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Related Experiment Video

Updated: Jul 11, 2026

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Randomized Trial Protocol: Epic Generative AI Chart Summarization Tool to Reduce Ambulatory Provider Cognitive Task

Aaron T Chin^1,2, Nina Zhu^1,2, Thomas Kingsley¹

¹UCLA Health Information Technology, UCLA Health, University of California, Los Angeles, Los Angeles, CA, United States.

Medrxiv : the Preprint Server for Health Sciences

|February 27, 2026

Summary

This summary is machine-generated.

This study tested a new AI tool to summarize patient charts for doctors. Early results suggest the generative AI chart summarizer may help reduce clinician workload, but more research is needed.

Keywords:

EHR chart review clinician burden generative AI randomized trial task load

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Area of Science:

Clinical Informatics
Artificial Intelligence in Healthcare
Medical Documentation

Background:

Electronic Health Record (EHR) documentation and chart review increase clinician workload and burnout.
Epic's generative AI chart summarizer tool aims to reduce pre-charting burden.
The impact of this AI tool has not been evaluated in randomized trials.

Purpose of the Study:

To evaluate if an Epic generative AI chart summarization tool reduces cognitive task load for ambulatory providers.
Comparison against usual care to assess the tool's effectiveness.

Main Methods:

A 90-day, two-arm, parallel-group randomized controlled trial involving ambulatory clinicians.
Randomization of clinicians 1:1 to either AI tool access or usual care.
Primary outcome: change in a 4-item physician task load (PTL) for pre-charting. Exploratory outcomes include EHR time metrics, burnout, and usability.

Main Results:

Data analysis will utilize clinician-level survey responses and aggregated EHR metrics.
No patient-level protected health information will be included.
Results will be disseminated through preprints and peer-reviewed publications.

Conclusions:

The study evaluates a pragmatic randomized controlled trial of an EHR-embedded generative AI tool for summarizing clinical notes.
Primary outcome is cognitive task load, with exploratory outcomes including time metrics, burnout, and usability.
Limitations include single-center design and unblinded, optional-use intervention.