Healthcare Provider Well-beingNCT06517082
Ambient AI for Provider Well-Being
A study testing Artificial Intelligence in people with Healthcare Provider Well-being, run by University of Wisconsin, Madison at 1 site in United States.
Trial summary
The goal of this clinical trial is to learn whether using Ambient Artificial Intelligence for provider documentation will enhance provider well-being and improve documentation quality. Participants will complete their documentation using the Ambient AI software. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Healthcare Provider Well-being
- What is being tested?
- Artificial Intelligence
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 66 participants
- Where
- 1 siteUnited States
- Study dates
- 15 Aug 2024to 27 Mar 2025
- 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 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Healthcare Provider in the UW Health Outpatient Clinic Setting
- Willingness to engage and use ambient technology
- Owns an Apple mobile device, as the software is accessible only on this platform
- Adult (greater than 18 years)
- English or Spanish speaking
- Completed the training and in-servicing required to use the tool
- Providing outpatient care to no less than 20 encounters on a weekly average
Who cannot join
- Planned leave in 6 weeks following randomization
- Not registered onto Epic's mobile Haiku system for access
- Enrolled in a virtual scribe program and not willing to leave the program
Trial locations and contacts
1 site in 1 country.
About this study
Official title: An EHR-embedded Pragmatic Stepped-wedge Individual Randomized Clinical Trial of Ambient Artificial Intelligence to Improve Provider Well-Being
The goal of this clinical trial is to learn whether using Ambient Artificial Intelligence for provider documentation will enhance provider well-being and improve documentation quality.
Participants will complete their documentation using the Ambient AI software.
Read the detailed description
Provider documentation of patient visits is a time-consuming activity that extends throughout the workday and often continues outside office hours. This ongoing clerical burden negatively impacts provider well-being, contributing to burnout and job dissatisfaction.
To address these challenges, the researchers propose to test the effectiveness of the Ambient AI tool in improving provider fulfillment and note documentation efficiency. The overarching goal is to leverage AI technology to enhance provider well-being and documentation quality.
- Conditions
- Healthcare Provider Well-being
- Being tested
- Artificial Intelligence
- Keywords
- Artificial Intelligence, Physician well-being, Healthcare provider
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Artificial IntelligenceOther
Ambient AI software intervention is implemented into the providers workflow. The software incorporates Automated Speech Recognition technology with Large Language Models to generate clinical documentation in real-time.
| Study group | Role | What they receive |
|---|---|---|
| Ambient Listening Group 1 | Experimental | Participants randomized to this arm will start using Ambient AI at week 7. Receives: Other: Artificial Intelligence |
| Ambient Listening Group 2 | Experimental | Participants randomized to this arm will start using Ambient AI at week 13. Receives: Other: Artificial Intelligence |
| Ambient Listening Group 3 | Experimental | Participants randomized to this arm will start using Ambient AI at week 19. Receives: Other: Artificial Intelligence |
What is being measured
The primary outcome is the main question the study is designed to answer.
Change in provider fulfillment index
Using the Professional Well-Being Academic Consortium Survey Measures, the fulfillment index is a 6-item questionnaire. Each question is scored on a 0-4 Likert scale, with total possible scores of 0-24. Higher scores indicate greater fulfillment
Measured: Baseline to weeks 6, 12, 18, and 24
Change in provider burnout
Using the Professional Well-Being Academic Consortium Survey Measures, the burnout index includes two subcomponents of work exhaustion and interpersonal disengagement. It is a 10-item questionnaire, scored together as a composite. Each question is scored on a 0-4 Likert scale, with a total possible range of 0-40. Higher scores indicate greater burnout, indicating lower well-being
Measured: Baseline to weeks 6, 12, 18, and 24
Secondary outcomes (4)
Change in time spent on documentation outside work hours
Providers will track amount of time spent on EHR (electronic health records) outside of scheduled patient hours per 8 hours of patient scheduled time
Measured: Baseline to 24 weeks
Change in task load
Hours spent on documentation per 8 hours of scheduled patient time
Measured: Baseline to 24 weeks
Change in meaningfulness of work
Meaningfulness of work is a 4-item questionnaire, where each question is scored on a 0-4 Likert scale. Total possible scores range from 0-16, with higher scores indicating lower sense of meaningfulness of work.
Measured: Baseline to 24 weeks
Change in meaningful relationships
Using the Professional Well-Being Academic Consortium Survey Measures, the negative impact of work on relationships index is a 4-item questionnaire. Each question is scored on a 0-4 Likert scale, with total possible scores ranging from 0-16. Higher scores indicate less meaningful relationships.
Measured: Baseline to 24 weeks
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted24 Jul 2024
- Study start15 Aug 2024
- Primary completion27 Mar 2025
- Study completion27 Mar 2025
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (3)Papers the sponsor has linked to this study.
- Other trials for Healthcare Provider Well-beingStudies 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
- The stepped wedge design involves staggered implementation of an intervention across different providers over multiple time periods, allowing all providers to eventually receive the intervention.
