Impact of a Digital Scribe System on Clinical Documentation Time and Quality: Usability Study

Journals

1. Alli S, Hossain S, Das S, Upshur R. The Potential of Artificial Intelligence Tools for Reducing Uncertainty in Medicine and Directions for Medical Education. JMIR Medical Education 2024;10:e51446 View
2. Saadat S, Khalilizad Darounkolaei M, Qorbani M, Hemmat A, Hariri S. Enhancing Clinical Documentation with AI: Reducing Errors, Improving Interoperability, and Supporting Real-Time Note-Taking. InfoScience Trends 2025;2(1):1 View
3. Biro J, Handley J, Cobb N, Kottamasu V, Collins J, Krevat S, Ratwani R. Accuracy and Safety of AI-Enabled Scribe Technology: Instrument Validation Study. Journal of Medical Internet Research 2025;27:e64993 View
4. Rashid Z, Ahmed H, Nadeem N, Zafar S, Yousaf M. The paradigm of digital health: AI applications and transformative trends. Neural Computing and Applications 2025;37(17):11039 View
5. Gilchrist C, Goldszmidt M. Proceed with caution: Conceptualizing the risk of artificial intelligence scribes in medical education. Medical Teacher 2025:1 View
6. Ha E, Choon-Kon-Yune I, Murray L, Luan S, Montague E, Bhattacharyya O, Agarwal P. Evaluating the Usability, Technical Performance, and Accuracy of Artificial Intelligence Scribes for Primary Care: Competitive Analysis. JMIR Human Factors 2025;12:e71434 View
7. Sasseville M, Yousefi F, Ouellet S, Naye F, Stefan T, Carnovale V, Bergeron F, Ling L, Gheorghiu B, Hagens S, Gareau-Lajoie S, LeBlanc A. The Impact of AI Scribes on Streamlining Clinical Documentation: A Systematic Review. Healthcare 2025;13(12):1447 View
8. Ng J, Wang E, Zhou X, Zhou K, Goh C, Sim G, Tan H, Goh S, Ng Q. Evaluating the performance of artificial intelligence-based speech recognition for clinical documentation: a systematic review. BMC Medical Informatics and Decision Making 2025;25(1) View
9. Devereux C, Jacob B, Araz K, Bullen C, Murphy C, Redmond P. Protocol for a Scoping Review of Digital Scribes in Primary Care: Design, Implementation, Accuracy and Impact. HRB Open Research 2025;8:79 View
10. Clusmann J, Balaguer-Montero M, Bassegoda O, Schneider C, Seraphin T, Paintsil E, Luedde T, Lopez R, Calderaro J, Gilbert S, Marjot T, Spann A, Shawcross D, Lens S, Trépo E, Kather J. The barriers to uptake of artificial intelligence in hepatology and how to overcome them. Journal of Hepatology 2025;83(6):1410 View
11. Pérez Martínez D. Proposal for Responsible Use of Generative Artificial Intelligence in Medical Practice. Revista de Neurología 2025;80(7) View
12. Draper T, Leake J, Lamb-Riddell K, Cox T, McCormick J, Trowell S, Kiely J, Luxton R. Impact of acoustic and informational noise on AI-generated clinical summaries. BMJ Digital Health & AI 2025;1(1):e000057 View
13. Draper T, Cox T, Lamb-Riddell K, Moretti L, McCormick J, Trowell S, Kiely J, Luxton R. Clinical AI Scribes in primary care: accuracy, error severity and implications for clinical practice. BMJ Digital Health & AI 2025;1(1):e000092 View
14. Leiserowitz G, Mansfield J, Tamakuwala S, MacDonald S, Jost M. Patient Attitudes Towards Ambient Voice Technology: A Pre-Implementation Patient Survey in an Academic Medical Center (Preprint). JMIR Medical Informatics 2025 View
15. Anderson T, Mohan V, Dorr D, Ratwani R, Biro J, Gold J. Evaluating the Quality and Safety of Ambient Digital Scribe Platforms Using Simulated Ambulatory Encounters. Mayo Clinic Proceedings: Digital Health 2025;3(4):100292 View
16. Moura L, Mishuris R, Metlay J, Habib M, Ting D, Gallagher K, Brodney S, Rieu-Werden M, Haas J. Hybrid Ambient Clinical Documentation and Physician Performance: Work Outside of Work, Documentation Delay, and Financial Productivity. Journal of General Internal Medicine 2025 View
17. Van Tiem J, Cramer E, Iverson C, Kennelty K, Andrys N, Lee J, Knake L, Misurac J, Blum J, Reisinger H. Listening to the note: clinician perspectives on ambient artificial intelligence scribes in medical documentation. Journal of the American Medical Informatics Association 2025 View
18. Clusmann J, Schneider C, Foersch S, Truhn D, Kather J. Künstliche Intelligenz: Chancen und Grenzen. Forum 2025 View
19. Cittadino J, Traulsen P, Schmahl T, Wewetzer L, Cummerow J, Flägel K, Strumann C, Goetz K, Steinhäuser J. Information Extraction of Doctoral Theses Using Two Different Large Language Models vs Health Services Researchers: Development and Usability Study. JMIR Formative Research 2025;9:e77707 View
20. Dundas N, Law T, Brender T, Mills H, Espejo E, A. Heintz T, Wallace A, Cobert J. All That Shines Is Not Gold: Maintaining Scientific Rigor When Evaluating, Interpreting, and Reviewing Studies Using Large Language Models. Anesthesiology 2025 View
21. Yost C, Jumreornvong O, Hasoon J, Ruan Q, Ang S, Palumbo P, Bianco G, Yong R, Zetter G, Christo P, Kaye A, Hilger H, Chung M, Duszynski B, Robinson C. Artificial Intelligence-Assisted Scribing for Chronic Pain Care: A Narrative Review. Current Pain and Headache Reports 2026;30(1) View
22. Woo B, Cato K, Cho H, You S, Song J. The use of large language models in clinical documentation: A scoping review. International Journal of Nursing Studies 2025:105322 View
23. Zhao J, Liu H, Chen Y, Song F. Application of artificial intelligence tools and clinical documentation burden: a systematic review and meta-analysis. BMC Medical Informatics and Decision Making 2025 View

Books/Policy Documents

1. R. Wojda T, Vino Dominic Savio F, Hochheiser H, Amaravathi A, Bharat K, Fischer G. Artificial Intelligence in Medicine and Surgery - An Exploration of Current Trends, Potential Opportunities, and Evolving Threats, Volume 3 [Working Title]. View

Dissertations

1. . Implementation of Artificial Intelligence for Scribing in an Outpatient Mental Health Clinic. View