Burnout, Healthcare WorkersEvidentlyNCT07498582
AI Tool to Reduce Clinician Documentation Burden
A study testing AI Clinical Summarization Tool (Evidently) in people with Burnout, Healthcare Workers and Clinical Workflow Optimization, run by University of North Carolina, Chapel Hill at 1 site in United States.
Trial summary
This study looks at whether a clinician-facing artificial intelligence (AI) tool can help outpatient doctors spend less time reviewing medical records and documenting care. The tool creates brief summaries of existing medical record information to support routine clinical work. Read more about this study
- Who is it for?
- Any ageHealthy volunteers can take part
- Conditions the study is for
- Burnout, Healthcare Workers, Clinical Workflow Optimization, Health Information Technology
- What is being tested?
- AI Clinical Summarization Tool (Evidently)
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 128 participants
- Where
- 1 siteUnited States
- Study dates
- 30 Mar 2026to 8 Jun 2026
- Phase
- Interventional
- Are there results?
- None posted in the registry
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
- Healthy volunteers accepted
- Child, Adult, Older adult
Who may be able to join
- Participants must meet all of the following criteria:
- Attending outpatient specialists affiliated with UNCFP or UNCMG.
- At least two half-days (≥3.5 hours per session) of scheduled outpatient clinic per week.
- Primary specialty in an outpatient, patient-facing specialty practice within UNCFP or UNCMG.
- Anesthesiologists will be enrolled under the same protocol but analyzed separately due to distinct workflow characteristics.
Who cannot join
- Clinicians meeting any of the following criteria will be excluded:
- Trainees (e.g., residents or fellows).
- Advanced practice providers (APPs).
- Attendings whose outpatient workflows are predominantly supervisory or shared with trainees or APPs, defined as clinicians who self-report that 25% or more of outpatient clinic sessions are conducted jointly with trainees or APPs.
- Clinicians who participated in a prior Evidently pilot study.
- Clinicians with planned time away exceeding one week during the study period. Exclusion criteria will be assessed using self-report in the baseline survey, supplemented by administrative records where available (e.g., prior pilot participation or clinic volume). Clinicians meeting any exclusion criterion will not be randomized.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Evidently Workflow Study: Randomized Evaluation of a Clinician-Facing AI Documentation Support Tool in Outpatient Specialty Practice
This study looks at whether a clinician-facing artificial intelligence (AI) tool can help outpatient doctors spend less time reviewing medical records and documenting care. The tool creates brief summaries of existing medical record information to support routine clinical work. This study examines how use of this tool affects clinicians' workload, time spent in the electronic health record, and overall experience with documentation. The goal is to better understand whether AI documentation support tools can improve efficiency and reduce burden for clinicians in outpatient specialty practice.
Eligible UNC outpatient specialists may be invited to complete surveys and, if they qualify, are randomly assigned either to receive access to the tool (Evidently) at the beginning of the study period or to continue their usual workflow for eight weeks before receiving access. The study does not recruit patients and does not change medical care for patients.
Read the detailed description
Background and aim: This is a behavioral and health-information-technology study focused on clinical workflow. It does not target a specific patient disease or condition; it evaluates whether a clinician-facing artificial intelligence (AI) tool (Evidently) that produces brief summaries of existing electronic health record information can reduce documentation burden and improve efficiency and experience for outpatient specialists.
Design: Interventional, randomized, parallel-group trial. Eligible clinicians are randomly assigned either to receive access to Evidently at the start of the study period or to continue usual documentation workflow for eight weeks before receiving access. The primary comparison window is eight weeks per arm description in the protocol.
Setting and population: Recruitment targets outpatient attending physicians affiliated with UNC Faculty Practice (UNCFP) or UNC Medical Group (UNCMG) in the United States who can consent and complete study activities in English, with age limits and inclusion of birth-assigned sex categories as specified in the approved IRB application. Participants are recruited by invitation through professional clinical channels; the study does not recruit the general public.