- Masking
- None (open label)
- Enrolment
- 66 participants (actual)
Sponsor and investigators
- Lead sponsor
- University of Wisconsin, Madison
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Majid Afshar, MD, MS, Principal investigator, University of Wisconsin, MadisonJoel Gordon, MD, Principal investigator, University of Wisconsin, Madison
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06517082
- Sponsor's protocol ID
- 2024-1028
- Other IDs
- A534285, Protocol Version 7/7/2024
- Status last verified
- May 2025
- First submitted
- 18 Jul 2024
- Last updated
- 30 May 2025
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: As part of the UW Learning Health System, the data queries, data dictionary, and data procedure will be mirrored over from the UW Health GitHub instance to SMPH GitLab instance for secondary research use. All patient data except timestamps will be deidentified (limited dataset) and managed and stored on SMPH servers and devices and provided through Clinical Research Data Service (CRDS) team in ICTR's Center for Health Informatics Institute and the UW SMPH Honest Broker. Provider data will be stored with identifiers for the follow-up focus groups and interviews.
Publications
Afshar M, Baumann MR, Resnik F, Hintzke J, Sullivan AG, Wills G, Lemmon K, Dambach J, Ann Mrotek L, Quinn M, Abramson K, Kleinschmidt P, Brazelton TB, Leaf MA, Twedt H, Kunstman D, Patterson B, Liao F, Rasmussen S, Burnside ES, Goswami C, Gordon J. A Pragmatic Randomized Controlled Trial of Ambient Artificial Intelligence to Improve Health Practitioner Well-Being. NEJM AI. 2025 Dec;2(12):10.1056/aioa2500945. doi: 10.1056/aioa2500945. Epub 2025 Nov 26.
PubMed 41625485Afshar M, Resnik F, Baumann MR, Hintzke J, Lemmon K, Sullivan AG, Shah T, Stordalen A, Oberst M, Dambach J, Mrotek LA, Quinn M, Abramson K, Kleinschmidt P, Brazelton T, Twedt H, Kunstman D, Wills G, Long J, Patterson BW, Liao FJ, Rasmussen S, Burnside E, Goswami C, Gordon JE. A Novel Playbook for Pragmatic Trial Operations to Monitor and Evaluate Ambient Artificial Intelligence in Clinical Practice. NEJM AI. 2025 Sep;2(9):10.1056/aidbp2401267. doi: 10.1056/aidbp2401267. Epub 2025 Aug 28.
PubMed 40959192Afshar M, Resnik F, Baumann MR, Hintzke J, Lemmon K, Sullivan AG, Shah T, Stordalen A, Oberst M, Dambach J, Mrotek LA, Quinn M, Abramson K, Kleinschmidt P, Brazelton T, Twedt H, Kunstman D, Wills G, Long J, Patterson BW, Liao FJ, Rasmussen S, Burnside E, Goswami C, Gordon JE. A Novel Playbook for Pragmatic Trial Operations to Monitor and Evaluate Ambient Artificial Intelligence in Clinical Practice. medRxiv [Preprint]. 2025 Aug 14:2024.12.27.24319685. doi: 10.1101/2024.12.27.24319685.
PubMed 39763559
Study at a glance
From the registry record, last updated by the sponsor on 30 May 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- An EHR-embedded Pragmatic Stepped-wedge Individual Randomized Clinical Trial of Ambient Artificial Intelligence to Improve Provider Well-Being
- ClinicalTrials.gov ID
- NCT06517082
- Acronym / sponsor ID
- 2024-1028
- Conditions
- Healthcare Provider Well-being
- Keywords
- Artificial Intelligence, Physician well-being, Healthcare provider
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 66 participants (actual)
- Lead sponsor
- University of Wisconsin, MadisonUniversity, hospital or other
- Study start
- 15 Aug 2024 (actual)
- Primary completion
- 27 Mar 2025 (actual)
- Study completion
- 27 Mar 2025 (actual)
- First posted
- 24 Jul 2024 (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.
The goal of this clinical trial is to learn whether using Ambient Artificial Intelligence for provider documentation will enhance provider well-being and improve documentation quality.
Participants will complete their documentation using the Ambient AI software.
Detailed description
Provider documentation of patient visits is a time-consuming activity that extends throughout the workday and often continues outside office hours. This ongoing clerical burden negatively impacts provider well-being, contributing to burnout and job dissatisfaction.
To address these challenges, the researchers propose to test the effectiveness of the Ambient AI tool in improving provider fulfillment and note documentation efficiency. The overarching goal is to leverage AI technology to enhance provider well-being and documentation quality.
