Quality ImprovementNCT07438743
An Evaluation of Epic EHR AI Outpatient Chart Summarization
A study testing GenAI Chart Summarization in people with Quality Improvement, run by University of California, Los Angeles at 1 site in United States.
Trial 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. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Quality Improvement
- What is being tested?
- GenAI Chart Summarization
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 284 participants
- Where
- 1 siteUnited States
- Study dates
- 23 Feb 2026to May 2026
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Who may be able to join
- 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
Who cannot join
- Trainee providers (e.g., residents, medical students), and psychologists
Trial locations and contacts
1 site in 1 country.
United States1 site
University of California, Los Angeles
Los Angeles, California, 90095
About this study
Official title: Epic Generative Artificial Intelligence Chart Summarization Tool to Reduce Ambulatory Provider Cognitive Task Load: A Randomized Controlled Trial
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.
Read the detailed description
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.
- Conditions
- Quality Improvement
- Being tested
- GenAI Chart Summarization
- Keywords
- Physician Task Load, Professional Fulfillment, Artificial Intelligence, Chart Summarization, System Usability
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
GenAI Chart SummarizationOther
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.
| Study group | Role | What they receive |
|---|---|---|
| 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. Receives: 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. |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: Baseline and 90 days after initial exposure to the intervention
Secondary outcomes (10)
Change in Modified Total Chart Time Per Encounter
Using Caboodle, Epic's enterprise data warehouse, we will use a customized metric to measure clinician time spent reviewing the patient's chart. Based on internal validation where clinicians could access the chart summarization tool, the metric includes Caboodle Tier 1 activities corresponding to Clinical Review (all activities), Documentation limited to pre-charting activity only, and Other limited to Navigator-related activity, as well as the activity dedicated to the chart summarization tool. All note-writing, order entry, and encounter-signing activities are excluded. Time post checkout is also excluded. Change will be assessed relative to a 6-month retrospective baseline. No patient level information will be collected for this outcome measure.
Measured: 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
The Professional Fulfillment Index (PFI) is a validated 16-item instrument that uses a 5-point Likert scale (0-4) to measure professional fulfillment, work exhaustion, and interpersonal disengagement. Burnout is reported based on combined results of the work exhaustion and interpersonal disengagement subscales. A higher score indicates greater level of exhaustion. No patient level information will be collected for this outcome measure.
Measured: Baseline and 90 days after initial exposure to the intervention
Change from Baseline Self-Reported Pre-Charting Effectiveness
Providers will answer questions regarding self-reported effectiveness and efficiency in pre-charting. The questions use a 5-point Likert scale to measure these metrics, with a higher score indicating greater self-reported efficiency and effectiveness.
Measured: Baseline and 90 days from initial exposure to the intervention
Provider Satisfaction Scores
Self-reported satisfaction survey that includes physician reported effect of chart summarization tool on pre-charting efficiency and effectiveness, and other potential unintended consequences. No patient level information will be collected for this outcome.
Measured: 90 days after initial exposure to the intervention
System Usability Scale
The system usability scale (SUS) is a ten-item questionnaire that uses a 5-point Likert scale to measure different aspects of system usability. The total scale ranges from 0-100. A higher SUS score indicates higher usability.
Measured: 90 days from initial exposure to the intervention
Safety Events
Clinician-reported safety of AI-generated chart summaries, including perceived frequency of clinically significant errors and occurrence of major safety events during the intervention period. No patient level information will be collected for this outcome.
Measured: Over the 90 day period following after initial exposure to the intervention
Qualitative Tool-Specific EHR Feedback
Aggregated real-time feedback submitted by clinicians through the EHR- native summarization interface during the intervention period, including ratings of accuracy, completeness, and hallucinations. No patient level information will be collected for this outcome.
Measured: Over the 90 days following initial exposure to the intervention
Change from Baseline Consumer Assessment of Healthcare Providers and Systems Clinician & Group Survey (CG-CAHPS) Metric
The Consumer Assessment of Healthcare Providers and Systems Clinician \& Group Survey (CG-CAHPS) is a standardized patient feedback survey measuring experiences with providers. We will examine changes in the CG-CAHPS mean scores compared to 6 months prior to the intervention for the question "In the last 6 months, how often did this doctor seem to know the important information about your medical history".
Measured: Baseline and 90 days after initial exposure to the intervention
Change from Baseline Epic Signal (Activity) Metric: Time Outside Scheduled Hours
We will examine change from a retrospective baseline 6 months prior to enrollment in Signal metrics including time outside scheduled hours per scheduled day. Using this data will determine how a provider's time is utilized in the EHR. No patient level information will be collected for this outcome measure.
Measured: Baseline and 90 days after the initial exposure to the intervention
Clinician Relative Value Units (RVUs) per Week
Average relative value units (RVUs) per week during intervention months 2 and 3, adjusted for baseline (6-month pre-intervention period)
Measured: 60 days after exposure to the intervention, and 90 days after exposure to the intervention
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted27 Feb 2026
- Study start23 Feb 2026
- Primary completionMay 2026 (estimated)
- Study completionMay 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (7)Papers the sponsor has linked to this study.
- Other trials for Quality ImprovementStudies of the same condition, open and under way.
