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| ID | Type | Description | Link |
|---|---|---|---|
| A534285 | Other Identifier | UW- Madison | |
| Protocol Version 7/7/2024 | Other Identifier | UW- Madison |
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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.
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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Ambient Listening Group 1 | Experimental | Participants randomized to this arm will start using Ambient AI at week 7. |
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| Ambient Listening Group 2 | Experimental | Participants randomized to this arm will start using Ambient AI at week 13. |
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| Ambient Listening Group 3 | Experimental | Participants randomized to this arm will start using Ambient AI at week 19. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Artificial Intelligence | Other | 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. |
| Measure | Description | Time Frame |
|---|---|---|
| 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 | 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 | Baseline to weeks 6, 12, 18, and 24 |
| Measure | Description | Time Frame |
|---|---|---|
| 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 | Baseline to 24 weeks |
| Change in task load |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Majid Afshar, MD, MS | University of Wisconsin, Madison | Principal Investigator |
| Joel Gordon, MD | University of Wisconsin, Madison | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University of Wisconsin | Madison | Wisconsin | 53705 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 41625485 | Derived | 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. | |
| 40959192 |
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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.
Duration of storage will be at least 10 years.
Access to data and recordings and security measures will require IRB approval and request through CRDS.
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| ID | Term |
|---|---|
| D001185 | Artificial Intelligence |
| ID | Term |
|---|---|
| D000465 | Algorithms |
| D055641 | Mathematical Concepts |
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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.
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Hours spent on documentation per 8 hours of scheduled patient time
| 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. | 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. | Baseline to 24 weeks |
| Derived |
| Afshar 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. |
| 39763559 | Derived | Afshar 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. |