Balloch Jasmine, Sridharan Shankar, Oldham Geralyn, Wray Jo, Gough Paul, Robinson Robert, Sebire Neil J, Khalil Saleh, Asgari Elham, Tan Christopher, Taylor Andrew, Pimenta Dominic
TORTUS AI, Holborn Town Hall, London, UK.
Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK.
Future Healthc J. 2024 Jun 26;11(3):100157. doi: 10.1016/j.fhj.2024.100157. eCollection 2024 Sep.
Electronic health records (EHRs) have contributed to increased workloads for clinicians. Ambient artificial intelligence (AI) tools offer potential solutions, aiming to streamline clinical documentation and alleviate cognitive strain on healthcare providers.
To assess the clinical utility of an ambient AI tool in enhancing consultation experience and the completion of clinical documentation.
Outpatient consultations were simulated with actors and clinicians, comparing the AI tool against standard EHR practices. Documentation was assessed by the Sheffield Assessment Instrument for Letters (SAIL). Clinician experience was measured through questionnaires and the NASA Task Load Index.
AI-produced documentation achieved higher SAIL scores, with consultations 26.3% shorter on average, without impacting patient interaction time. Clinicians reported an enhanced experience and reduced task load.
The AI tool significantly improved documentation quality and operational efficiency in simulated consultations. Clinicians recognised its potential to improve note-taking processes, indicating promise for integration into healthcare practices.
电子健康记录（EHRs）导致临床医生的工作量增加。环境人工智能（AI）工具提供了潜在的解决方案，旨在简化临床文档记录并减轻医疗服务提供者的认知负担。
评估一种环境AI工具在提升会诊体验和完成临床文档记录方面的临床效用。
使用演员和临床医生模拟门诊会诊，将AI工具与标准电子健康记录操作进行比较。通过谢菲尔德信件评估工具（SAIL）对文档记录进行评估。通过问卷调查和NASA任务负荷指数来衡量临床医生的体验。
由AI生成的文档记录获得了更高的SAIL分数，会诊平均缩短了26.3%，且不影响医患互动时间。临床医生报告称体验得到了提升，任务负荷有所减轻。
该AI工具在模拟会诊中显著提高了文档记录质量和运营效率。临床医生认可其改善记录过程的潜力，表明其有望融入医疗实践。
