xRead - Incorporating Artificial Intelligence into Clinical Practice (March 2026)
Ng et al. BMC Medical Informatics and Decision Making
(2025) 25:236
Page 24 of 24
dermatologist workflow and patient encounters. JAAD Int. 2024;15:149–51. h ttps://doi.org/10.1016/j.jdin.2024.02.009. 25. Haberle T, Cleveland C, Snow GL, Barber C, Stookey N, Thornock C, Younger L, Mullahkhel B, Ize-Ludlow D. The impact of nuance DAX ambient listening AI documentation: a cohort study. J Am Med Inf Assoc. 2024;31(4):975–9. https:/ /doi.org/10.1093/jamia/ocae022. 26. Islam MN, Mim ST, Tasfia T, Hossain MM. Enhancing patient treatment through automation: the development of an efficient scribe and prescribe system. Inf Med Unlocked. 2024;45:101456. 27. Liu TL, Hetherington TC, Stephens C, McWilliams A, Dharod A, Carroll T, Cleveland JA. AI-Powered clinical Documentation and clinicians’ electronic health record experience: A nonrandomized clinical trial. JAMA Netw Open. 2024;7(9):e2432460. https://doi.org/10.1001/jamanetworkopen.2024.32460. 28. Misurac J, Knake LA, Blum JM. The effect of ambient artificial intelligence notes on provider burnout. Appl Clin Inf. 2024. https://doi.org/10.1055/a-246 1-4576. 29. Owens LM, Wilda JJ, Grifka R, Westendorp J, Fletcher JJ. Effect of ambient voice technology, natural Language processing, and artificial intelligence on the Patient-Physician relationship. Appl Clin Inf. 2024;15(4):660–7. https://doi. org/10.1055/a-2337-4739. 30. Sezgin E, Sirrianni JW, Kranz K. Evaluation of a digital scribe: conversation summarization for emergency department consultation calls. Appl Clin Inf. 2024;15(3):600–11. https://doi.org/10.1055/a-2327-4121. 31. van Buchem MM, Kant IMJ, King L, Kazmaier J, Steyerberg EW, Bauer MP. Impact of a digital scribe system on clinical Documentation time and quality: usability study. JMIR AI. 2024;3:e60020. https://doi.org/10.2196/60020. 32. Biro J, Handley JL, Cobb NK, Kottamasu V, Collins J, Krevat S, Ratwani RM. Accuracy and safety of AI-Enabled scribe technology: instrument validation study. J Med Internet Res. 2025;27:e64993. https://doi.org/10.2196/64993. 33. Duggan MJ, Gervase J, Schoenbaum A, Hanson W, Howell JT 3rd, Shein berg M, Johnson KB. Clinician experiences with ambient scribe technology to assist with Documentation burden and efficiency. JAMA Netw Open. 2025;8(2):e2460637. https://doi.org/10.1001/jamanetworkopen.2024.60637. 34. Ma SP, Liang AS, Shah SJ, Smith M, Jeong Y, Devon-Sand A, Crowell T, Delahaie C, Hsia C, Lin S, Shanafelt T, Pfeffer MA, Sharp C, Garcia P. Ambient artificial
intelligence scribes: utilization and impact on Documentation time. J Am Med Inf Assoc. 2025;32(2):381–5. https://doi.org/10.1093/jamia/ocae304. 35. Moryousef J, Nadesan P, Uy M, Matti D, Guo Y. Assessing the efficacy and clini cal utility of artificial intelligence scribes in urology. Urology. 2025;196:12–7. h ttps://doi.org/10.1016/j.urology.2024.11.061. 36. Shah SJ, Devon-Sand A, Ma SP, Jeong Y, Crowell T, Smith M, Liang AS, Delahaie C, Hsia C, Shanafelt T, Pfeffer MA, Sharp C, Lin S, Garcia P. Ambient artificial intelligence scribes: physician burnout and perspectives on usability and Documentation burden. J Am Med Inf Assoc. 2025;32(2):375–80. https://doi.o rg/10.1093/jamia/ocae295. 37. Joseph J, Moore ZEH, Patton D, O’Connor T, Nugent LE. The impact of imple menting speech recognition technology on the accuracy and efficiency (time to complete) clinical Documentation by nurses: A systematic review. J Clin Nurs. 2020;29(13–14):2125–37. https://doi.org/10.1111/jocn.15261. 38. Koenecke A, Nam A, Lake E, Nudell J, Quartey M, Mengesha Z, Toups C, Rick ford JR, Jurafsky D, Goel S. Racial disparities in automated speech recognition. Proc Natl Acad Sci U S A. 2020;117(14):7684–9. https://doi.org/10.1073/pnas.1 915768117. 39. Blackley SV, Huynh J, Wang L, Korach Z, Zhou L. Speech recognition for clini cal Documentation from 1990 to 2018: a systematic review. J Am Med Inf Assoc. 2019;26(4):324–38. https://doi.org/10.1093/jamia/ocy179. 40. Gardner N, Khan H, Hung C-C. Definition modeling: literature review and dataset analysis. Appl. Comput. Intell. 2022;2:83–98. https://doi.org/10.3934/a ci.2022005. 41. Lawton J. NHS AI trial hailed as ‘remarkable’ and most ‘transformative’ tech in 15 years [Internet]. 2025 [cited 2025 Mar 10]. Available from: https://www.dail ystar.co.uk/news/latest-news/nhs-ai-trial-hailed-remarkable-34423254 Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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