Literature DB >> 12509359

Speech recognition as a transcription aid: a randomized comparison with standard transcription.

David N Mohr1, David W Turner, Gregory R Pond, Joseph S Kamath, Cathy B De Vos, Paul C Carpenter.   

Abstract

OBJECTIVE: Speech recognition promises to reduce information entry costs for clinical information systems. It is most likely to be accepted across an organization if physicians can dictate without concerning themselves with real-time recognition and editing; assistants can then edit and process the computer-generated document. Our objective was to evaluate the use of speech-recognition technology in a randomized controlled trial using our institutional infrastructure.
DESIGN: Clinical note dictation from physicians in two specialty divisions was randomized to either a standard transcription process or a speech-recognition process. Secretaries and transcriptionists also were assigned randomly to each of these processes. MEASUREMENTS: The duration of each dictation was measured. The amount of time spent processing a dictation to yield a finished document also was measured. Secretarial and transcriptionist productivity, defined as hours of secretary work per minute of dictation processed, was determined for speech recognition and standard transcription.
RESULTS: Secretaries in the endocrinology division were 87.3% (confidence interval, 83.3%, 92.3%) as productive with the speech-recognition technology as implemented in this study as they were using standard transcription. Psychiatry transcriptionists and secretaries were similarly less productive. Author, secretary, and type of clinical note were significant (p < 0.05) predictors of productivity.
CONCLUSION: When implemented in an organization with an existing document-processing infrastructure (which included training and interfaces of the speech-recognition editor with the existing document entry application), speech recognition did not improve the productivity of secretaries or transcriptionists.

Mesh:

Year:  2003        PMID: 12509359      PMCID: PMC150361          DOI: 10.1197/jamia.m1130

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


  5 in total

1.  Comparative evaluation of three continuous speech recognition software packages in the generation of medical reports.

Authors:  E G Devine; S A Gaehde; A C Curtis
Journal:  J Am Med Inform Assoc       Date:  2000 Sep-Oct       Impact factor: 4.497

2.  How do you unload an obsolete computer?

Authors:  R Lowes
Journal:  Med Econ       Date:  2000-08-07

3.  Continuous speech recognition for clinicians.

Authors:  A Zafar; J M Overhage; C J McDonald
Journal:  J Am Med Inform Assoc       Date:  1999 May-Jun       Impact factor: 4.497

4.  Computer-based speech recognition as an alternative to medical transcription.

Authors:  S M Borowitz
Journal:  J Am Med Inform Assoc       Date:  2001 Jan-Feb       Impact factor: 4.497

5.  A voice-enabled, structured medical reporting system.

Authors:  D F Rosenthal; J M Bos; R A Sokolowski; J B Mayo; K A Quigley; R A Powell; M M Teel
Journal:  J Am Med Inform Assoc       Date:  1997 Nov-Dec       Impact factor: 4.497

  5 in total
  9 in total

Review 1.  Speech recognition implementation in radiology.

Authors:  Keith S White
Journal:  Pediatr Radiol       Date:  2005-05-18

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

3.  Asynchronous Speech Recognition Affects Physician Editing of Notes.

Authors:  Kevin J Lybarger; Mari Ostendorf; Eve Riskin; Thomas H Payne; Andrew A White; Meliha Yetisgen
Journal:  Appl Clin Inform       Date:  2018-10-17       Impact factor: 2.342

Review 4.  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

5.  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 6.  A systematic review of speech recognition technology in health care.

Authors:  Maree Johnson; Samuel Lapkin; Vanessa Long; Paula Sanchez; Hanna Suominen; Jim Basilakis; Linda Dawson
Journal:  BMC Med Inform Decis Mak       Date:  2014-10-28       Impact factor: 2.796

Review 7.  Artificial intelligence in clinical and genomic diagnostics.

Authors:  Raquel Dias; Ali Torkamani
Journal:  Genome Med       Date:  2019-11-19       Impact factor: 11.117

8.  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

9.  Physician experience with speech recognition software in psychiatry: usage and perspective.

Authors:  John Fernandes; Ian Brunton; Gillian Strudwick; Suman Banik; John Strauss
Journal:  BMC Res Notes       Date:  2018-10-01
  9 in total

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