Evaluation of an Ambient Artificial Intelligence Documentation Platform for Clinicians

The increase of electronic health record (EHR) work negatively impacts clinician well-being. One potential solution is incorporating an ambient artificial intelligence (AI) documentation platform.

To understand clinician experience before and after implementing ambient AI. Design, Setting, and Participants: This quality improvement study was a pilot evaluation with before and after survey and EHR metrics conducted at a large health care organization in Northern and Central California. Clinicians were purposively sampled to be representative of region and specialty. Ambient AI was implemented in April 2024 with EHR data from 3 months before and after implementation. Data were analyzed from May to September 2024. Exposure: Ambient AI access. Main Outcomes and Measures: Metrics of time were examined in notes per appointment, off-hour EHR activities (5:30 pm to 7:00 am on weekdays and nonscheduled weekends and holidays), documentation note length, progress note length, NASA Task Load Index (NASA-TLX) score, mini-Z burnout question, and overall experience. It was hypothesized that time in notes per appointment would decrease and clinical well-being would improve. Logistic regression and linear mixed-effect models were used.