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
3 other identifiers
interventional
250
1 country
1
Brief Summary
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.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for not_applicable
Started May 2026
Shorter than P25 for not_applicable
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
Click on a node to explore related trials.
Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
March 2, 2026
CompletedFirst Posted
Study publicly available on registry
March 6, 2026
CompletedStudy Start
First participant enrolled
May 5, 2026
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 1, 2026
ExpectedStudy Completion
Last participant's last visit for all outcomes
December 1, 2026
June 1, 2026
May 1, 2026
7 months
March 2, 2026
May 27, 2026
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Change in Active Time Spent in Flowsheets per shift hour
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 Outcomes (7)
Change in Active Time Spent in Flowsheets per patient per shift
Baseline to 22 weeks
Change in the number of clicks or taps in Flowsheets
Baseline to 22 weeks
Change in Amount of Overtime Charting
Baseline to 22 weeks
Change in Clinician Worklife Survey (Mini-Z) Score
Baseline to 22 weeks
Change in Mini-Z Subscale Scores: Supportive Work Environment
Baseline to 22 weeks
- +2 more secondary outcomes
Study Arms (3)
Ambient Listening Group 1
EXPERIMENTALThe hospital unit will be randomized and all nursing staff within the unit will have access to start using Ambient AI at week 8.
Ambient Listening Group 2
EXPERIMENTALThe hospital unit will be randomized and all nursing staff within the unit will have access to start using Ambient AI at week 11.
Ambient Listening Group 3
EXPERIMENTALThe hospital unit will be randomized and all nursing staff within the unit will have access to start using Ambient AI at week 14.
Interventions
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
Eligibility Criteria
You may qualify if:
- 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
You may not qualify if:
- Planned leave more than 6 weeks during study timeframe
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
UW Health - East Madison Hospital
Madison, Wisconsin, 53718, United States
Related Publications (2)
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.
PMID: 41625485BACKGROUNDAfshar 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.
PMID: 40959192BACKGROUND
MeSH Terms
Interventions
Intervention Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Ann Wieben, PhD, RN
University of Wisconsin, Madison
- PRINCIPAL INVESTIGATOR
Jann Pfaff, PhD, RN
University of Wisconsin, Madison
Central Study Contacts
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- NONE
- Purpose
- HEALTH SERVICES RESEARCH
- Intervention Model
- PARALLEL
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
March 2, 2026
First Posted
March 6, 2026
Study Start
May 5, 2026
Primary Completion (Estimated)
December 1, 2026
Study Completion (Estimated)
December 1, 2026
Last Updated
June 1, 2026
Record last verified: 2026-05
Data Sharing
- IPD Sharing
- Will share
- Shared Documents
- STUDY PROTOCOL, SAP, ICF, ANALYTIC CODE
- Time Frame
- We will make the IPD information available in early 2027 once we have completed our analysis and are ready for publication. It will be available indefinitely.
- Access Criteria
- We will provide a publicly accessible GitLab link where all study materials can be downloaded
We plan to share the majority of our research documentation including the Study Protocol, Statistical Analysis Plan, Informed Consent Plan, Analytics Code, data dictionary, and de-identified survey and interview/focus group results data.