Graduation Semester and Year
Spring 2026
Language
English
Document Type
DNP Project
Degree Name
Doctor of Nursing Practice
Department
Nursing
First Advisor
Kirstine Cope, DNP, MSN, RN, NEA-BC
Abstract
Background: Electronic health record (EHR) documentation burdens contribute to increased “pajama time” or after–hours charting, reduced job satisfaction, and provider burnout. Provider burnout leads to provider and critical access point losses. Ambient–listening artificial intelligence (AI) technologies have emerged as a possible tool to reduce charting burdens; however, evidence from outpatient wellness settings remains limited.
Local Problem: At an urban adult wellness clinic in Texas with limited resources for completing tasks, in-clinic and after-hours “pajama time” charting burdens contributed to provider fatigue, job dissatisfaction, and burnout.
Methods: A quality improvement (QI) project using the Plan-Do-Study-Act (PDSA) framework implemented an AI ambient listening documentation bundle consisting of DeepCura’s AI ambient–listening dictation tool, in-office and pajama time charting time tracking, dictation error tracking, and weekly provider wellness assessments. The intervention replaced the existing Dragon voice–to–text dictation with DeepCura’s AI ambient listening dictation during an eight-week implementation period. Outcome measures included clinic charting time per encounter, weekly “pajama time” spent charting, provider well-being scores, and clinical note accuracy. Descriptive analyses and inferential testing were used to evaluate pre- and post-implementation trends.
Results: The QI project achieved a 69.4% reduction in average clinic charting and eliminated pajama time charting by the end of the 8-week implementation period. Provider Well-Being Index scores improved across all domains, indicating a transition from elevated burnout risk to wellness. Documentation quality analysis indicated that DeepCura’s AI ambient listening dictation tool produced high-quality, accurate output.
Conclusions: Results demonstrated that integrating AI ambient listening dictation tools into clinical practice reduced charting times and improved provider wellness. Further evaluation is needed to determine long-term sustainability, patient experience effects, and long-term accuracy outcomes. This project contributed emerging evidence supporting AI-ambient listening dictation tools as a potential contribution to organizational strategies to address clinician burnout in small outpatient settings.
Keywords
Artificial Intelligence, Charting time, Provider burnout, “Pajama time”
Disciplines
Health Information Technology | Nursing Administration | Quality Improvement
License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Recommended Citation
Russette, Odia, "Ambient Listening: Using Artificial Intelligence to Transcribe Provider Office Visits" (2026). Doctor of Nursing Practice (DNP) Scholarly Projects-Archive. 128.
https://mavmatrix.uta.edu/nursing_dnpprojects/128
Included in
Health Information Technology Commons, Nursing Administration Commons, Quality Improvement Commons