Literature DB >> 11447517

Voice recognition software versus a traditional transcription service for physician charting in the ED.

R G Zick1, J Olsen.   

Abstract

This study was conducted to compare real-time voice recognition software to a traditional transcription service. Two emergency department (ED) physicians dictated 47 charts using a voice dictation software program and a traditional transcription service. Accuracy, word per minute dictation time and turnaround time were calculated from the data. The transcription service used in our study was more accurate than the voice recognition program with an accuracy of 99.7 percent versus 98.5 percent for the voice recognition program. The average number of corrections per chart was 2.5 for the voice recognition program and 1.2 for the traditional transcription service. Turnaround time was much better using the computer voice recognition program with an average turnaround time of 3.65 minutes versus a turnaround time of 39.6 minutes for the traditionally transcribed charts. The charts dictated using the voice recognition program were considerably less costly than the manually transcribed charts. In summary, computer voice recognition is nearly as accurate as traditional transcription, it has a much shorter turnaround time and is less expensive than traditional transcription. We recommend its use as a tool for physician charting in the ED.

Mesh:

Year:  2001        PMID: 11447517     DOI: 10.1053/ajem.2001.24487

Source DB:  PubMed          Journal:  Am J Emerg Med        ISSN: 0735-6757            Impact factor:   2.469


  15 in total

1.  Impact of PACS and voice-recognition reporting on the education of radiology residents.

Authors:  Antonio J Gutierrez; Mark E Mullins; Robert A Novelline
Journal:  J Digit Imaging       Date:  2005-06       Impact factor: 4.056

Review 2.  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

3.  A usability framework for speech recognition technologies in clinical handover: a pre-implementation study.

Authors:  Linda Dawson; Maree Johnson; Hanna Suominen; Jim Basilakis; Paula Sanchez; Dominique Estival; Barbara Kelly; Leif Hanlen
Journal:  J Med Syst       Date:  2014-05-15       Impact factor: 4.460

4.  Incidence of speech recognition errors in the emergency department.

Authors:  Foster R Goss; Li Zhou; Scott G Weiner
Journal:  Int J Med Inform       Date:  2016-05-26       Impact factor: 4.046

5.  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

6.  Capturing patient information at nursing shift changes: methodological evaluation of speech recognition and information extraction.

Authors:  Hanna Suominen; Maree Johnson; Liyuan Zhou; Paula Sanchez; Raul Sirel; Jim Basilakis; Leif Hanlen; Dominique Estival; Linda Dawson; Barbara Kelly
Journal:  J Am Med Inform Assoc       Date:  2014-10-21       Impact factor: 4.497

7.  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

8.  Course Corrections for Clinical AI.

Authors:  Alex J DeGrave; Joseph D Janizek; Su-In Lee
Journal:  Kidney360       Date:  2021-09-27

9.  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

Review 10.  Mapping turnaround times (TAT) to a generic timeline: a systematic review of TAT definitions in clinical domains.

Authors:  Bernhard Breil; Fleur Fritz; Volker Thiemann; Martin Dugas
Journal:  BMC Med Inform Decis Mak       Date:  2011-05-24       Impact factor: 2.796

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