对比传统和人工智能增强的策略来开发患者决策辅助工具:一个多个案例研究
Anik Giguere1,2, Delphine Auclair-Rochon2, Maéva Robin2
1Department of Family Medicine and Emergency Medicine, Université Laval, Québec City, Québec, Canada anik.giguere@fmed.ulaval.ca.
BMJ evidence-based medicine
|October 22, 2025
概括
人工智能 (AI) 可以通过生成更多基于证据的内容来增强患者决策辅助 (DA) 开发. 与传统方法相比,这种人工智能增强的战略产生了更丰富的信息,提高了效率和质量.
科学领域:
- 医疗信息学 医疗信息学
- 医疗决策的制定 医疗决策的制定
- 医疗保健中的人工智能
背景情况:
- 患者决策辅助工具 (DA) 对于明智的医疗保健选择至关重要.
- 传统的DA开发是资源密集型的,并且可能耗时.
- 人工智能 (AI) 的整合为优化 DA 内容创建提供了潜力.
研究的目的:
- 开发和评估人工智能驱动的提示,以生成平衡的,基于证据的患者DA内容.
- 将人工智能增强的DA开发策略与传统的人为主导的方法的有效性进行比较.
主要方法:
- 一项比较混合方法研究分析了来自太华库存的八个DA.
- 两位研究人员独立提取内容,并使用精致提示开发了AI增强的内容.
- 定量和定性分析比较了人工智能增强和传统的DA开发成果.
主要成果:
- 人工智能增强的策略产生了显著更高的独特的好处/危害的百分比,以选项为重点的DA (66%) 和以结果为重点的DA (47%).
- 证据搜索验证了人工智能生成的选项,证实了它们的好处,并排除了幻觉.
- 定性分析表明,人工智能增强的内容通常更丰富,尽管没有建议最佳组合.
结论:
- 人工智能驱动的提示工程可以显著提高患者DA开发的效率和质量.
- 这项研究为利用人工智能在创建基于证据的患者决策支持工具方面提供了实际见解.
- 进一步的研究可能会探索AI在建议DA内容最佳组合方面的作用.
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