The Effect of Ambient Artificial Intelligence Scribes on Trainee Documentation Burden

Abstract

Background

Ambient artificial intelligence scribes have become widespread commercial products in the era of generative artificial intelligence. While studies have examined the effect of these tools on the experience of attending physicians, little evidence is available regarding their use by resident physician trainees.

Objectives

To assess trainee experience with an ambient artificial intelligence scribe using measures of usability, acceptability, and documentation burden.

Methods

This prospective observational study enrolled 47 trainees in a 2-month pilot. Pre/postsurveys were conducted with the NASA Task Load Index (NASA-TLX, raw unweighted form, pre/post, for cognitive load during the documentation), the System Usability Scale (post; general usability), the Net Promoter Score (post; acceptability), and the AMIA TrendBurden Survey (pre/post; documentation burden). Electronic health record utilization metrics were obtained from Epic Signal for both the pilot period and a 6-month baseline.

Results

In total, 43/47 (91.5%) of participants adopted the intervention in practice. NASA-TLX scores improved from 56.3 to 43.3 (p < 0.001), and multiple items on the TrendBurden survey improved with high measures of acceptability. No significant difference in time spent on notes activity per note written was observed, with a median increase of 0.4 minutes (p = 0.568).

Conclusion

Trainee use of an ambient artificial intelligence scribe was associated with improvements in documentation burden. Additional research on the effect of this technology on trainee learning and expertise development is needed.

Keywords

generative artificial intelligence - artificial intelligence - graduate medical education - electronic health record - health information technology

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