Using an Ambient Artificial Intelligence Tool to Document Clinical Pharmacist Patient Encounters: Real-World Evidence...

Documentation burden in the electronic health record (EHR), including clinical note writing, inbox management, and order entry, contributes to clinician inefficiency and burnout. Ambient artificial intelligence (AI) documentation tools can generate draft clinical notes for clinician review and have been shown to reduce documentation burden among physicians and advanced practice providers; however, their impact on clinical pharmacists has not been described.

This retrospective, observational study evaluated changes in EHR efficiency and clinical productivity metrics among ambulatory care clinical pharmacists at a federally qualified health center during the 2 months before and after implementation of an ambient AI documentation tool. Outcomes included time in notes per day, time in notes per appointment, time in clinical review, number of clinical encounters per month, number of clinical interventions per month, and inbasket tasks completed per month. descriptive statistics characterized the cohorts. Wilcoxon signed-rank tests were used to compare EHR efficiency metrics, and paired t-tests were used to compare clinical productivity data between pre and postimplementation periods.

Nine ambient AI documentation tool users demonstrated a 31.17% reduction in median time spent documenting notes per day (38.5 vs. 26.5 min, p = 0.04). Ambient AI users showed an average increase of approximately 33 visits per 1.0 full-time equivalent (FTE) per month, whereas nonusers saw an increase of about 17 visits per 1.0 FTE per month during the same period, though neither of these changes were statistically significant.

Ambient AI documentation tools were associated with reduced documentation time among ambulatory care clinical pharmacists and may enable increased clinical capacity. These findings provide early implementation evidence supporting the use of ambient AI documentation tools in pharmacy practice, demonstrating feasibility and measurable workflow impact in the ambulatory care setting.