在癌症患者的急性护理之前的症状模式
Chichi Chang1, Jie Jane Chen2, Jean Feng3
1Bakar Computational Health Sciences Institute, University of California, San Francisco.
JAMA network open
|April 22, 2025
概括
患有癌症的患者通常由于症状负担而经历无计划的急性护理. 这项研究使用自然语言处理 (NLP) 来识别急性护理前的症状,揭示了患者群体之间的差异.
科学领域:
- 在瘤学瘤学.
- 医疗保健服务研究 医疗服务研究
- 数据科学数据科学数据科学
背景情况:
- 患有癌症的患者由于疾病或治疗并发症,经常需要计划外的急性护理 (急诊室访问,住院).
- 了解这些急性护理事件之前的症状模式对于改善患者的治疗结果和生活质量至关重要.
- 在不同患者群体中表征这些前面的症状及其记录方面存在知识差距.
研究的目的:
- 在癌症患者急性护理接触前30天记录的症状的特征.
- 根据社会人口统计学和癌症相关特征量化症状记录的差异.
主要方法:
- 在一个单一的三级医疗机构进行了回顾性队列研究.
- 自然语言处理 (NLP) 分析了临床文档,以识别急性护理之前的症状.
- 后勤回归检查了患者/癌症特征和症状负担之间的关联.
主要成果:
- 分析了超过7万次急症护理访问,揭示了超过85万次记录的症状.
- 疼痛,恶心和吐是最常见的症状.
- 女性患者,种族/族裔少数群体和医疗补助保险患者在急性护理之前记录的症状负担更高.
结论:
- 该研究确定了癌症患者急性护理之前的常见症状,并突出了症状记录中的差异.
- 需要进一步的研究来开发能够减少患者负担和急性护理利用率的干预措施.
- 改善症状识别和记录是提高护理质量和患者结果的关键.
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