- More trials run by University of California, Los AngelesThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind
- Who is masked
- Investigator
- Enrolment
- 284 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of California, Los Angeles
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, John N. Mafi, MD, MPH, University of California, Los Angeles
- Investigators
- John N Mafi, MD, MPH, Principal investigator, Division of General Internal Medicine & Health Services Research, David Geffen School of Medicine at the University of California, Los AngelesPaul J Lukac, MD, MBA, MS, Principal investigator, UCLA Health Information Technology, UCLA Health
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07438743
- Sponsor's protocol ID
- IRB-26-0066
- Status last verified
- Mar 2026
- First submitted
- 22 Feb 2026
- Last updated
- 6 Mar 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
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.
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.
PubMed 39524814Quigley 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.
PubMed 39403289Melnick 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.
PubMed 33289493Trockel 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.
PubMed 29196982Lukac 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.
PubMed 41497288Chin AT, Zhu N, Vangala S, Woo H, Wisk LE, Kingsley T, Mafi JN, Lukac PJ. A Pragmatic Randomized Trial of an EHR-Integrated Generative AI Chart Summarization Tool for Ambulatory Clinicians. medRxiv [Preprint]. 2026 Aug 31:2026.08.26.26361496. doi: 10.64898/2026.08.26.26361496.
PubMed 42922608
Study at a glance
From the registry record, last updated by the sponsor on 6 Mar 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Epic Generative Artificial Intelligence Chart Summarization Tool to Reduce Ambulatory Provider Cognitive Task Load: A Randomized Controlled Trial
- ClinicalTrials.gov ID
- NCT07438743
- Acronym / sponsor ID
- IRB-26-0066
- Conditions
- Quality Improvement
- Keywords
- Physician Task Load, Professional Fulfillment, Artificial Intelligence, Chart Summarization, System Usability
- Study type
- Interventional
- Recruitment status
- Active, not recruiting
- Enrolment
- 284 participants (estimated)
- Lead sponsor
- University of California, Los AngelesUniversity, hospital or other
- Study start
- 23 Feb 2026 (actual)
- Primary completion
- May 2026 (estimated)
- Study completion
- May 2026 (estimated)
- First posted
- 27 Feb 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
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.
Study design
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (investigator)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Intervention Arm | Experimental | Other: GenAI Chart SummarizationParticipants 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. |
| Care As Usual | No intervention | –Participants in this arm will not have access to chart summarization tool and will continue their usual clinical practice. |
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
Key inclusion criteria (2 listed)
- 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
Key exclusion criteria (1 listed)
- Trainee providers (e.g., residents, medical students), and psychologists
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| GenAI Chart SummarizationEpic'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. | Other | Intervention Arm |
Primary outcome
Change from Baseline Physician Task Load
Time frame: Baseline and 90 days after initial exposure to the intervention
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.
10 secondary outcomes
Change in Modified Total Chart Time Per Encounter
Time frame: 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
Time frame: Baseline and 90 days after initial exposure to the intervention
Change from Baseline Self-Reported Pre-Charting Effectiveness
Time frame: Baseline and 90 days from initial exposure to the intervention
Provider Satisfaction Scores
Time frame: 90 days after initial exposure to the intervention
System Usability Scale
Time frame: 90 days from initial exposure to the intervention
Safety Events
Time frame: Over the 90 day period following after initial exposure to the intervention
Qualitative Tool-Specific EHR Feedback
Time frame: Over the 90 days following initial exposure to the intervention
Change from Baseline Consumer Assessment of Healthcare Providers and Systems Clinician & Group Survey (CG-CAHPS) Metric
Time frame: Baseline and 90 days after initial exposure to the intervention
Change from Baseline Epic Signal (Activity) Metric: Time Outside Scheduled Hours
Time frame: Baseline and 90 days after the initial exposure to the intervention
Clinician Relative Value Units (RVUs) per Week
Time frame: 60 days after exposure to the intervention, and 90 days after exposure to the intervention
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 6 Mar 2026.
- BackgroundCarolus, 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: PubMed 39524814Koch 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.
- Background: PubMed 39403289Quigley 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.
- Background: PubMed 33289493Melnick 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.
- Background: PubMed 29196982Trockel 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.
- Background: PubMed 41497288Lukac 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.
- Derived from this study: PubMed 42922608Chin AT, Zhu N, Vangala S, Woo H, Wisk LE, Kingsley T, Mafi JN, Lukac PJ. A Pragmatic Randomized Trial of an EHR-Integrated Generative AI Chart Summarization Tool for Ambulatory Clinicians. medRxiv [Preprint]. 2026 Aug 31:2026.08.26.26361496. doi: 10.64898/2026.08.26.26361496.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
John N Mafi, MD, MPH principal investigator
Division of General Internal Medicine & Health Services Research, David Geffen School of Medicine at the University of California, Los Angeles
Paul J Lukac, MD, MBA, MS principal investigator
UCLA Health Information Technology, UCLA Health
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing GenAI Chart Summarization in people with Quality Improvement, run by University of California, Los Angeles at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: under way, not looking for participants, as of the sponsor's last update on 6 Mar 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Change from Baseline Physician Task Load (time frame: Baseline and 90 days after initial exposure to the intervention). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07438743, which also lists 7 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 6 Mar 2026.