Eligibility (summary): Screening confirms attending physician role; UNCFP or UNCMG affiliation; primary specialty in the protocol-eligible list (for example cardiology, pulmonology, gastroenterology, neurology, oncology, surgery, or anesthesiology); at least two half-day outpatient sessions per week (each at least 3.5 hours); fewer than 25 percent of outpatient sessions jointly staffed with trainees or advanced practice providers at or above the protocol threshold; no participation in a prior Evidently pilot; and no anticipated absence from work longer than one week during the eight-week study period. Individuals who do not meet these criteria are not enrolled.
Procedures for participants: Participation includes an eligibility and baseline survey (approximately 10 to 15 minutes), randomization, use or non-use of Evidently according to assignment during the randomized period, and a brief follow-up survey. There is no monetary compensation. The consent materials describe voluntary participation, confidentiality protections, and that participation is not reported to supervisors or leadership and does not affect employment status, evaluation, or clinical responsibilities.
Outcomes (high level): Outcomes emphasize clinician-reported workload; time and effort related to reviewing and summarizing medical records and using the electronic health record; task-load and related experience measures; and, for those assigned to early access, usability and perceived impact of the tool. The study does not enroll patients and does not assign interventions to patients; any linkage of survey responses to workflow data for analysis follows the approved consent and privacy plan.
Operational identifiers needed to link survey responses to workflow systems, if collected, are described in the approved consent and are handled per institutional policies and the IRB-approved protocol.
- Conditions
- Burnout, Healthcare Workers, Clinical Workflow Optimization, Health Information Technology, Electronic Health Records
- Being tested
- AI Clinical Summarization Tool (Evidently)
- Keywords
- clinician workload, artificial intelligence, clinical documentation, physician task load
- Medical subject headings
- Burnout, Psychological
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI Clinical Summarization Tool (Evidently)Behavioural
Also called Evidently
Clinicians randomized to the intervention arm will receive access to the AI clinical summarization tool following randomization and completion of baseline study procedures. Clinicians randomized to the control arm will continue usual chart review and documentation practices for the duration of the study.
Participation in the study and use of the AI clinical summarization tool are voluntary. Clinicians assigned to the intervention arm are not required to use the tool as part of routine care. Use of the AI clinical summarization tool will be characterized using system-generated utilization metrics provided by the vendor. These metrics may include measures such as the number of sessions (i.e., the number of times the tool is invoked), the number of patients for whom the tool is used, and, where available, the number of customized summaries generated. All utilization measures will be aggregated at the clinician level over the study period.
| Study group | Role | What they receive |
|---|---|---|
| Experimental: Evidently | Experimental | Clinicians randomized to the intervention arm will receive access to a clinician-facing AI clinical summarization tool (Evidently) integrated into routine clinical workflow. The intervention includes standardized onboarding and training materials (e.g., an onboarding webinar or equivalent asynchronous training, tip sheets, and on-demand implementation support). Optional personalization may be available to clinicians but is not required for participation in the study. Receives: Behavioral: AI Clinical Summarization Tool (Evidently) |
| No Intervention: Control | No intervention | Clinicians randomized to the control arm will continue usual chart review and documentation practices without access to the AI clinical summarization tool during the study period. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Change in Clinician Cognitive Load
Cognitive load measured using the Physician Task Load (PTL) scale, adapted from the National Aeronautics and Space Administration (NASA) Task Load Index. The PTL includes four items-mental demand, physical demand, effort, and time pressure-each rated on a 0-100 scale with reference to a typical clinical workday during the past 1-2 weeks. Item scores will be summed to produce a continuous composite score ranging from 0 to 400, with higher scores indicating greater cognitive workload. The primary outcome is the clinician-level change in PTL score from baseline to the end of Study Month 2, analyzed under an intention-to-treat framework.
Measured: Baseline to end of Study Month 2
Secondary outcomes (16)
Change in time in clinical review
Epic Signal-derived time spent in clinical review, capturing time spent reviewing patient charts and clinical information.
Measured: Baseline to Study Month 2
Change in time outside work hours
Epic Signal-derived time spent outside scheduled work hours, including evenings and unscheduled days where available.
Measured: Baseline to Study Month 2
Change in clinic preparation time
Self-reported time spent preparing for clinic, during scheduled and outside scheduled work hours (minutes per half-day clinic).