Study design
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 3
- Model description
- The stepped wedge design involves staggered implementation of an intervention across different providers over multiple time periods, allowing all providers to eventually receive the intervention.
| Arm | Type | Receives |
|---|---|---|
| Ambient Listening Group 1 | Experimental | Other: Artificial IntelligenceParticipants randomized to this arm will start using Ambient AI at week 7. |
| Ambient Listening Group 2 | Experimental | Other: Artificial IntelligenceParticipants randomized to this arm will start using Ambient AI at week 13. |
| Ambient Listening Group 3 | Experimental | Other: Artificial IntelligenceParticipants randomized to this arm will start using Ambient AI at week 19. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (7 listed)
- Healthcare Provider in the UW Health Outpatient Clinic Setting
- Willingness to engage and use ambient technology
- Owns an Apple mobile device, as the software is accessible only on this platform
- Adult (greater than 18 years)
- English or Spanish speaking
Key exclusion criteria (3 listed)
- Planned leave in 6 weeks following randomization
- Not registered onto Epic's mobile Haiku system for access
- Enrolled in a virtual scribe program and not willing to leave the program
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 |
|---|---|---|
| Artificial IntelligenceAmbient AI software intervention is implemented into the providers workflow. The software incorporates Automated Speech Recognition technology with Large Language Models to generate clinical documentation in real-time. | Other | Ambient Listening Group 1, Ambient Listening Group 2, Ambient Listening Group 3 |
Primary outcome
Change in provider fulfillment index
Time frame: Baseline to weeks 6, 12, 18, and 24
Using the Professional Well-Being Academic Consortium Survey Measures, the fulfillment index is a 6-item questionnaire. Each question is scored on a 0-4 Likert scale, with total possible scores of 0-24. Higher scores indicate greater fulfillment
Change in provider burnout
Time frame: Baseline to weeks 6, 12, 18, and 24
Using the Professional Well-Being Academic Consortium Survey Measures, the burnout index includes two subcomponents of work exhaustion and interpersonal disengagement. It is a 10-item questionnaire, scored together as a composite. Each question is scored on a 0-4 Likert scale, with a total possible range of 0-40. Higher scores indicate greater burnout, indicating lower well-being
4 secondary outcomes
Change in time spent on documentation outside work hours
Time frame: Baseline to 24 weeks
Change in task load
Time frame: Baseline to 24 weeks
Change in meaningfulness of work
Time frame: Baseline to 24 weeks
Change in meaningful relationships
Time frame: Baseline to 24 weeks
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 30 May 2025.
- Derived from this study: PubMed 41625485Afshar M, Baumann MR, Resnik F, Hintzke J, Sullivan AG, Wills G, Lemmon K, Dambach J, Ann Mrotek L, Quinn M, Abramson K, Kleinschmidt P, Brazelton TB, Leaf MA, Twedt H, Kunstman D, Patterson B, Liao F, Rasmussen S, Burnside ES, Goswami C, Gordon J. A Pragmatic Randomized Controlled Trial of Ambient Artificial Intelligence to Improve Health Practitioner Well-Being. NEJM AI. 2025 Dec;2(12):10.1056/aioa2500945. doi: 10.1056/aioa2500945. Epub 2025 Nov 26.
- Derived from this study: PubMed 40959192Afshar M, Resnik F, Baumann MR, Hintzke J, Lemmon K, Sullivan AG, Shah T, Stordalen A, Oberst M, Dambach J, Mrotek LA, Quinn M, Abramson K, Kleinschmidt P, Brazelton T, Twedt H, Kunstman D, Wills G, Long J, Patterson BW, Liao FJ, Rasmussen S, Burnside E, Goswami C, Gordon JE. A Novel Playbook for Pragmatic Trial Operations to Monitor and Evaluate Ambient Artificial Intelligence in Clinical Practice. NEJM AI. 2025 Sep;2(9):10.1056/aidbp2401267. doi: 10.1056/aidbp2401267. Epub 2025 Aug 28.
- Derived from this study: PubMed 39763559Afshar M, Resnik F, Baumann MR, Hintzke J, Lemmon K, Sullivan AG, Shah T, Stordalen A, Oberst M, Dambach J, Mrotek LA, Quinn M, Abramson K, Kleinschmidt P, Brazelton T, Twedt H, Kunstman D, Wills G, Long J, Patterson BW, Liao FJ, Rasmussen S, Burnside E, Goswami C, Gordon JE. A Novel Playbook for Pragmatic Trial Operations to Monitor and Evaluate Ambient Artificial Intelligence in Clinical Practice. medRxiv [Preprint]. 2025 Aug 14:2024.12.27.24319685. doi: 10.1101/2024.12.27.24319685.
- Individual participant dataSharing planned: Yes. As part of the UW Learning Health System, the data queries, data dictionary, and data procedure will be mirrored over from the UW Health GitHub instance to SMPH GitLab instance for secondary research use. All patient data except timestamps will be deidentified (limited dataset) and managed and stored on SMPH servers and devices and provided through Clinical Research Data Service (CRDS) team in ICTR's Center for Health Informatics Institute and the UW SMPH Honest Broker. Provider data will be stored with identifiers for the follow-up focus groups and interviews.
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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.
Majid Afshar, MD, MS principal investigator
University of Wisconsin, Madison
Joel Gordon, MD principal investigator
University of Wisconsin, Madison
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Artificial Intelligence in people with Healthcare Provider Well-being, run by University of Wisconsin, Madison 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 7 inclusion and 3 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 30 May 2025. 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 provider fulfillment index (time frame: Baseline to weeks 6, 12, 18, and 24). The study lists 2 primary outcomes in all. 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 NCT06517082, which also lists 3 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 30 May 2025.