倦怠
工作流程
医学
交叉研究
临床试验
物理疗法
随机对照试验
产品(数学)
患者满意度
渡线
病人护理
梅德林
心理干预
患者数据
替代医学
护理部
研究设计
作者
Anand Chowdhury,Michele Casey,Jonathan Wilson,Kathryn I. Pollak,Benjamin A Goldstein,Armando Bedoya,Eric G Poon
标识
DOI:10.1093/jamia/ocag018
摘要
OBJECTIVE: This study aims to compare the effectiveness of 2 ambient AI scribe technologies in reducing physician burnout, improving workflow satisfaction, and enhancing documentation efficiency through a randomized crossover trial. MATERIALS AND METHODS: An open-label randomized crossover trial involving 160 outpatient clinicians was conducted at a tertiary academic medical center. Volunteers were randomized to 2 groups of 80 with 2 crossover periods. We assessed workflow satisfaction (1-7 scale), burnout (Copenhagen Burnout Index), and efficiency metrics (eg, electronic health record time outside scheduled hours, documentation time, etc.). Data was analyzed using Wilcoxon signed-rank tests and generalized linear mixed models. RESULTS: Surveys from 136 respondents were analyzed. Clinicians reported greater improvements in satisfaction with product B (2.51 points on a 7-point scale) compared to product A (1.91 points; mean difference: 0.60, 95% CI: 0.32-0.90). Both tools reduced personal and work burnout scores, but differences between tools were not meaningful. Product B demonstrated greater reductions in average minutes-in-notes per day compared to product A (B - A = -3.19 minutes; 95% CI -4.87 to -1.50). No meaningful differences were observed in pajama time or patient-related burnout. DISCUSSION: Both tools improved workflow satisfaction and reduced burnout, with product B showing superior performance in satisfaction and documentation time. However, efficiency metrics like pajama time were largely unaffected, potentially due to participant selection bias and the study period's timing. CONCLUSION: Product B yielded greater satisfaction and time savings compared to product A, though both tools effectively reduced physician burnout and improved workflow satisfaction.
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