Measured: Baseline to Study Month 2
Change in new patient record review time
Self-reported time spent reviewing and summarizing a new patient's record prior to clinic.
Measured: Baseline to Study Month 2
Change in burnout
Change in clinician burnout assessed using a validated single-item self-report measure. The item asks clinicians to rate their current level of burnout on a 5-point ordinal scale ranging from 1 (no symptoms of burnout) to 5 (completely burned out). Higher scores indicate greater burnout. The outcome is the clinician-level change in this single-item burnout rating from baseline to the end of Study Month 2.
Measured: Baseline to Study Month 2
Number of tool sessions invoked
Total number of times the AI clinical summarization tool (Evidently) was invoked by each clinician during the study period, as recorded by vendor-provided system logs. Reported as a count aggregated at the clinician level (intervention arm only).
Measured: Study Month 2
Number of patients with tool use
Total number of unique patients for whom the AI clinical summarization tool (Evidently) was used by each clinician during the study period, as recorded by vendor-provided system logs. Reported as a count aggregated at the clinician level (intervention arm only).
Measured: Study Month 2
Proportion of eligible visits with tool use
Proportion of eligible outpatient visits during the study period for which the AI clinical summarization tool (Evidently) was used by each clinician, as derived from vendor-provided system logs and scheduling data. Reported as a percentage aggregated at the clinician level (intervention arm only).
Measured: Study Month 2
Context of use
System-generated data describing clinical contexts in which Evidently was used (e.g., new versus return visits, specialty workflows), supplemented by structured survey items where necessary (intervention arm only).
Measured: Study Month 2
Usability and fit
Usability and fit are assessed using a study-specific Likert agreement questionnaire comprising three statements about Evidently, each rated on a 5-point Likert agreement scale scored from 1 (Strongly disagree) to 5 (Strongly agree); higher scores indicate more favorable usability and fit. The statements are: Evidently is easy to use; Evidently was easy to learn; Evidently fits the chart review and summarization needs of my specialty. Item-level distributions and/or summary scores (e.g., mean or median per item) will be reported at Study Month 2 (intervention arm only).
Measured: Study Month 2
Accuracy and trust
Perceived accuracy and trust are assessed using a study-specific Likert agreement questionnaire comprising four statements, each rated on a 5-point Likert agreement scale scored from 1 (Strongly disagree) to 5 (Strongly agree); higher scores indicate more favorable perceptions of accuracy and trust. The statements address whether Evidently-generated summaries are generally accurate; whether Evidently highlights clinically relevant information; whether Evidently surfaces relevant information the respondent may not have found independently; and whether summaries from Evidently are at least as good as summaries the respondent would otherwise prepare. Item-level distributions and/or summary scores will be reported at Study Month 2 (intervention arm only).
Measured: Study Month 2
Impact on day
Single-item measure assessed using a 5-point Likert agreement scale scored from 1 (Strongly disagree) to 5 (Strongly agree); higher scores indicate stronger agreement that Evidently helps the clinician get through their clinical day more easily. The item prompt is: Evidently helps me get through my clinical day more easily. Distribution of responses will be reported at Study Month 2 (intervention arm only).
Measured: Study Month 2
Time savings
Self-reported perceived time savings per half-day clinic attributable to Evidently (intervention arm only).
Measured: Study Month 2
Impact on care
Single-item measure assessed using a 5-point Likert agreement scale scored from 1 (Strongly disagree) to 5 (Strongly agree); higher scores indicate stronger agreement that Evidently helps the clinician provide better patient care. The item prompt is: Using Evidently helps me provide better patient care. Distribution of responses will be reported at Study Month 2 (intervention arm only).
Measured: Study Month 2
Overall satisfaction with AI clinical summarization tool assessed by single-item Likert agreement scale
Overall satisfaction with the AI clinical summarization tool (Evidently) is assessed using a single-item measure on a 5-point Likert agreement scale scored from 1 (Strongly disagree) to 5 (Strongly agree); higher scores indicate greater overall satisfaction. The item prompt is: Overall, I am satisfied with Evidently. The outcome is reported as the distribution of responses (frequency and percentage per category) at Study Month 2 (intervention arm only).
