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.
Keywords: artificial intelligence; burnout; clinical documentation; electronic health records; professional; randomized controlled trials.
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