Emergency Medicine Practitioners Overall Well-being Enhancement With Ambient AI Scribes
EMPOWER
1 other identifier
interventional
55
1 country
1
Brief Summary
The primary objective of the study is to investigate the impact of an ambient AI scribe on clinicians' wellness and well-being outcomes; additionally, we also investigate how the use of the ambient AI scribe will lead to changes in documentation burden, clinical note characteristics and financial productivity.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P25-P50 for not_applicable
Started Apr 2026
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
Study Start
First participant enrolled
April 29, 2026
CompletedFirst Submitted
Initial submission to the registry
July 21, 2026
CompletedFirst Posted
Study publicly available on registry
August 3, 2026
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 1, 2026
ExpectedStudy Completion
Last participant's last visit for all outcomes
July 1, 2027
August 3, 2026
July 1, 2026
7 months
July 21, 2026
July 28, 2026
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Impact of an ambient AI scribe on clinician well-being and professional fulfillment
We will fit a linear model to describe the effect of Ambient tool introduction on our co-primary outcomes under the intention-to-treat (ITT) framework with a random effects structure to describe within provider variability. While we anticipate high or complete survey completion rates, in the event that not all surveys are completed and returned, we will perform a primary analysis on completed surveys only, and perform sensitivity analyses accounting for potentially systematic survey non-response bias using a response weighting strategy, using provider, scheduling, and patient encounter characteristics to create survey response weights (within each survey time period), then reweighting observations to account for non-response patterns. In analyses for both co-primary outcomes, we will perform Wald type hypothesis tests for inferences on the overall Ambient treatment effect and compare p-values to 0.05 / 2 to conservatively account for multiple comparisons using Bonferroni's method.
From enrollment to the end of maintenance phase at 24 weeks
Secondary Outcomes (1)
Assessment of the longitudinal changes in documentation burden
From enrollment to the end of maintenance phase at 42 weeks
Study Arms (3)
Ambient AI Scribe Intervention, Wave 1 (Step-wedge design)
EXPERIMENTALClinicians use an ambient AI scribe during patient encounters to assist with clinical documentation. Wave 1 participants receive the intervention for 18 weeks. Outcomes are compared before and after implementation.
Ambient AI Scribe Intervention, Wave 2 (Step-wedge design)
EXPERIMENTALClinicians use an ambient AI scribe during patient encounters to assist with clinical documentation. Wave 2 participants receive the intervention for 12 weeks. Outcomes are compared before and after implementation.
Ambient AI Scribe Intervention Wave 3 (Step-wedge design)
EXPERIMENTALClinicians use an ambient AI scribe during patient encounters to assist with clinical documentation. Wave 1 participants receive the intervention for 6 weeks. Outcomes are compared before and after implementation.
Interventions
Clinicians will use an ambient AI scribe as part of routine clinical care. The AI scribe captures the patient-clinician conversation, generates a draft clinical note, and supports documentation in the electronic health record. Clinicians receive training before beginning use of the AI scribe. The intervention is introduced in three sequential waves using a stepped-wedge design, with all participants eventually receiving the intervention.
Eligibility Criteria
You may qualify if:
- Must be a Clinician (attendings and advanced practice practitioners) who is part of the Emergency Medicine Department
- Must be willing to use Ambient AI as apart of their clinical practice work
You may not qualify if:
- Residents who are apart of the Emergency Medicine Department
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Washington University School of Medicine
St Louis, Missouri, 63110, United States
Related Publications (30)
Tierney, Aaron A., et al. "Ambient artificial intelligence scribes to alleviate the burden of clinical documentation." NEJM Catalyst Innovations in Care Delivery
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PMID: 31931523BACKGROUND
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Thomas Kannampallil, PhD
Washington University in Saint Louis
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- SINGLE
- Who Masked
- CARE PROVIDER
- Purpose
- HEALTH SERVICES RESEARCH
- Intervention Model
- SINGLE GROUP
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Professor and Director, Institute for Informatics, Data Science, and Biostatistics (I2DB), WashU Medicine Vice Chancellor for Biomedical Informatics and Data Science, WashU Medicine Chief Health AI Officer, BJC Health and WashU Medicine
Study Record Dates
First Submitted
July 21, 2026
First Posted
August 3, 2026
Study Start
April 29, 2026
Primary Completion (Estimated)
December 1, 2026
Study Completion (Estimated)
July 1, 2027
Last Updated
August 3, 2026
Record last verified: 2026-07
Data Sharing
- IPD Sharing
- Will not share