TY  - JOUR
AU  - Kanaparthy, Naga Sasidhar
AU  - Villuendas-Rey, Yenny
AU  - Bakare, Tolulope
AU  - Diao, Zihan
AU  - Iscoe, Mark
AU  - Loza, Andrew
AU  - Wright, Donald
AU  - Safranek, Conrad
AU  - Faustino, Isaac V
AU  - Brackett, Alexandria
AU  - Melnick, Edward R
AU  - Taylor, R Andrew
PY  - 2025
DA  - 2025/10/10
TI  - Real-World Evidence Synthesis of Digital Scribes Using Ambient Listening and Generative Artificial Intelligence for Clinician Documentation Workflows: Rapid Review
JO  - JMIR AI
SP  - e76743
VL  - 4
KW  - digital scribes
KW  - artificial intelligence in medicine
KW  - clinical documentation
KW  - speech recognition software
KW  - patient-clinician communication
AB  - Background: As physicians spend up to twice as much time on electronic health record tasks as on direct patient care, digital scribes have emerged as a promising solution to restore patient-clinician communication and reduce documentation burden—making it essential to study their real-world impact on clinical workflows, efficiency, and satisfaction. Objective: This study aimed to synthesize evidence on clinician efficiency, user satisfaction, quality, and practical barriers associated with the use of digital scribes using ambient listening and generative artificial intelligence (AI) in real-world clinical settings. Methods: A rapid review was conducted to evaluate the real-world evidence of digital scribes using ambient listening and generative AI in clinical practice from 2014 to 2024. Data were collected from Ovid MEDLINE, Embase, Web of Science–Core Collection, Cochrane CENTRAL and Reviews, and PubMed Central. Predefined eligibility criteria focused on studies addressing clinical implementation, excluding those centered solely on technical development or model validation. The findings of each study were synthesized and analyzed through the QUEST human evaluation framework for quality and safety and the Systems Engineering Initiative for Patient Safety (SEIPS) 3.0 model to assess integration into clinicians’ workflows and experience. Results: Of the 1450 studies identified, 6 met the inclusion criteria. These studies included an observational study, a case report, a peer-matched cohort study, and survey-based assessments conducted across academic health systems, community settings, and outpatient practices. The major themes noted were as follows: (1) they decreased self-reported documentation times, with associated increased length of notes; (2) physician burnout measured using standardized scales was unaffected, but physician engagement improved; (3) physician productivity, assessed via billing metrics, was unchanged; and (4) the studies fell short when compared to standardized frameworks. Conclusions: Digital scribes show promise in reducing documentation burden and enhancing clinician satisfaction, thereby supporting workflow efficiency. However, the currently available evidence is sparse. Future real-world, multifaceted studies are needed before AI scribes can be recommended unequivocally. 
SN  - 2817-1705
UR  - https://ai.jmir.org/2025/1/e76743
UR  - https://doi.org/10.2196/76743
DO  - 10.2196/76743
ID  - info:doi/10.2196/76743
ER  -