Measured: Study Month 2
Open-ended feedback
Qualitative open-ended feedback collected via a single optional free-text item on the end-of-study questionnaire (no numeric scale is used for this measure). The item invites additional narrative feedback about Evidently, including what worked well, where Evidently was most helpful, what was frustrating or less useful than expected, and suggestions for improvement or new functionality. Responses will be analyzed using qualitative content or thematic analysis. Results will be reported as major themes with counts or proportions of respondents whose responses were assigned to each theme where appropriate, plus representative anonymized quotations. If concise enough, a tabulation of the most common paraphrased response categories may be presented; lengthy narrative responses will be summarized thematically rather than as a ranked list of full verbatim answers (intervention arm only).
Measured: Study Month 2
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted27 Mar 2026
- Study start30 Mar 2026
- Primary completion8 Jun 2026
- Study completion8 Jun 2026
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Burnout, Healthcare WorkersStudies of the same condition, open and under way.
- 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
- Model description
- This is a two-arm randomized controlled trial comparing access to a clinician-facing AI clinical summarization tool (Evidently), combined with standardized onboarding and implementation support, versus usual chart review and documentation practices without access to the tool. Prior to randomization, all eligible clinicians will complete baseline surveys, and six months of retrospective clinician-level electronic health record (EHR) workflow metadata (Epic Signal) will be obtained to characterize baseline workflow and support covariate-constrained randomization. In addition, limited retrospective patient-level data without direct identifiers may be used over the same period to characterize clinician workload and clinical context, including measures such as patients seen per day, visit duration, and aggregated proxies of chart complexity. These patient-level data will be aggregated at the clinician level and will not be used to identify or contact individual patients.
- Masking
- None (open label)
- Enrolment
- 128 participants (actual)
Sponsor and investigators
- Lead sponsor
- University of North Carolina, Chapel Hill
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Spencer Dorn, MD, MPH, MHA, Principal investigator, University of North Carolina, Chapel Hill
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07498582
- Sponsor's protocol ID
- 26-0202
- Acronym
- Evidently
- Status last verified
- Mar 2026
- First submitted
- 20 Mar 2026
- Last updated
- 26 Jun 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: Deidentified individual participant data that supports the results will be shared beginning 9 to 36 months following publication, provided the investigator who proposes to use the data has approval from an Institutional Review Board (IRB), Independent Ethics Committee (IEC), or Research Ethics Board (REB), as applicable, and executes a data use/sharing agreement with UNC.
Study at a glance
From the registry record, last updated by the sponsor on 26 Jun 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Evidently Workflow Study: Randomized Evaluation of a Clinician-Facing AI Documentation Support Tool in Outpatient Specialty Practice
- ClinicalTrials.gov ID
- NCT07498582
- Acronym / sponsor ID
- Evidently / 26-0202
- Conditions
- Burnout, Healthcare Workers, Clinical Workflow Optimization, Health Information Technology, Electronic Health Records
- Keywords
- clinician workload, artificial intelligence, clinical documentation, physician task load
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 128 participants (actual)
- Lead sponsor
- University of North Carolina, Chapel HillUniversity, hospital or other
- Study start
- 30 Mar 2026 (actual)
- Primary completion
- 8 Jun 2026 (actual)
- Study completion
- 8 Jun 2026 (actual)
- First posted
- 27 Mar 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 study looks at whether a clinician-facing artificial intelligence (AI) tool can help outpatient doctors spend less time reviewing medical records and documenting care. The tool creates brief summaries of existing medical record information to support routine clinical work. This study examines how use of this tool affects clinicians' workload, time spent in the electronic health record, and overall experience with documentation. The goal is to better understand whether AI documentation support tools can improve efficiency and reduce burden for clinicians in outpatient specialty practice.
Eligible UNC outpatient specialists may be invited to complete surveys and, if they qualify, are randomly assigned either to receive access to the tool (Evidently) at the beginning of the study period or to continue their usual workflow for eight weeks before receiving access. The study does not recruit patients and does not change medical care for patients.
