Emergency Medicine Practitioners Overall Well-being Enhancement With Ambient AI Scribes

Impact of an ambient AI scribe on clinician well-being and professional fulfillment

时间窗: From enrollment to the end of maintenance phase at 24 weeks

A linear model will be used to describe the effect of Ambient tool introduction on our co-primary outcomes under the intention-to-treat framework with a random effects structure to describe within provider variability. While high or complete survey completion rates is expected, in the event that not all surveys are completed and returned, a primary analysis on completed surveys only will be performed, and perform sensitivity analyses accounting for potentially systematic survey non-response bias using a response weighting strategy, using provider, scheduling, and patient encounter characteristics to create survey response weights (within each survey time period), then reweighting observations to account for non-response patterns. In analyses for both co-primary outcomes, Wald type hypothesis tests for inferences on the overall Ambient treatment effect and compare p-values to 0.05 / 2 to conservatively account for multiple comparisons using Bonferroni's method will be performed.