Transforming clinical documentation with ambient artificial intelligence (AI) scribes: a narrative review of technology, impact, and implementation
Ambient AI scribes show promise in reducing workload, improving efficiency, and decreasing burnout, but current systems still generate high omission rates and intermittent factual inaccuracies that may affect clinical decision-making. Evidence remains limited by small cohorts and methodological variability, warranting cautious interpretation. More rigorous, standardized evaluations are needed before routine clinical adoption.
Authors
- Hesham Sheashaa
- Milagros Pereyra
- Mahshad Razaghi (ORCID: https://orcid.org/0000-0002-0756-3004)
- Isabel G. Scalia (ORCID: https://orcid.org/0000-0002-6459-9767)
- Kamal Awad (ORCID: https://orcid.org/0000-0001-6707-1629)
- Juan Farina (ORCID: https://orcid.org/0000-0002-5824-8485)
- Steven J. Lester
- Fatmaelzahraa E. Abdelfattah
- Chadi Ayoub
- Abdelrahman Hafez
Institutions
- WinnMed (US)
- Mayo Clinic in Florida (US)
Publication Details
- Journal
- Cardiovascular Diagnosis and Therapy
- Published
- 2026-01-21
- DOI
- https://doi.org/10.21037/cdt-2025-454
- Citations
- 1
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 17.70