Volume 7, Issue 6, November 2019, Page: 147-150
The Adjunct of Voice Recognition to Medical Transcriptionist in Asian Countries–The Pros and Cons
Amjad Sattar, Dow Institute of Radiology, Dow University of Health Sciences, Karachi, Pakistan
Mahnoor Hafeez, Dow Institute of Radiology, Dow University of Health Sciences, Karachi, Pakistan
Received: Jul. 14, 2019;       Accepted: Aug. 19, 2019;       Published: Oct. 26, 2019
DOI: 10.11648/j.ajim.20190706.12      View  55      Downloads  15
Abstract
Voice recognition software (VRS) is a form of Artificial intelligence; it’s a phenomenon of converting or transcribing acoustic human speech (i.e. sound waves) into a symbolic form of a human language such as English whereas Dictaphone (DP) is an electronic voice recorder analogous to cell phone that saves and records voice files. The Radiologists believe that Report generation in Radiology is a daunting task, including reading scans, requiring analytical and observational skills, interpretation of findings, dictating cases, proof reading, re analyzing cases and signing off after corrections, especially when the case list is long. In solving this multi-step process, VRS and DP have emerged as handy tech savvy equipments for “automatic typing” of scans, with the involvement of Medical transcriptionist (MT) for timely generation of reports. In the past few decades, there has been considerable transition from manual hand signed reports to electronically generated reports. MT has been a closed companion of Radiologist, even in manually generated reports. There has been a threat to MT being replaced by VRS at tertiary care hospitals, because of its low economic impact. The pros and cons of tool are elaborated in this article with the survey of Radiology Institutes of Pakistan.
Keywords
Voice Recognition Software, VRS, Dictaphone, Medical Transcriptionist, MT, Clinical Practice
To cite this article
Amjad Sattar, Mahnoor Hafeez, The Adjunct of Voice Recognition to Medical Transcriptionist in Asian Countries–The Pros and Cons, American Journal of Internal Medicine. Vol. 7, No. 6, 2019, pp. 147-150. doi: 10.11648/j.ajim.20190706.12
Copyright
Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Reference
[1]
Ringler MD, Goss BC, Bartholmai BJ. Syntactic and Semantic Errors in Radiology Reports Associated With Speech Recognition Software. Stud Health Technol Inform. 2015; 216: 922.
[2]
Tang A, Tam R, Cadrin-Chênevert A, Guest W, Chong J, Barfett J et al. Canadian Association of Radiologists White Paper on Artificial Intelligence in Radiology. Can Assoc Radiol J. 2018 May; 69 (2): 120-135.
[3]
Graham-C Andrew. How I Use It: Voice recognition software. Occupational Medicine, Volume 62, Issue 4, 4 June 2012, Page 315.
[4]
Mehta A. (2002) Voice Recognition. In: Dreyer K. J., Mehta A., Thrall J. H. (eds) PACS. Springer, New York, NY
[5]
Gale B, Safriel Y, Lukban A, Kalowitz J, Fleischer J, Gordon D. Radiology report production times: voice recognition vs. transcription. Radiol Manage. 2001 Mar-Apr; 23 (2): 18-22.
[6]
Sferrella SM. Success with voice recognition. Radiol Manage. 2003 May-Jun; 25 (3): 42-9.
[7]
Krishnaraj A, Lee JK, Laws SA, Crawford TJ. Voice recognition software: effect on radiology report turnaround time at an academic medical center. AJR Am J Roentgenol. 2010 Jul; 195 (1): 194-7.
[8]
Strahan RH, Schneider-Kolsky ME. Voice recognition versus transcriptionist: error rates and productivity in MRI reporting. J Med Imaging Radiat Oncol. 2010 Oct; 54 (5): 411-4.
[9]
Hafeez M., Khalid D., Mirza W, Nadeem N. Radiology Reporting Errors; Voice Recognition Software versus Dictation Transcription Methods in Non-Native English Speakers. 19th PGME Conference - Enhancing Academic Standards for Quality Care, Aga Khan University Hospital, Pakistan, May 2014.
[10]
Pezzullo JA, Tung GA, Rogg JM, Davis LM, Brody JM, Mayo-Smith WW. Voice recognition dictation: radiologist as transcriptionist. J Digit Imaging. 2008 Dec; 21 (4): 384-9.
[11]
Rana DS, Hurst G, Shepstone L, Pilling J, Cockburn J, Crawford M. Voice recognition for radiology reporting: is it good enough? Clin Radiol. 2005. Nov; 60 (11): 1205-12.
[12]
McGurk S, Brauer K, Macfarlane TV, Duncan KA. The effect of voice recognition software on comparative error rates in radiology reports. Br J Radiol. 2008 Oct; 81 (970): 767-70.
[13]
Rosenthal DI, Chew FS, Dupuy DE, Kattapuram SV, Palmer WE, Yap RM, Levine LA. Computer-based speech recognition as a replacement for medical transcription. AJR Am J Roentgenol. 1998 Jan; 170 (1): 23-5.
[14]
Chang CA, Strahan R, Jolley D. Non-clinical errors using voice recognition dictation software for radiology reports: a retrospective audit. J Digit Imaging. 2011 Aug; 24 (4): 724-8. doi: 10.1007/s10278-010-9344-z.
[15]
Bhan SN, Coblentz CL, Norman GR, Ali SH. Effect of voice recognition on radiologist reporting time. Can Assoc Radiol J. 2008 Oct; 59 (4): 203-9.
Browse journals by subject