Detailed description
Background and aim: This is a behavioral and health-information-technology study focused on clinical workflow. It does not target a specific patient disease or condition; it evaluates whether a clinician-facing artificial intelligence (AI) tool (Evidently) that produces brief summaries of existing electronic health record information can reduce documentation burden and improve efficiency and experience for outpatient specialists.
Design: Interventional, randomized, parallel-group trial. Eligible clinicians are randomly assigned either to receive access to Evidently at the start of the study period or to continue usual documentation workflow for eight weeks before receiving access. The primary comparison window is eight weeks per arm description in the protocol.
Setting and population: Recruitment targets outpatient attending physicians affiliated with UNC Faculty Practice (UNCFP) or UNC Medical Group (UNCMG) in the United States who can consent and complete study activities in English, with age limits and inclusion of birth-assigned sex categories as specified in the approved IRB application. Participants are recruited by invitation through professional clinical channels; the study does not recruit the general public.
Eligibility (summary): Screening confirms attending physician role; UNCFP or UNCMG affiliation; primary specialty in the protocol-eligible list (for example cardiology, pulmonology, gastroenterology, neurology, oncology, surgery, or anesthesiology); at least two half-day outpatient sessions per week (each at least 3.5 hours); fewer than 25 percent of outpatient sessions jointly staffed with trainees or advanced practice providers at or above the protocol threshold; no participation in a prior Evidently pilot; and no anticipated absence from work longer than one week during the eight-week study period. Individuals who do not meet these criteria are not enrolled.
Procedures for participants: Participation includes an eligibility and baseline survey (approximately 10 to 15 minutes), randomization, use or non-use of Evidently according to assignment during the randomized period, and a brief follow-up survey. There is no monetary compensation. The consent materials describe voluntary participation, confidentiality protections, and that participation is not reported to supervisors or leadership and does not affect employment status, evaluation, or clinical responsibilities.
Outcomes (high level): Outcomes emphasize clinician-reported workload; time and effort related to reviewing and summarizing medical records and using the electronic health record; task-load and related experience measures; and, for those assigned to early access, usability and perceived impact of the tool. The study does not enroll patients and does not assign interventions to patients; any linkage of survey responses to workflow data for analysis follows the approved consent and privacy plan.
Operational identifiers needed to link survey responses to workflow systems, if collected, are described in the approved consent and are handled per institutional policies and the IRB-approved protocol.
Study design
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
- Model description
- This is a two-arm randomized controlled trial comparing access to a clinician-facing AI clinical summarization tool (Evidently), combined with standardized onboarding and implementation support, versus usual chart review and documentation practices without access to the tool. Prior to randomization, all eligible clinicians will complete baseline surveys, and six months of retrospective clinician-level electronic health record (EHR) workflow metadata (Epic Signal) will be obtained to characterize baseline workflow and support covariate-constrained randomization. In addition, limited retrospective patient-level data without direct identifiers may be used over the same period to characterize clinician workload and clinical context, including measures such as patients seen per day, visit duration, and aggregated proxies of chart complexity. These patient-level data will be aggregated at the clinician level and will not be used to identify or contact individual patients.
| Arm | Type | Receives |
|---|---|---|
| Experimental: Evidently | Experimental | Behavioral: AI Clinical Summarization Tool (Evidently)Clinicians randomized to the intervention arm will receive access to a clinician-facing AI clinical summarization tool (Evidently) integrated into routine clinical workflow. The intervention includes standardized onboarding and training materials (e.g., an onboarding webinar or equivalent asynchronous training, tip sheets, and on-demand implementation support). Optional personalization may be available to clinicians but is not required for participation in the study. |
| No Intervention: Control | No intervention | –Clinicians randomized to the control arm will continue usual chart review and documentation practices without access to the AI clinical summarization tool during the study period. |
Who may qualify
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
Key inclusion criteria (5 listed)
- Attending outpatient specialists affiliated with UNCFP or UNCMG.
- At least two half-days (≥3.5 hours per session) of scheduled outpatient clinic per week.
- Primary specialty in an outpatient, patient-facing specialty practice within UNCFP or UNCMG.
