在电子健康记录系统中识别人工智能辅助临床决策支持的实施促进者和障碍者
Joseph Finkelstein1, Aileen Gabriel2, Susanna Schmer3
1Department of Biomedical Informatics, University of Utah, 421 Wakara Way, Rm. 2028, Salt Lake City, UT, 84108, USA. Joseph.Finkelstein@utah.edu.
Journal of medical systems
|September 18, 2024
概括
在电子健康记录 (EHR) 中实施人工智能 (AI) 辅助的临床决策支持 (CDS) 需要仔细规划. 解决信任和透明度等障碍对于成功在医疗保健中采用人工智能至关重要.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 实施科学 实施科学
背景情况:
- 人工智能 (AI) 的进步正在推动AI支持的医疗保健技术的发展.
- 集成到电子健康记录 (EHR) 中的AI辅助临床决策支持 (CDS) 显示了改善临床护理的潜力.
- 在人工智能辅助的CDS实施中,社会技术方面的挑战可能会导致意想不到的后果和低于最佳的采用.
研究的目的:
- 通过方法评估48小时排放预测工具 (48DPT) 的实施,这是一款人工智能辅助的EHR CDS.
- 通过实施科学框架,识别影响48DPT采用和维护的障碍和促进者.
主要方法:
- 利用了RE-AIM (覆盖范围,有效性,采用,实施,维护) 和实施研究综合框架 (CFIR) 的框架.
- 分析了与参与使用48DPT的24个关键利益相关者的采访.
主要成果:
- 确定了关键的实施障碍:缺乏意识,对准确性和信任的担忧,有限的可访问性和不足的透明度.
- 确定了对于成功实施人工智能辅助的EHR CDS至关重要的促进者.
结论:
- 成功实施人工智能辅助的EHR CDS需要临床利益相关者尽早参与人工智能工具开发.
- 优先考虑透明度,可解释性,持续的用户教育和持续的反对于有效的AI工具集成和维护至关重要.
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