医疗保健中的人工智能 - 了解患者信息需求和设计可理解的透明度:定性研究
Renee Robinson1, Cara Liday2, Sarah Lee3
1College of Pharmacy, Idaho State University, Anchorage, AK, US.
JMIR AI
|February 9, 2024
概括
人工智能 (AI) 和机器学习 (ML) 在医疗保健方面表现有前途,但患者和提供者对安全性和可用性存在担忧. 这项研究探讨了患者的需求和信任因素,以确保在糖尿病管理中安全使用AI/ML.
科学领域:
- 医疗保健技术 技术 医疗保健 技术
- 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:
- 人工智能 (AI) 和机器学习 (ML) 提供先进的计算方法来预测健康结果和解决患者需求.
- 虽然AI/ML技术对医疗保健,特别是糖尿病管理具有前景,但它给患者和提供者带来了可用性和安全性的担忧.
研究的目的:
- 了解患者在医疗保健中对AI/ML的信息和培训需求.
- 确定影响患者信任和AI/ML医疗保健应用的感知价值的因素.
- 确定如何最好地支持糖尿病患者安全和适当使用AI/ML设备和应用程序.
主要方法:
- 在阿拉斯加州,爱达荷州和弗吉尼亚州,与患者 (n=40) 和提供者 (n=6) 进行了重点小组 (n=9) 和采访 (n=3).
- 利用基于理论的数据收集,合成和分析,采用专题内容和常数比较分析.
- 应用了诱导方法来识别关键概念,如患者与提供者之间的互动,信任,准确性,价值,保证和信息透明度.
主要成果:
- 确定了有关患者对AI/ML信息的偏好,患者和提供者的培训需求以及影响信任的因素的关键主题和建议.
- 突出了参与者的建议,以改善设备功能,信息标签 (例如在线资源,24 / 7支持),访问实践设备,社区资源连接和简化显示/报警系统.
- 综合了患者和提供者对AI/ML启用设备和医疗保健管理中的应用的观点.
结论:
- 患者和提供者建议可以为联邦监督机构提供信息,以提高AI/ML技术在糖尿病监测中的使用和安全性.
- 通过知情监督来提高设备的安全性和有效性,可以在糖尿病管理中获得更好的患者结果.
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