xRead - Incorporating Artificial Intelligence into Clinical Practice (March 2026)
Ng et al. BMC Medical Informatics and Decision Making
(2025) 25:236
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Acknowledgements We thank Dr Clyve Yu Leon Yaow and Mr Ansel Shao Pin Tang for helping to develop and refine the search strategies for this review. Author contributions All authors have made substantial contributions to all the following: (1) the conception and design of the study, or acquisition of data, or analysis and interpretation of data, (2) drafting the article or revising it critically for important intellectual content, (3) final approval of the version to be submitted. No writing assistance was obtained in the preparation of the manuscript. The manuscript, including related data, figures and tables has not been previously published, and the manuscript is not under consideration elsewhere. Conceptualization, Design and Methodology: K.X.Z., Q.X.N., Data Curation: K.X.Z., C.X.L.G., G.Z.N.S., S.S.N.G., Q.X.N., J.J.W.N., E.W., X.Z., Formal Analysis: K.X.Z., C.X.L.G., G.Z.N.S., Q.X.N., J.J.W.N., E.W., X.Z., S.S.N.G., H.K.T., Investigation: C.X.L.G., G.Z.N.S., K.X.Z., Q.X.N., J.J.W.N., E.W., X.Z., H.K.T., S.S.N.G., Supervision: H.K.T., S.S.N.G., Q.X.N., Writing– original draft: Q.X.N., J.J.W.N., E.W., X.Z., Writing– review & editing: K.X.Z., H.K.T., S.S.N.G., Q.X.N., J.J.W.N., E.W., X.Z.
D. The PRISMA 2020 statement: an updated guideline for reporting system atic reviews. BMJ. 2021;372:n71. https://doi.org/10.1136/bmj.n71. 7. Whiting PF, Rutjes AW, Westwood ME, Mallett S, Deeks JJ, Reitsma JB, Leeflang MM, Sterne JA, Bossuyt PM, QUADAS-2 Group. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011;155(8):529–36. https://doi.org/10.7326/0003-4819-155-8-201110180-00 009. 8. Popay J, Roberts H, Sowden A, Petticrew M, Arai L, Rodgers M, Britten N, Roen K, Duffy S. Guidance on the conduct of narrative synthesis in systematic reviews. A product from the ESRC. Methods Programme Version. 2006;1(1):b92. 9. Zick RG, Olsen J. Voice recognition software versus a traditional transcription service for physician charting in the ED. Am J Emerg Med. 2001;19(4):295–8. h ttps://doi.org/10.1053/ajem.2001.24487. 10. Happe A, Pouliquen B, Burgun A, Cuggia M, Le Beux P. Automatic concept extraction from spoken medical reports. Int J Med Inf. 2003;70(2–3):255–63. h ttps://doi.org/10.1016/s1386-5056(03)00055-8. 11. Mohr DN, Turner DW, Pond GR, Kamath JS, De Vos CB, Carpenter PC. Speech recognition as a transcription aid: a randomized comparison with standard transcription. J Am Med Inf Assoc. 2003 Jan-Feb;10(1):85–93. https://doi.org/1 0.1197/jamia.m1130. 12. Issenman RM, Jaffer IH. Use of voice recognition software in an outpatient pediatric specialty practice. Pediatrics. 2004;114(3):e290–3. https://doi.org/10. 1542/peds.2003-0724-L. 13. Almario CV, Chey W, Kaung A, Whitman C, Fuller G, Reid M, Nguyen K, Bolus R, Dennis B, Encarnacion R, Martinez B, Talley J, Modi R, Agarwal N, Lee A, Kubomoto S, Sharma G, Bolus S, Chang L, Spiegel BM. Computer-generated vs. physician-documented history of present illness (HPI): results of a blinded comparison. Am J Gastroenterol. 2015;110(1):170–9. https://doi.org/10.1038/ ajg.2014.356. 14. Almario CV, Chey WD, Iriana S, Dailey F, Robbins K, Patel AV, Reid M, Whitman C, Fuller G, Bolus R, Dennis B, Encarnacion R, Martinez B, Soares J, Modi R, Agarwal N, Lee A, Kubomoto S, Sharma G, Bolus S, Chang L, Spiegel BM. Computer versus physician identification of Gastrointestinal alarm features. Int J Med Inf. 2015;84(12):1111–7. https://doi.org/10.1016/j.ijmedinf.2015.07.0 06. 15. Suominen H, Johnson M, Zhou L, Sanchez P, Sirel R, Basilakis J, Hanlen L, Estival D, Dawson L, Kelly B. Capturing patient information at nursing shift changes: methodological evaluation of speech recognition and information extraction. J Am Med Inf Assoc. 2015;22(e1):e48–66. https://doi.org/10.1136/a miajnl-2014-002868. 16. Hodgson T, Magrabi F, Coiera E. Efficiency and safety of speech recognition for Documentation in the electronic health record. J Am Med Inf Assoc. 2017;24(6):1127–33. https://doi.org/10.1093/jamia/ocx073. 