可用性
文档
工作流程
梅德林
医疗保健
包裹体(矿物)
医学教育
医学
Web应用程序
磁盘格式化
心理学
卫生信息技术
健康档案
使用数据
网站的可用性
计算机科学
知识管理
护理部
健康信息学
循证医学
电子健康档案
万维网
应用心理学
可用性工程
多学科方法
作者
Samuel Atiku,Olufisayo Olakotan,Kehinde Owolanke
摘要
ABSTRACT Background Clinical documentation is a major contributor to physician burnout, and artificial intelligence (AI) scribes are increasingly being adopted to help reduce the burden of documentation. These tools automatically generate clinical notes from patient–provider conversations using speech recognition and natural language processing. However, their usability and effectiveness still remain an issue. Aim To synthesise the existing evidence on usability‐related barriers and facilitators influencing the adoption and use of AI scribes for clinical documentation in healthcare settings. Method The scoping review employed the methodology developed by Arksey and O'Malley in 2005 and further expanded by Levac and Colquhoun in 2010. We searched PubMed, Scopus, Ovid MEDLINE, and Web of Science to identify relevant studies published in English between 2015 and 2025. All findings were reported according to PRISMA guidelines for scoping reviews. Results Of 4588 identified records, 14 studies met the inclusion criteria and employed qualitative, quantitative, and mixed‐methods. AI scribes were consistently associated with reduced cognitive load, faster documentation, improved work–life balance, and positive user experience. However, common barriers included frequent errors, excessive note length, limited formatting options, and poor integration with electronic health records (EHR). Editing demands varied by clinician experience, with some finding that time savings were lost when substantial corrections were needed. Overall, usability was rated more favourably in routine or protocol‐driven visits, with mixed outcomes reported on long‐term burnout and workflow impact. Conclusion AI scribes show promise in reducing documentation burden and improving clinical workflow, but important usability challenges remain. Enhancing accuracy, streamlining integration, and allowing greater customization will be essential to support broader adoption and sustained use in clinical practice.
科研通智能强力驱动
Strongly Powered by AbleSci AI