- Anesthesiologists will be enrolled under the same protocol but analyzed separately due to distinct workflow characteristics.
Key exclusion criteria (6 listed)
- Trainees (e.g., residents or fellows).
- Advanced practice providers (APPs).
- Attendings whose outpatient workflows are predominantly supervisory or shared with trainees or APPs, defined as clinicians who self-report that 25% or more of outpatient clinic sessions are conducted jointly with trainees or APPs.
- Clinicians who participated in a prior Evidently pilot study.
- Clinicians with planned time away exceeding one week during the study period. Exclusion criteria will be assessed using self-report in the baseline survey, supplemented by administrative records where available (e.g., prior pilot participation or clinic volume). Clinicians meeting any exclusion criterion will not be randomized.
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 |
|---|---|---|
| AI Clinical Summarization Tool (Evidently)Also: EvidentlyClinicians randomized to the intervention arm will receive access to the AI clinical summarization tool following randomization and completion of baseline study procedures. Clinicians randomized to the control arm will continue usual chart review and documentation practices for the duration of the study. Participation in the study and use of the AI clinical summarization tool are voluntary. Clinicians assigned to the intervention arm are not required to use the tool as part of routine care. Use of the AI clinical summarization tool will be characterized using system-generated utilization metrics provided by the vendor. These metrics may include measures such as the number of sessions (i.e., the number of times the tool is invoked), the number of patients for whom the tool is used, and, where available, the number of customized summaries generated. All utilization measures will be aggregated at the clinician level over the study period. | Behavioural | Experimental: Evidently |
Primary outcome
Change in Clinician Cognitive Load
Time frame: Baseline to end of Study Month 2
Cognitive load measured using the Physician Task Load (PTL) scale, adapted from the National Aeronautics and Space Administration (NASA) Task Load Index. The PTL includes four items-mental demand, physical demand, effort, and time pressure-each rated on a 0-100 scale with reference to a typical clinical workday during the past 1-2 weeks. Item scores will be summed to produce a continuous composite score ranging from 0 to 400, with higher scores indicating greater cognitive workload. The primary outcome is the clinician-level change in PTL score from baseline to the end of Study Month 2, analyzed under an intention-to-treat framework.
16 secondary outcomes
Change in time in clinical review
Time frame: Baseline to Study Month 2
Change in time outside work hours
Time frame: Baseline to Study Month 2
Change in clinic preparation time
Time frame: Baseline to Study Month 2
Change in new patient record review time
Time frame: Baseline to Study Month 2
Change in burnout
Time frame: Baseline to Study Month 2
Number of tool sessions invoked
Time frame: Study Month 2
Number of patients with tool use
Time frame: Study Month 2
Proportion of eligible visits with tool use
Time frame: Study Month 2
Context of use
Time frame: Study Month 2
Usability and fit
Time frame: Study Month 2
Accuracy and trust
Time frame: Study Month 2
Impact on day
Time frame: Study Month 2
Time savings
Time frame: Study Month 2
Impact on care
Time frame: Study Month 2
Overall satisfaction with AI clinical summarization tool assessed by single-item Likert agreement scale
Time frame: Study Month 2
Open-ended feedback
Time frame: Study Month 2
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 26 Jun 2026.
- Individual participant dataSharing planned: Yes. Deidentified individual participant data that supports the results will be shared beginning 9 to 36 months following publication, provided the investigator who proposes to use the data has approval from an Institutional Review Board (IRB), Independent Ethics Committee (IEC), or Research Ethics Board (REB), as applicable, and executes a data use/sharing agreement with UNC.
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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.
Spencer Dorn, MD, MPH, MHA principal investigator
University of North Carolina, Chapel Hill
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing AI Clinical Summarization Tool (Evidently) in people with Burnout, Healthcare Workers and Clinical Workflow Optimization, run by University of North Carolina, Chapel Hill 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 5 inclusion and 6 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: finished, as of the sponsor's last update on 26 Jun 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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
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 in Clinician Cognitive Load (time frame: Baseline to end of Study Month 2). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 26 Jun 2026.