临床实践中信息需求的转变:生成性AI在解决临床医生对特定背景知识需求方面的演变作用
Sachleen K Tuteja1,2, Elise L Boventer2,3, Abdulaziz Alkattan2,4
1Weinberg College of Arts and Science, Northwestern University, Evanston, IL, USA.
AMIA ... Annual Symposium proceedings. AMIA Symposium
|February 23, 2026
概括
生成型人工智能 (Gen AI) 可以满足不断变化的临床医生信息需求. 这项研究将分类学扩展到整合AI,改善患者护理和临床效率.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 临床决策支持 临床决策支持
背景情况:
- 持续的临床医生信息需求会影响医疗保健效率和患者的结果.
- 电子健康记录 (EHR) 的进步尚未完全解决这些差距.
- 现有的框架可能无法捕捉到现代临床信息要求的全部范围.
研究的目的:
- 探索临床医生不断变化的信息需求.
- 评估生成人工智能 (Gen AI) 在满足这些需求方面的潜力.
- 重新评估和扩展库里等人. (2003) 临床信息的分类学.
主要方法:
- 在哥伦比亚大学欧文医疗中心 (CUIMC) 进行了横截面调查.
- 分析了临床医生生成的Gen AI提示.
- 提示与已建立的Currie等人进行了比较. (2003年) 的分类学.
主要成果:
- 80%的Gen AI提示与现有的2003年分类类别保持一致.
- 20%的提示表明新出现的临床医生需求.
- 新出现的需求包括人工智能驱动的工作流程优化和公平性调查.
结论:
- 现有的临床信息分类学需要适应以整合AI.
- 一代人工智能有潜力弥合信息差距并增强临床决策支持.
- 扩展了库里等人. 分类学为在医疗保健中利用Gen AI提供了一个框架.
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