Literature DB >> 22032576

Voice recognition technology implementation in surgical pathology: advantages and limitations.

Meenakshi Singh1, Timothy R Pal.   

Abstract

CONTEXT: Voice recognition technology (VRT) has been in use for medical transcription outside of laboratories for many years, and in recent years it has evolved to a level where it merits consideration by surgical pathologists.
OBJECTIVE: To determine the feasibility and impact of making a transition from a transcriptionist-based service to VRT in surgical pathology.
DESIGN: We have evaluated VRT in a phased manner for sign out of general and subspecialty surgical pathology cases after conducting a pilot study. We evaluated the effect on turnaround time, workflow, staffing, typographical error rates, and the overall ability of VRT to be adapted for use in surgical pathology.
RESULTS: The stepwise implementation of VRT has resulted in real-time sign out of cases and improvement in average turnaround time from 4 to 3 days. The percentage of cases signed out in 1 day improved from 22% to 37%. Amendment rates for typographical errors have decreased. Use of templates and synoptic reports has been facilitated. The transcription staff has been reassigned to other duties and is successfully assisting in other areas. Resident involvement and exposure to complete case sign out has been achieved resulting in a positive impact on resident education.
CONCLUSIONS: Voice recognition technology allows for a seamless workflow in surgical pathology, with improvements in turnaround time and a positive impact on competency-based resident education. Individual practices may assess the value of VRT and decide to implement it, potentially with gains in many aspects of their practice.

Mesh:

Year:  2011        PMID: 22032576     DOI: 10.5858/arpa.2010-0714-OA

Source DB:  PubMed          Journal:  Arch Pathol Lab Med        ISSN: 0003-9985            Impact factor:   5.534


  5 in total

1.  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

2.  Language-Based Process Phase Detection in the Trauma Resuscitation.

Authors:  Yue Gu; Xinyu Li; Shuhong Chen; Hunagcan Li; Richard A Farneth; Ivan Marsic; Randall S Burd
Journal:  IEEE Int Conf Healthc Inform       Date:  2017-09-14

Review 3.  Challenges in the pathology of non-muscle-invasive bladder cancer: a dialogue between the urologic surgeon and the pathologist.

Authors:  Donna E Hansel; Jeremy S Miller; Michael S Cookson; Sam S Chang
Journal:  Urology       Date:  2013-03-19       Impact factor: 2.649

4.  Benchmarking clinical speech recognition and information extraction: new data, methods, and evaluations.

Authors:  Hanna Suominen; Liyuan Zhou; Leif Hanlen; Gabriela Ferraro
Journal:  JMIR Med Inform       Date:  2015-04-27

Review 5.  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

  5 in total

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