弥合患者差距:探索生成人工智能,以支持有意义的患者参与卫生技术评估
Manuel Cossio1, Ramiro E Gilardino2
1University of Barcelona, 08007 Barcelona, Spain.
Journal of comparative effectiveness research
|November 4, 2025
概括
简单的语言摘要 (PLS) 和患者摘要 (SIP) 可以提高医疗技术评估 (HTA) 的公平性和透明度. 整合人工智能需要仔细监督,以保持HTA中以患者为中心.
科学领域:
- 医疗技术评估 (HTA) 是指对医疗技术进行评估.
- 患者参与 患者参与
- 卫生沟通健康沟通
背景情况:
- 患者和公众参与现在是HTA的政策要求.
- 持续的沟通障碍阻碍了有效的患者参与.
- 欧洲的监管转变强调了可访问的信息.
研究的目的:
- 探索简单语言摘要 (PLS) 和患者信息摘要 (SIP) 在提高HTA方面的作用.
- 讨论HTA中信息可访问性,质量和可行性之间的平衡.
- 检查生成人工智能 (AI) 在制作患者友好的HTA摘要方面的潜力.
主要方法:
- 这是一篇综合当前文献和监管发展的观点文章.
- 在HTA框架内分析沟通策略.
- 在健康沟通中探索人工智能应用.
主要成果:
- PLS和SIP可以显著提高HTA的公平性和透明度.
- 在平衡可访问性,质量和可行性方面存在挑战.
- 生成型人工智能为可扩展的摘要制作提供了潜力,但需要仔细实施.
结论:
- 加强PLS和SIP的使用对于公平和透明的HTA至关重要.
- 负责地将人工智能整合到HTA中,需要强有力的监督和以患者为中心的方法.
- 未来的HTA框架必须优先考虑明确的沟通和患者参与.
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