An Evaluation of Epic EHR AI Outpatient Chart Summarization

NCT07438743 | Active Not Recruiting

• 1 other identifier: IRB-26-0066
• Study Type: interventional
• Target: 284
• Locations: 1 country
• Sites: 1

Brief 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.

Conditions

Quality Improvement

Keywords

Physician Task Load; Professional Fulfillment; Artificial Intelligence; Chart Summarization; System Usability

Outcome Measures

Primary Outcomes (1)

• Change from Baseline Physician Task Load

  Physician task load adapted from the NASA Task Load Index (TLX), a validated tool for assessing EHR-related cognitive task load in four sub-scales (mental demand, temporal demand, physical demand, and effort). This outcome is adapted to capture the task of pre-charting, defined for this study as the practice of reviewing patient information in the EHR before a patient visit to prepare for the encounter. Each sub-scale is rated from 0 (low) to 100 (high) and is aggregated to a 0-400 point scale. No patient level information will be collected for this outcome measure.

  Baseline and 90 days after initial exposure to the intervention

Secondary Outcomes (10)

• Change in Modified Total Chart Time Per Encounter

  Baseline, after 60 days of exposure to the intervention, and after 90 days of exposure to the intervention.

• Change from Baseline Professional Fulfillment Index Score

  Baseline and 90 days after initial exposure to the intervention

• Change from Baseline Self-Reported Pre-Charting Effectiveness

  Baseline and 90 days from initial exposure to the intervention

• Provider Satisfaction Scores

  90 days after initial exposure to the intervention

• System Usability Scale

  90 days from initial exposure to the intervention

Study Arms (2)

Intervention Arm

EXPERIMENTAL

Participants in this arm will have access to Epic's outpatient chart summarization tool and will continue their usual clinical practice, supported by the generative AI tool, which is integrated within the EHR. The tool provides a summary for providers and does not provide clinical decision support. They have access to an educational module and tipsheet, and weekly town halls to help with any questions for the first three weeks of the trial.

Other: GenAI Chart Summarization

Care As Usual

NO INTERVENTION

Participants in this arm will not have access to chart summarization tool and will continue their usual clinical practice.

Interventions

GenAI Chart Summarization OTHER

Epic's generative AI chart summarization tool summarizes a subset of a patient's notes. Use of the tool is optional and intended solely to provide a summary for providers and does not provide clinical decision support. The system automatically selects recent notes or a provider can manually select specific notes of interest. The number of notes summarized is limited by the character constraints of the EHR, 24,000 English characters or 30 notes. The system uses AI to generate a short summary of relevant information. The summaries are meant to be used as a tool to aid providers and are not intended to be placed in clinical notes. The summaries created are currently not stored in the patient's chart.

Intervention Arm

Eligibility Criteria

• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)

You may qualify 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 may not qualify if:

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

Sponsors & Collaborators

• University of California, Los Angeles: lead

Study Sites (1)

University of California, Los Angeles

Los Angeles, California, 90095, United States

Location

Related Publications (6)

• Carolus, A., Koch, M. J., Straka, S., Latoschik, M. E., & Wienrich, C. (2023). MAILS-Meta AI literacy scale: Development and testing of an AI literacy questionnaire based on well-founded competency models and psychological change-and meta-competencies. Computers in Human Behavior: Artificial Humans, 1(2), 100014.

  BACKGROUND

• Koch MJ, Carolus A, Wienrich C, Latoschik ME. Meta AI literacy scale: Further validation and development of a short version. Heliyon. 2024 Oct 22;10(21):e39686. doi: 10.1016/j.heliyon.2024.e39686. eCollection 2024 Nov 15.

  PMID: 39524814 BACKGROUND

• Quigley DD, Elliott MN, Qureshi N, Predmore Z, Hays RD. Associations of the Consumer Assessment of Healthcare Providers and Systems (CAHPS) Clinician and Group Survey Scores with Interventions and Site, Provider, and Patient Factors: A Systematic Review of the Evidence. J Patient Exp. 2024 Oct 13;11:23743735241283204. doi: 10.1177/23743735241283204. eCollection 2024.

  PMID: 39403289 BACKGROUND

• Melnick ER, Harry E, Sinsky CA, Dyrbye LN, Wang H, Trockel MT, West CP, Shanafelt T. Perceived Electronic Health Record Usability as a Predictor of Task Load and Burnout Among US Physicians: Mediation Analysis. J Med Internet Res. 2020 Dec 22;22(12):e23382. doi: 10.2196/23382.

  PMID: 33289493 BACKGROUND

• Trockel M, Bohman B, Lesure E, Hamidi MS, Welle D, Roberts L, Shanafelt T. A Brief Instrument to Assess Both Burnout and Professional Fulfillment in Physicians: Reliability and Validity, Including Correlation with Self-Reported Medical Errors, in a Sample of Resident and Practicing Physicians. Acad Psychiatry. 2018 Feb;42(1):11-24. doi: 10.1007/s40596-017-0849-3. Epub 2017 Dec 1.

  PMID: 29196982 BACKGROUND

• Lukac PJ, Turner W, Vangala S, Chin AT, Khalili J, Shih YT, Sarkisian C, Cheng EM, Mafi JN. Ambient AI Scribes in Clinical Practice: A Randomized Trial. NEJM AI. 2025 Dec;2(12):10.1056/aioa2501000. doi: 10.1056/aioa2501000. Epub 2025 Nov 26.

  PMID: 41497288 BACKGROUND

Study Officials

• John N Mafi, MD, MPH

  Division of General Internal Medicine & Health Services Research, David Geffen School of Medicine at the University of California, Los Angeles

  PRINCIPAL INVESTIGATOR

• Paul J Lukac, MD, MBA, MS

  UCLA Health Information Technology, UCLA Health

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: INVESTIGATOR
• Purpose: HEALTH SERVICES RESEARCH
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Associate Professor of Medicine

Study Record Dates

• First Submitted: February 22, 2026
• First Posted: February 27, 2026
• Study Start: February 23, 2026
• Primary Completion: May 1, 2026
• Study Completion: May 1, 2026
• Last Updated: March 6, 2026

Record last verified: 2026-03

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)