17. Kodish-Wachs J, Agassi E, Kenny P 3rd, Overhage JM. A systematic compari son of contemporary automatic speech recognition engines for conversa tional clinical speech. AMIA Annu Symp Proc. 2018;2018:683–689. 18. Lybarger K, Ostendorf M, Yetisgen M. Automatically detecting likely edits in clinical notes created using automatic speech recognition. AMIA Annu Symp Proc. 2018;2017:1186–95. 19. Zhou L, Blackley SV, Kowalski L, Doan R, Acker WW, Landman AB, Kontrient E, Mack D, Meteer M, Bates DW, Goss FR. Analysis of errors in dictated clinical documents assisted by speech recognition software and professional tran scriptionists. JAMA Netw Open. 2018;1(3):e180530. https://doi.org/10.1001/ja manetworkopen.2018.0530. 20. Goss FR, Blackley SV, Ortega CA, Kowalski LT, Landman AB, Lin CT, Meteer M, Bakes S, Gradwohl SC, Bates DW, Zhou L. A clinician survey of using speech recognition for clinical Documentation in the electronic health record. Int J Med Inf. 2019;130:103938. https://doi.org/10.1016/j.ijmedinf.2019.07.017. 21. Blackley SV, Schubert VD, Goss FR, Al Assad W, Garabedian PM, Zhou L. Physi cian use of speech recognition versus typing in clinical documentation: A controlled observational study. Int J Med Inf. 2020;141:104178. https://doi.org /10.1016/j.ijmedinf.2020.104178. 22. Van Woensel W, Taylor B, Abidi SSR. Towards an adaptive clinical transcription system for In-Situ transcribing of patient encounter information. Stud Health Technol Inf. 2022;290:158–62. https://doi.org/10.3233/SHTI220052. 23. Bundy H, Gerhart J, Baek S, Connor CD, Isreal M, Dharod A, Stephens C, Liu TL, Hetherington T, Cleveland J. Can the administrative loads of physicians be alleviated by AI-Facilitated clinical documentation? J Gen Intern Med. 2024;39(15):2995–3000. https://doi.org/10.1007/s11606-024-08870-z. 24. Cao DY, Silkey JR, Decker MC, Wanat KA. Artificial intelligence-driven digital scribes in clinical documentation: pilot study assessing the impact on
Data availability No datasets were generated or analysed during the current study.
Declarations
Competing interests The authors declare no competing interests.
Author details 1 NUS Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore 2 Department of Oral and Maxillofacial Surgery, McGill University Health Center, Montreal, Quebec, Canada 3 Division of Surgery and Surgical Oncology, Singapore General Hospital and National Cancer Centre Singapore, Singapore, Singapore 4 SingHealth Duke-NUS Global Health Institute, Singapore, Singapore 5 Duke Global Health Institute, Duke University, Durham, NC, USA 6 Department of Surgery, National University Hospital, Singapore, Singapore 7 Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
Received: 26 November 2024 / Accepted: 4 June 2025
References 1.
Kuhn T, Basch P, Barr M, Yackel T, Medical Informatics Committee of the American College of Physicians. Clinical Documentation in the 21st century: executive summary of a policy position paper from the American college of physicians. Ann Intern Med. 2015;162(4):301–3. https://doi.org/10.7326/M1 4-2128. 2. Moy AJ, Schwartz JM, Chen R, Sadri S, Lucas E, Cato KD, Rossetti SC. Measure ment of clinical Documentation burden among physicians and nurses using electronic health records: a scoping review. J Am Med Inf Assoc. 2021;28(5):998–1008. https://doi.org/10.1093/jamia/ocaa325. 3. Gesner E, Dykes PC, Zhang L, Gazarian P. Documentation burden in nursing and its role in clinician burnout syndrome. Appl Clin Inf. 2022;13(5):983–90. ht tps://doi.org/10.1055/s-0042-1757157. 4. Balloch J, Sridharan S, Oldham G, Wray J, Gough P, Robinson R, Sebire NJ, Khalil S, Asgari E, Tan C, Taylor A, Pimenta D. Use of an ambient artificial intel ligence tool to improve quality of clinical Documentation. Future Healthc J. 2024;11(3):100157. https://doi.org/10.1016/j.fhj.2024.100157. 5. Perkins SW, Muste JC, Alam T, Singh RP. Improving clinical Documentation with artificial intelligence: A systematic review. Perspect Health Inform Man age. 2024;21(2):1–25. 6. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, Shamseer L, Tetzlaff JM, Akl EA, Brennan SE, Chou R, Glanville J, Grimshaw JM, Hróbjartsson A, Lalu MM, Li T, Loder EW, Mayo-Wilson E, McDonald S, McGuinness LA, Stewart LA, Thomas J, Tricco AC, Welch VA, Whiting P, Moher
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