Literature DB >> 15342888

Use of voice recognition software in an outpatient pediatric specialty practice.

Robert M Issenman1, Iqbal H Jaffer.   

Abstract

BACKGROUND: Voice recognition software (VRS), with specialized medical vocabulary, is being promoted to enhance physician efficiency, decrease costs, and improve patient safety. This study reports the experience of a pediatric subspecialist (pediatric gastroenterology) physician with the use of Dragon Naturally Speaking (version 6; ScanSoft Inc, Peabody, MA), incorporated for use with a proprietary electronic medical record, in a large university medical center ambulatory care service.
METHODS: After 2 hours of group orientation and 2 hours of individual VRS instruction, the physician trained the software for 1 month (30 letters) during a hospital slowdown. Set-up, dictation, and correction times for the physician and medical transcriptionist were recorded for these training sessions, as well as for 42 subsequently dictated letters. Figures were extrapolated to the yearly clinic volume for the physician, to estimate costs (physician: 110 dollars per hour; transcriptionist: 11 dollars per hour, US dollars).
RESULTS: The use of VRS required an additional 200% of physician dictation and correction time (9 minutes vs 3 minutes), compared with the use of electronic signatures for letters typed by an experienced transcriptionist and imported into the electronic medical record. When the cost of the license agreement and the costs of physician and transcriptionist time were included, the use of the software cost 100% more, for the amount of dictation performed annually by the physician.
CONCLUSIONS: VRS is an intriguing technology. It holds the possibility of streamlining medical practice. However, the learning curve and accuracy of the tested version of the software limit broad physician acceptance at this time.

Entities:  

Mesh:

Year:  2004        PMID: 15342888     DOI: 10.1542/peds.2003-0724-L

Source DB:  PubMed          Journal:  Pediatrics        ISSN: 0031-4005            Impact factor:   7.124


  11 in total

1.  Voice recognition dictation: radiologist as transcriptionist.

Authors:  John A Pezzullo; Glenn A Tung; Jeffrey M Rogg; Lawrence M Davis; Jeffrey M Brody; William W Mayo-Smith
Journal:  J Digit Imaging       Date:  2008-12       Impact factor: 4.056

2.  Towards spoken clinical-question answering: evaluating and adapting automatic speech-recognition systems for spoken clinical questions.

Authors:  Feifan Liu; Gokhan Tur; Dilek Hakkani-Tür; Hong Yu
Journal:  J Am Med Inform Assoc       Date:  2011-06-24       Impact factor: 4.497

Review 3.  Electronic Health Record Interactions through Voice: A Review.

Authors:  Yaa A Kumah-Crystal; Claude J Pirtle; Harrison M Whyte; Edward S Goode; Shilo H Anders; Christoph U Lehmann
Journal:  Appl Clin Inform       Date:  2018-07-18       Impact factor: 2.342

4.  Digital dictation and voice transcription software enhances outpatient clinic letter production: a crossover study.

Authors:  Kinesh Patel; Marcus Harbord
Journal:  Frontline Gastroenterol       Date:  2012-04-24

5.  The effect of seniority and education on departmental dictation utilization.

Authors:  Kevin C Bax; Kambiz Norozi; Ajay P Sharma; Guido Filler
Journal:  Health Econ Rev       Date:  2011-07-20

6.  Lessons learned from implementation of voice recognition for documentation in the military electronic health record system.

Authors:  Robert Hoyt; Ann Yoshihashi
Journal:  Perspect Health Inf Manag       Date:  2010-01-01

Review 7.  Risks and benefits of speech recognition for clinical documentation: a systematic review.

Authors:  Tobias Hodgson; Enrico Coiera
Journal:  J Am Med Inform Assoc       Date:  2015-11-17       Impact factor: 4.497

8.  Speech recognition software and electronic psychiatric progress notes: physicians' ratings and preferences.

Authors:  Yaron D Derman; Tamara Arenovich; John Strauss
Journal:  BMC Med Inform Decis Mak       Date:  2010-08-25       Impact factor: 2.796

9.  Analysis of Documentation Speed Using Web-Based Medical Speech Recognition Technology: Randomized Controlled Trial.

Authors:  Markus Vogel; Wolfgang Kaisers; Ralf Wassmuth; Ertan Mayatepek
Journal:  J Med Internet Res       Date:  2015-11-03       Impact factor: 5.428

10.  Typed versus voice recognition for data entry in electronic health records: emergency physician time use and interruptions.

Authors:  Jonathan E Dela Cruz; John C Shabosky; Matthew Albrecht; Ted R Clark; Joseph C Milbrandt; Steven J Markwell; Jason A Kegg
Journal:  West J Emerg Med       Date:  2014-07
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