使用自然语言处理来评估癌症患者的护理目标对话
Melissa K Greene1, Gloria Broadwater2, Donna Niedzwiecki2
1Duke University School of Medicine, Durham, NC.
JCO clinical cancer informatics
|October 16, 2025
概括
改善癌症患者的治疗目标 (GOC) 文档质量与不那么积极的生命终端 (EOL) 护理有关. 中国政府的综合性说明与减少激进的EOL治疗相关,突出了改善患者护理的机会.
科学领域:
- 在瘤学瘤学.
- 抚慰性护理是一种缓解性护理.
- 医疗信息学 医疗信息学
背景情况:
- 医疗保健目标 (GOC) 讨论对于晚期严重疾病和生命终端 (EOL) 护理至关重要.
- 机构越来越多地追踪中国政府文件的频率和时间.
- 对中国政府文档内容质量的大规模评估是有限的.
研究的目的:
- 使用自然语言处理 (NLP) 来评估中国癌症患者的文档质量.
- 评估中国政府文档质量与癌症患者接受的终身护理之间的关联.
主要方法:
- 在2018年至2022年期间死亡的癌症患者的回顾性审查,以及在生命的最后一年中记录的GOC笔记.
- 确定了中国政府的八个关键组成部分 (疾病理解,信息偏好,预后披露,目标,恐惧,可接受的功能,权衡,家庭参与).
- 利用NLP寻找这些成分的存在,并评估与积极的EOL护理的关联.
主要成果:
- 2,031名患者符合纳入标准;只有5.4%的八个中华人民共和国成分被记录.
- 更全面的中国政府笔记与较低的积极EOL护理率相关 (例如,50.3%具有6-7组件,而73.2%具有0组件).
- 中国药物成分文档 (≤6对≥7成分) 和主要瘤部位是积极的EOL护理的独立预测因素.
结论:
- 更高质量和更全面的中国政府文档与癌症患者积极的EOL护理的可能性降低有关.
- 提高中国政府对话的质量和文档提供了一个积极影响EOL护理的机会.
- NLP提供了一种可扩展的方法来评估中国政府的文档质量.
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