Department of Internal Medicine, Rush University, 1725 West Harrison Street, Suite 010, Chicago, IL 60612, USA.
Agency for Healthcare Research and Quality, 5600 Fishers Lane, Mail Stop 06E53A, Rockville, MD 20857, USA.
Crit Care Clin. 2023 Oct;39(4):769-782. doi: 10.1016/j.ccc.2023.02.004. Epub 2023 Mar 27.
Predictive analytics based on artificial intelligence (AI) offer clinicians the opportunity to leverage big data available in electronic health records (EHR) to improve clinical decision-making, and thus patient outcomes. Despite this, many barriers exist to facilitating trust between clinicians and AI-based tools, limiting its current impact. Potential solutions are available at both the local and national level. It will take a broad and diverse coalition of stakeholders, from health-care systems, EHR vendors, and clinical educators to regulators, researchers and the patient community, to help facilitate this trust so that the promise of AI in health care can be realized.
基于人工智能的预测分析为临床医生提供了利用电子健康记录 (EHR) 中可用的大数据来改善临床决策,从而改善患者预后的机会。尽管如此,在促进临床医生和基于人工智能的工具之间的信任方面仍然存在许多障碍,限制了其当前的影响。潜在的解决方案可在地方和国家层面获得。需要来自医疗保健系统、EHR 供应商和临床教育者、监管机构、研究人员和患者群体的广泛而多样化的利益相关者联盟来帮助促进这种信任,以便实现人工智能在医疗保健中的承诺。