生命末期护理规划对话的人工智能决策支持工具

Weiyi Xie, Robyn Butcher
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引用次数: 0

摘要

为什么这是一个问题? 临终关怀在生命的最后阶段为患者及其家属提供支持。生命末期谈话旨在帮助人们更好地了解自己的疾病预后和预期生存期,使他们能够就生命末期的护理做出明智的决定。 姑息关怀的重点是缓解严重或危及生命疾病患者的症状并改善其生活质量。大约 89% 的癌症等局限生命的疾病患者可以从姑息关怀中获益。然而,并非所有患者都能及时得到姑息治疗。 部分由于预后的不确定性和乐观偏差,生命末期的规划对话和姑息关怀决定并没有及早做出,以至于无法获得最大的益处。旨在提示或帮助识别那些可以从姑息治疗和/或临终规划中获益的患者的干预措施可以提高护理质量。 这项技术是什么? 基于人工智能(AI)的 "提示 "是一种决策支持工具,它使用提示和警报来帮助临床医生决定是否以及何时与患者讨论临终规划。 提示 "会向临床医生发送警报和/或提醒,以提示与短期内死亡风险较高的患者进行临终谈话。这些患者是通过电子健康记录(EHR)系统中的机器学习死亡率预测算法识别出来的。 针对癌症患者设计了两种基于人工智能的劝导工具。这两种工具都是在美国开发并经过内部验证的。 潜在影响是什么? 基于人工智能的提示有可能增加临床医生与患者之间的临终规划对话次数以及临终服务转介次数。 在临床工作流程中实施人工智能提示还能帮助临床医生更容易地识别有姑息关怀需求的病人。 我们还需要了解什么? 在撰写本文时,加拿大尚未批准使用基于人工智能的提示,也没有使用加拿大数据进行验证研究。 与许多人工智能算法一样,提示中使用的死亡率预测算法的有效性和通用性也存在不确定性。 由于临床医生对人工智能指导的态度和经验各不相同,临床医生对人工智能指导的接受程度也不明确,而且我们也没有发现任何从患者角度报告人工智能指导经验的研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial Intelligence Decision Support Tools for End-of-Life Care Planning Conversations
Why Is This an Issue? End-of-life care provides support for patients and their families during the last stage of life. End-of-life conversations aim to help people better understand their disease prognosis and expected survival, enabling them to make informed decisions regarding end-of-life care. Palliative care focuses on relieving symptoms and improving quality of life for patients with serious or life-threatening diseases. Approximately 89% of patients with life-limiting diseases, such as cancer, can benefit from palliative care. However, not all patients receive it in a timely manner. Due in part to prognostic uncertainty and optimism bias, end-of-life planning conversations and palliative care decisions do not occur early enough to have maximum benefit. Interventions that aim to prompt or help identify those patients who can benefit from palliative and/or end-of-life planning could improve the quality of care. What Is the Technology? An artificial intelligence (AI)–based “nudge” is a decision-making support tool that uses prompts and alerts to aid clinicians in deciding whether and when to discuss end-of-life planning with patients. The nudge sends alerts and/or reminders to clinicians to prompt end-of-life conversations with patients who are at high risk of short-term mortality. These patients are identified by machine learning mortality prediction algorithms incorporated in the electronic health record (EHR) system. Two AI-based nudges designed for patients with cancer were identified. Both tools were developed and internally validated in the US. What Is the Potential Impact? AI-based nudges have the potential to increase the number of end-of-life planning conversations between clinicians and patients as well as the number of referrals to end-of life services. Implementing the nudges into clinical workflows could also help clinicians more easily identify patients with palliative care needs. What Else Do We Need to Know? No AI-based nudges have been approved for use in Canada at the time of this writing nor have there been validation studies using Canadian data. As with many AI algorithms, there is uncertainty about the validity and generalizability of the mortality predictive algorithms used in the nudges. The acceptance of AI-based nudges by clinicians is unclear due to varying clinician attitudes and experiences with nudges and because we did not identify any studies that reported the experience of AI-based nudges from the patient perspective.
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