开发一种人工智能工具来推导初级保健患者健康的社会决定因素:来自代码设计研讨会的定性发现
Stephanie Garies1,2, Simon Liang3, Karen Weyman3
1Department of Family & Community Medicine, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada sgaries@ucalgary.ca.
Annals of family medicine
|July 22, 2024
概括
初级保健医生需要健康的社会决定因素 (SDOH) 数据. 与临床医生共同设计人工智能 (AI) 工具是有效实施和在实践中使用数据缺口的关键.
科学领域:
- 医疗信息学 医疗信息学
- 初级保健研究研究初级保健研究
- 人工智能在医学中的应用
背景情况:
- 健康的社会决定因素 (SDOH) 对公平的初级保健至关重要,但被不一致地捕获.
- 电子健康记录 (EHR) 往往缺乏全面的SDOH数据,造成临床信息的差距.
- 人工智能 (AI) 为填补这些数据缺口提供了一个潜在的解决方案,但需要仔细,协作设计.
研究的目的:
- 探索初级保健临床医生在开发,实施和使用人工智能工具以从EHR数据中获得SDOH方面的观点.
- 了解与将人工智能驱动的SDOH数据集成到初级保健环境中的实际考虑和挑战.
- 为人工智能工具的协作设计提供信息,以便在临床实践中捕捉健康的社会决定因素.
主要方法:
- 在一个大型城市家庭健康团队中与初级保健临床医生进行半结构化研讨会.
- 利用感应性主题分析来解释参与者对拟议的基于AI的SDOH工具的反.
- 在4个研讨会中从15名参与者收集了关于EHR数据可用性和AI工具实施的见解.
主要成果:
- 临床医生发现了在电子健康记录中获得SDOH信息的重大差距和困难.
- 人工智能工具实施的关键主题以人,过程和技术为中心.
- 建议包括优先考虑特定的SDOH (例如,收入,住房) 并确保足够的资源,培训和患者沟通策略.
结论:
- 与最终用户,特别是初级保健临床医生共同设计对于开发有效的社会数据人工智能工具至关重要.
- 该研究为在初级保健中基于AI的SDOH工具的有意义设计和实施提供了实际指导.
- 解决临床医生对患者互动和数据验证的担忧对于成功采用人工智能至关重要.
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