自然语言处理应用于后急性护理环境中的临床文档:一个范围审查
Danielle Scharp1, Mollie Hobensack1, Anahita Davoudi2
1Columbia University School of Nursing, New York, NY, USA.
Journal of the American Medical Directors Association
|October 14, 2023
概括
自然语言处理 (NLP) 在后急性护理中正在出现. 未来的研究应该使用NLP与标准化数据来改善患者护理和公平,整合社会行为因素以获得更好的健康结果.
科学领域:
- 临床信息学 临床信息学
- 医疗保健服务研究 医疗服务研究
- 自然语言处理自然语言处理.
背景情况:
- 后急性护理 (PAC) 设置产生了广泛的自由文本临床笔记.
- 利用自然语言处理 (NLP) 来利用这些非结构化数据可以增强患者的护理和研究.
- 目前在PAC中的NLP应用有限,但显示出潜力.
研究的目的:
- 对NLP应用于急症后护理中的自由文本临床笔记进行范围审查.
- 确定NLP在这些环境中的当前用途,局限性和未来研究方向.
主要方法:
- 按照PRISMA-ScR指南进行了系统范围审查.
- 在2023年2月在PubMed,CINAHL和Embase中进行了搜索.
- 包括的研究使用了量化设计,将NLP应用于PAC环境中的临床文档.
主要成果:
- 包括21项研究,主要涉及家庭医疗保健.
- 大多数研究都专注于预测急性护理利用率和药物错误等负面结果.
- 报告指出,数据有限,许多研究缺乏人口统计细节和标准化术语;只有8项研究纳入了社会行为变量.
结论:
- 在急性后护理中NLP的应用处于早期阶段.
- 未来的研究应该使用标准化术语,并纳入社会行为决定因素,以实现公平和全面的护理.
- 将NLP与预测模型相结合,可以识别有风险的患者,促进及时干预.
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