Literature DB >> 28839659

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

Kinesh Patel1, Marcus Harbord1.   

Abstract

BACKGROUND: Digital voice transcription has been introduced widely in the National Health Service (NHS), though primarily in radiology departments. There has been a long-standing problem with recruitment of medical secretaries within the NHS, leading to long delays in the production of correspondence from outpatient clinics.
OBJECTIVE: To determine whether use of widely available digital transcription software improves efficiency and the time taken to produce correspondence.
METHODS: The project used a prospective, crossover trial design in a 'real-world' environment. Correspondence from clinics was transcribed after dictation by a secretary using conventional analogue audio tape or the dictation software. After a 2-week washout period the same clinics' dictations were transcribed using the other method to produce identical correspondence. The two sets of letters were compared.
RESULTS: The mean time for the secretary to produce letters for a complete clinic using digital dictation was 66 min whereas analogue dictation took 121 min (p<0.00002). There was no difference in the number of mistakes per letter (p>0.05).
CONCLUSION: Voice transcription software significantly decreased the time taken to transcribe outpatient clinic letters with minimal training of secretarial staff, resulting in improved efficiency.

Entities:  

Year:  2012        PMID: 28839659      PMCID: PMC5517278          DOI: 10.1136/flgastro-2011-100100

Source DB:  PubMed          Journal:  Frontline Gastroenterol        ISSN: 2041-4137


  11 in total

1.  The utility and cost effectiveness of voice recognition technology in surgical pathology.

Authors:  Walter H Henricks; Kavous Roumina; Bradley E Skilton; Debra J Ozan; Gwendolyn R Goss
Journal:  Mod Pathol       Date:  2002-05       Impact factor: 7.842

2.  Comparison of voice-automated transcription and human transcription in generating pathology reports.

Authors:  Maamoun M Al-Aynati; Katherine A Chorneyko
Journal:  Arch Pathol Lab Med       Date:  2003-06       Impact factor: 5.534

3.  Voice recognition versus transcriptionist: error rates and productivity in MRI reporting.

Authors:  Rodney H Strahan; Michal E Schneider-Kolsky
Journal:  J Med Imaging Radiat Oncol       Date:  2010-10       Impact factor: 1.735

4.  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

5.  Effect of voice recognition on radiologist reporting time.

Authors:  Sasha N Bhan; Craig L Coblentz; Geoffrey R Norman; Sammy H Ali
Journal:  Can Assoc Radiol J       Date:  2008-10       Impact factor: 2.248

6.  The effect of voice recognition software on comparative error rates in radiology reports.

Authors:  S McGurk; K Brauer; T V Macfarlane; K A Duncan
Journal:  Br J Radiol       Date:  2008-07-15       Impact factor: 3.039

7.  Voice recognition for radiology reporting: is it good enough?

Authors:  D S Rana; G Hurst; L Shepstone; J Pilling; J Cockburn; M Crawford
Journal:  Clin Radiol       Date:  2005-11       Impact factor: 2.350

8.  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

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

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

Authors:  Robert M Issenman; Iqbal H Jaffer
Journal:  Pediatrics       Date:  2004-09       Impact factor: 7.124

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