time, frequent interruptions, caring for a wide range of conditions, need for timely interventions, and language differences. We propose that chatbots could play a critical role in improving history taking in the PICU by collecting information related to a patient's current presentation and exploring areas that are commonly neglected, such as social histories. To explore the use of chatbots in the PICU setting, we will first describe the current scope of chatbots as medical history taking aids. Next, we will outline specific considerations for the development of chatbots for the PICU, including methods for involving users, such as patients, caregivers, and clinicians directly in the design, mitigating false information, and establishing safeguards for chatbot behavior. Finally, we will review methods to evaluate chatbots. The overall purpose of this perspective article is to 1) propose the PICU as a novel environment where chatbots could improve history taking and diagnostic reasoning and 2) delineate specific user-centric design and evaluation methods.

摘要

在本文中,我们描述了聊天机器人在改善儿科重症监护病房(PICU)病史采集方面的潜在效用和设计。PICU快节奏、高风险的环境常常迫使临床医生仅获取足够的信息来做出即时临床决策。全面病史采集的具体障碍包括时间不足、频繁中断、需要处理多种病情、需要及时干预以及语言差异。我们认为,聊天机器人通过收集与患者当前表现相关的信息并探索通常被忽视的领域,如社会史,在改善PICU病史采集中可以发挥关键作用。为了探索聊天机器人在PICU环境中的应用,我们首先将描述聊天机器人作为病史采集辅助工具的当前范围。接下来,我们将概述为PICU开发聊天机器人的具体注意事项,包括让用户(如患者、护理人员和临床医生)直接参与设计的方法、减少虚假信息以及为聊天机器人行为建立保障措施。最后,我们将回顾评估聊天机器人的方法。这篇观点文章的总体目的是:1)提出PICU是聊天机器人可以改善病史采集和诊断推理的新环境;2)阐述以用户为中心的具体设计和评估方法。

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