实施人工智能驱动的床上传感器:老年医疗护理跨学科团队的观点
Cromwell G Acosta1, Yayan Ye2,3, Karen Lok Yi Wong2
1University of British Columbia Hospital-STAT Centre Inpatient, Vancouver Coastal Health, Vancouver, BC V6T 2B5, Canada.
Sensors (Basel, Switzerland)
|November 9, 2024
概括
对于老年人来说,人工智能睡眠监测是有希望的,但成功实施需要解决工作人员的担忧,并提供适当的培训,以获得更好的患者护理和康复结果.
科学领域:
- 老年医学 老年医学
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
背景情况:
- 睡眠对于住院老年人的康复至关重要.
- 人工智能驱动的睡眠监测提供了增强的患者评估和定制干预措施.
- 睡眠感应技术为临床决策提供实时睡眠数据.
研究的目的:
- 探索跨学科医疗保健团队在老年医院护理中实施人工智能驱动的睡眠监测 (Sleepsense) 的观点.
- 识别用于采用Sleepsense技术的障碍和促进因素.
- 评估Sleepsense对患者监测和康复的感知影响.
主要方法:
- 使用专注小组与医生,护士,护理助理和活动工作者进行定性研究.
- 数据收集的解释性描述方法.
- 以"实施研究综合框架" (CFIR) 为指导的专题分析.
主要成果:
- 睡眠感应被视为节省时间,数据驱动的工具,增强患者监测和评估.
- 关键障碍包括对变革的抵抗力和对患者舒适性和安全性的担忧.
- 实施的促进者包括适当的培训和积极的员工参与.
结论:
- 像Sleepsense这样的人工智能驱动的睡眠监测工具在老年护理中具有潜力,但需要谨慎的实施策略.
- 解决员工的担忧和促进跨学科的支持对于成功采用技术至关重要.
- 进一步的研究应侧重于优化团队支持,以改善创新吸收和患者康复结果.
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