使用大型语言模型提高医疗效率:优化临床工作流程,提高患者护理效率
Satvik Tripathi1, Rithvik Sukumaran1, Tessa S Cook1
1Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Journal of the American Medical Informatics Association : JAMIA
|January 26, 2024
概括
大型语言模型 (LLM) 可以自动化医疗管理任务,减少临床医生的电子病历负担. 仔细实施确保LLMs补充,而不是取代,人类护理,以改善患者的治疗结果.
科学领域:
- 医疗信息学 医疗信息学
- 人工智能在医学中的应用
背景情况:
- 由于电子医疗记录,临床医生面临着巨大的行政负担.
- 需要对例行任务进行自动化,以提高效率并减少倦怠.
研究的目的:
- 探索大型语言模型 (LLM) 在自动化医疗管理任务方面的潜力.
- 确定在临床环境中LLM整合的具体应用和挑战.
主要方法:
- 文献综述和对医疗保健中的LLM能力的概念分析.
- 讨论潜在的用例,包括临床文档和事先授权.
主要成果:
- 法律法律管理系统可以增强临床文档,简化事先授权,个性化患者安排,改善患者教育和获得护理的机会.
- 关键考虑因素包括数据安全,患者隐私和监管合规性 (例如HIPAA).
结论:
- 当谨慎实施时,LLM提供了提高医疗保健效率和患者结果的巨大潜力.
- 整合LLMs应该增强,而不是取代,在患者护理中必不可少的人类因素.
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