Longitudinal effects of ambient artificial intelligence scribe use on documentation burden and financial productivity in primary care: a quasi-experimental study

Abstract Objectives To investigate the longitudinal effects of an ambient artificial intelligence (AI) scribe use in primary care on outcomes related to documentation time, note writing patterns, and clinician financial productivity. Materials and Methods We conducted a quasi-experimental study with an interrupted time-series design to ascertain the effect of AI scribe use on note writing time, time outside of scheduled hours (TOSH), pajama time (5:30PM-7:00aM), note length, note closure <24 h, and work relative value units (wRVU). For each primary care clinician (physician, advanced practice provider), date of initial access was day 0; each measure was calculated for 150 days prior (pre-period) and after (post-period) day zero. Results Two hundred and twenty clinicians (mean age = 43.7, 70.9% females; 56.4% physicians) from 36 clinics, conducting 314 845 patient encounters were included. Compared to the pre-period, there was 7% decrease in note writing time at day 0 (incidence rate ratio [IRR] 0.93, 95% credible interval [CI] [0.89, 0.98]), increasing to 16% decrease by day 150 (IRR 0.84, 95% CI [0.82, 0.87]). There was no change in pajama time, TOSH, or wRVU at day 0; however, at day 150, there was a 19% decrease in pajama time (0.81, 95% CI [0.73, 0.90]), 13% decrease in TOSH (0.87, 95% CI [0.77, 0.98]), and a 2% increase in wRVU (1.02, 95% CI [1.01, 1.04]). At day 0, there was a 5% increase in note closures (1.05, 95% CI [1.02, 1.08]), with no difference to pre-period levels by day 150. There were no changes in note length at day 0 or day 150. Discussion and Conclusion There were persistent changes in AI scribe use measures over time as clinicians situated these tools within their workflows.