This study is in progress, not accepting new patients

An Evaluation of Epic EHR AI Outpatient Chart Summarization

a study on Quality Improvement

Summary

Location
at UCLA
Dates
study started
study ends around
Principal Investigator
by John N Mafi, MD, MPH (ucla)Paul J Lukac, MD, MBA, MS (ucla)

Description

Summary

This is a RCT of 284 outpatient physicians at a large academic health system, randomized 1:1 to an electronic health record (EHR) produced generative AI outpatient chart summarization tool or a usual-care control group. The 90 day study will observe the effects of the tool prior to system-wide roll out of the tool.

Official Title

Epic Generative Artificial Intelligence Chart Summarization Tool to Reduce Ambulatory Provider Cognitive Task Load: A Randomized Controlled Trial

Details

The primary aim of this study is to evaluate the impact of an EHR developed generative AI outpatient chart summarization tool on self-reported physician-task load score (PTL), comparing the tool to a control group. Exploratory outcomes include EHR-derived time metrics (Caboodle and Signal), Professional fulfillment Index (PFI), usability (SUS), provider satisfaction and productivity, and patient experience item results from CG-CAHPS. We will also evaluate whether AI literacy modifies adoption and effect of the tool using the short-form Meta AI Literacy Scale (MAILS). On an exploratory basis, we will also perform adjustments based on provider specialty, access to an ambient-listening AI scribe, panel complexity, provider age group, provider sex, and time-varying effects by month over the study period.

Enrolled participants are randomized to one of two groups. Randomization will be stratified by whether the participant has an active AI scribe license, and covariate-constrained randomization will be performed within strata to improve balance on baseline PTL (NASA-TLX-adapted score) and a modified baseline chart review time (Caboodle-derived). Due to the nature of the intervention, participants cannot be blinded to group assignment.

The primary purpose of the initiative is to improve quality, efficiency, and business operations at University of California, Los Angeles (UCLA) Health and will inform the operational implementation of the tool across all providers within the UCLA Health System. Nevertheless, the UCLA study team plans to rigorously examine and publish the impact of this intervention across the health system, which is why the study team pre-registered the initiative.

Keywords

Quality Improvement, Physician Task Load, Professional Fulfillment, Artificial Intelligence, Chart Summarization, System Usability, GenAI Chart Summarization

Eligibility

You can join if…

  • Ambulatory care providers within the UCLA Health system including physicians and advanced practice providers (APPs), such as nurse practitioners and physician assistants with at least one half-day clinic session per week.
  • Providers complete baseline pre-survey

You CAN'T join if...

• Trainee providers (e.g., residents, medical students), and psychologists

Location

  • University of California, Los Angeles
    Los Angeles California 90095 United States

Lead Scientists at University of California Health

  • John N Mafi, MD, MPH (ucla)
    Dr. John N. Mafi is an Associate Professor at UCLA's David Geffen School of Medicine and Adjunct Physician Policy Researcher at RAND Corporation, where he leads a health services research program focused on evaluating healthcare innovations and technologies to improve care value for older adults.
  • Paul J Lukac, MD, MBA, MS (ucla)
    HS Assistant Clinical Professor, Pediatrics, Medicine. Authored (or co-authored) 8 research publications

Details

Status
in progress, not accepting new patients
Start Date
Completion Date
(estimated)
Sponsor
University of California, Los Angeles
ID
NCT07438743
Study Type
Interventional
Participants
Expecting 284 study participants
Last Updated