Skip to main content
×
×
Home

Voice recognition software: psychiatrist as transcriber

  • Malarvizhi Babu Sandilyan (a1) and Jonathan Darley (a1)
Abstract
Aims and method

Voice recognition software is promoted to improve clinician efficiency and decrease overall costs. Our aim was to compare its efficiency against the traditional method of dictation and typing in an older people's community mental health team. We compared the time taken to dictate, edit and type letters, and the total number of days required to send them out after seeing the patient, using the two methods. We also correlated the time taken by one doctor to dictate and edit clinic letters with the actual days on which they were dictated.

Results

The voice recognition system reduced the time taken to turn around clinic letters but at the cost of increased doctor's time being spent on dictating and editing the letters. We found no increase in efficiency with experience.

Clinical implications

The benefits of faster letter production may be outweighed by the effect of the extra time spent by clinicians to the detriment of their other commitments. The narrative form of psychiatry letters may make them less suited to computer transcription than those in other specialties.

  • View HTML
    • Send article to Kindle

      To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

      Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

      Find out more about the Kindle Personal Document Service.

      Voice recognition software: psychiatrist as transcriber
      Available formats
      ×
      Send article to Dropbox

      To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

      Voice recognition software: psychiatrist as transcriber
      Available formats
      ×
      Send article to Google Drive

      To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

      Voice recognition software: psychiatrist as transcriber
      Available formats
      ×
Copyright
This is an Open Access article, distributed under the terms of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Corresponding author
Malarvizhi Babu Sandilyan (dr.malar@gmail.com)
Footnotes
Hide All

Declaration of interest

None.

Footnotes
References
Hide All
1 Alwang, G, Stinson, C. Speech recognition: finding its voice. PC Mag 1998; 17: 191–8.
2 De Bruijn, LM, Verheijen, E, Hasman, A, Van Nes, FL, Arends, JW. Speech interfacing for diagnosis reporting systems: an overview. Comput Methods Programs Biomed 1995; 48: 151–6.
3 Leeming, BW, Porter, D, Jackson, JD, Bleich, HL, Simon, M. Computerized radiology reporting with voice data-entry. Radiology 1981; 138: 585–8.
4 Al-Aynati, MM, Chorneyko, KA. Comparison of voice automated transcription and human transcription in generating pathology reports. Arch Pathol Lab Med 2003; 127: 721–5.
5 Rana, DS, Hurst, G, Shepstone, L, Pilling, J, Cockburn, J, Crawford, M. Voice recognition for radiology reporting: is it good enough? Clin Radiol 2005; 60: 1205–12.
6 Zick, R, Olsen, J. Voice recognition software versus a traditional transcription service for physician charting in the ED. Am J Emerg Med 2001; 19: 295–8.
7 Hayt, DB, Alexander, S. The pros and cons of implementing PACS and speech recognition systems. J Digit Imaging 2001; 14: 149–57.
8 Ramaswamy, MR, Chaljub, G, Esch, O, Fanning, DD, van Sonnenberg, E. Continuous speech recognition in MR imaging reporting: advantages, disadvantages, and impact. AJR Am J Roentgenol 2000; 174: 617–22.
9 Chapman, WW, Aronsky, D, Fiszman, M, Haug, PJ. Contribution of a speech recognition system to a computerized pneumonia guideline in the emergency department. Proc AMIA Symp 2000; 131–5.
10 Kauppinen, T, Koivikko, MP, Ahovuo, J. Improvement of report workflow and productivity using speech recognition: a follow up study. J Digit Imaging 2008; 21: 378–82.
11 Lemme, PJ, Morin, RL. The implementation of speech recognition in an electronic radiology practice. J Digit Imaging 2000; 13 (suppl 1): 153–4.
12 Bhan, SN, Coblentz, CL, Norman, GR, Ali, SH. Effect of voice recognition on radiologist reporting time. Can Assoc Radiol J 2008; 59: 203–9.
13 Schwartz, LH, Kijewski, P, Hertogen, H, Roossin, PS, Castellino, RA. Voice recognition in radiology reporting. AJR Am J Roentgenol 1997; 169: 27–9.
14 Pezzullo, JA, Tung, GA, Rogg, JM, Davis, LM, Brody, JM, Mayo-Smith, WW. Voice recognition dictation: radiologist as transcriptionist. J Digit Imaging 2008; 21: 384–9.
Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

BJPsych Bulletin
  • ISSN: 1758-3209
  • EISSN: 1758-3217
  • URL: /core/journals/bjpsych-bulletin
Please enter your name
Please enter a valid email address
Who would you like to send this to? *
×

Metrics

Full text views

Total number of HTML views: 0
Total number of PDF views: 25 *
Loading metrics...

Abstract views

Total abstract views: 46 *
Loading metrics...

* Views captured on Cambridge Core between 2nd January 2018 - 20th July 2018. This data will be updated every 24 hours.

Voice recognition software: psychiatrist as transcriber

  • Malarvizhi Babu Sandilyan (a1) and Jonathan Darley (a1)
Submit a response

eLetters

No eLetters have been published for this article.

×

Reply to: Submit a response


Your details


Conflicting interests

Do you have any conflicting interests? *