Ambient AI for Reducing Nursing Staff Documentation Time
An EHR-Embedded Pragmatic Stepped-Wedge Clinical Trial of Ambient Artificial Intelligence to Reduce Nursing Staff Documentation Time
The goal of this clinical trial is to learn whether using Ambient Artificial Intelligence for nursing staff documentation in an inpatient setting will reduce the time spent in flowsheet documentation and enhance nurse staffing wellbeing.
Participants will use Ambient Listening AI software to draft documentation in discrete fields.
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Study Type
Study Type
Enrollment (Estimated)
Enrollment
Phase
Phase
- Not Applicable
Contacts and Locations
Study Contact
Study Contact
- Name: Ann Wieben, PhD, RN
- Phone Number: 6082651029
- Email: wieben@wisc.edu
Study Contact Backup
- Name: Jann Pfaff, PhD, RN
- Email: jpfaff2@uwhealth.org
Study Locations
-
-
Wisconsin
-
Madison, Wisconsin, United States, 53718
- Recruiting
- UW Health - East Madison Hospital
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Description
Inclusion Criteria:
- Willingness to engage and use ambient technology
- English speaking
- All Registered Nurses and Nursing Assistants with the study inpatient units
- Attest to completing all required training
Exclusion Criteria:
- Planned leave more than 6 weeks during study timeframe
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Health Services Research
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: None (Open Label)
Number of Arms
Arms and Interventions
Participant Group / ArmParticipant Group / Arm |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
Experimental: Ambient Listening Group 1
The hospital unit will be randomized and all nursing staff within the unit will have access to start using Ambient AI at week 8.
|
Ambient AI software intervention is implemented into the nursing staff workflow.
The software incorporates Automated Speech Recognition technology with Large Language Models to generate clinical documentation in real-time
|
|
Experimental: Ambient Listening Group 2
The hospital unit will be randomized and all nursing staff within the unit will have access to start using Ambient AI at week 11.
|
Ambient AI software intervention is implemented into the nursing staff workflow.
The software incorporates Automated Speech Recognition technology with Large Language Models to generate clinical documentation in real-time
|
|
Experimental: Ambient Listening Group 3
The hospital unit will be randomized and all nursing staff within the unit will have access to start using Ambient AI at week 14.
|
Ambient AI software intervention is implemented into the nursing staff workflow.
The software incorporates Automated Speech Recognition technology with Large Language Models to generate clinical documentation in real-time
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Change in Active Time Spent in Flowsheets per shift hour
Time Frame: Baseline to 22 weeks
|
To assess a change in nursing staff documentation time, the change active time spent in flowsheets per shift hour with the use of the Ambient Listening tool versus usual documentation will be reported.
|
Baseline to 22 weeks
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Change in Active Time Spent in Flowsheets per patient per shift
Time Frame: Baseline to 22 weeks
|
To assess nursing staff documentation burden, the change in active time spent in flowsheets per patient shift will be reported.
|
Baseline to 22 weeks
|
|
Change in the number of clicks or taps in Flowsheets
Time Frame: Baseline to 22 weeks
|
To assess nursing staff documentation burden, the change in the number of clicks or taps in flowsheets will be reported.
|
Baseline to 22 weeks
|
|
Change in Amount of Overtime Charting
Time Frame: Baseline to 22 weeks
|
To assess nursing staff documentation burden, the change in time spent documenting after end time of assignment will be reported.
|
Baseline to 22 weeks
|
|
Change in Clinician Worklife Survey (Mini-Z) Score
Time Frame: Baseline to 22 weeks
|
Professional Wellbeing will be assessed with the Mini Z 3.0, a 10 item tool (plus one open-ended question) designed to quickly assess clinician burnout, stress, satisfaction, and work-life drivers such as workload control, teamwork, and electronic health record (EHR) related stressors.
The Mini Z survey is scored by summing responses to the first 10 items, each rated on a 1-5 Likert scale, producing a total score ranging from 10 to 50.
Higher scores indicate better worklife conditions, with scores of 40 or above reflecting a "joyful" workplace.
|
Baseline to 22 weeks
|
|
Change in Mini-Z Subscale Scores: Supportive Work Environment
Time Frame: Baseline to 22 weeks
|
Professional Wellbeing will also be assessed with Mini Z subscales.
One Mini-Z subscale measures supportive work environment with 7-items (scores range from 7-35, higher scores indicate more supportive environment).
|
Baseline to 22 weeks
|
|
Change in Mini-Z (3.0) Subscale Scores: EHR Stress
Time Frame: Baseline to 22 weeks
|
Professional Wellbeing will also be assessed with Mini Z subscales.
One Mini-Z subscale measures EHR stress (scores range from 3-15, higher scores indicate more manageable EHR stress).
|
Baseline to 22 weeks
|
|
Change System Usability Scale (SUS)
Time Frame: 11 weeks to 22 weeks
|
The SUS is a 10-item scale that assesses perceived usability of a system, in this case, the Abridge Ambient Listening Tool.
It yields a single score that can range from 0-100 with higher scores indicating higher system usability.
|
11 weeks to 22 weeks
|
Collaborators and Investigators
Sponsor
Sponsor
Investigators
Investigators
- Principal Investigator: Ann Wieben, PhD, RN, University of Wisconsin, Madison
- Principal Investigator: Jann Pfaff, PhD, RN, University of Wisconsin, Madison
Publications and helpful links
General Publications
- 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.
- 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.
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Estimated)
Primary Completion
Study Completion (Estimated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- 2026-0311
- UWMSN | Nursing | Admin (Other Identifier: UW Madison)
- Protocol Version 5/15/26 (Other Identifier: UW Madison)
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
IPD Sharing Time Frame
IPD Sharing Access Criteria
IPD Sharing Supporting Information Type
- STUDY_PROTOCOL
- SAP
- ICF
- ANALYTIC_CODE
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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