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A systematic review of speech recognition technology in health care
BACKGROUND: To undertake a systematic review of existing literature relating to speech recognition technology and its application within health care. METHODS: A systematic review of existing literature from 2000 was undertaken. Inclusion criteria were: all papers that referred to speech recognition...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4283090/ https://www.ncbi.nlm.nih.gov/pubmed/25351845 http://dx.doi.org/10.1186/1472-6947-14-94 |
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author | Johnson, Maree Lapkin, Samuel Long, Vanessa Sanchez, Paula Suominen, Hanna Basilakis, Jim Dawson, Linda |
author_facet | Johnson, Maree Lapkin, Samuel Long, Vanessa Sanchez, Paula Suominen, Hanna Basilakis, Jim Dawson, Linda |
author_sort | Johnson, Maree |
collection | PubMed |
description | BACKGROUND: To undertake a systematic review of existing literature relating to speech recognition technology and its application within health care. METHODS: A systematic review of existing literature from 2000 was undertaken. Inclusion criteria were: all papers that referred to speech recognition (SR) in health care settings, used by health professionals (allied health, medicine, nursing, technical or support staff), with an evaluation or patient or staff outcomes. Experimental and non-experimental designs were considered. Six databases (Ebscohost including CINAHL, EMBASE, MEDLINE including the Cochrane Database of Systematic Reviews, OVID Technologies, PreMED-LINE, PsycINFO) were searched by a qualified health librarian trained in systematic review searches initially capturing 1,730 references. Fourteen studies met the inclusion criteria and were retained. RESULTS: The heterogeneity of the studies made comparative analysis and synthesis of the data challenging resulting in a narrative presentation of the results. SR, although not as accurate as human transcription, does deliver reduced turnaround times for reporting and cost-effective reporting, although equivocal evidence of improved workflow processes. CONCLUSIONS: SR systems have substantial benefits and should be considered in light of the cost and selection of the SR system, training requirements, length of the transcription task, potential use of macros and templates, the presence of accented voices or experienced and in-experienced typists, and workflow patterns. |
format | Online Article Text |
id | pubmed-4283090 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-42830902015-01-06 A systematic review of speech recognition technology in health care Johnson, Maree Lapkin, Samuel Long, Vanessa Sanchez, Paula Suominen, Hanna Basilakis, Jim Dawson, Linda BMC Med Inform Decis Mak Research Article BACKGROUND: To undertake a systematic review of existing literature relating to speech recognition technology and its application within health care. METHODS: A systematic review of existing literature from 2000 was undertaken. Inclusion criteria were: all papers that referred to speech recognition (SR) in health care settings, used by health professionals (allied health, medicine, nursing, technical or support staff), with an evaluation or patient or staff outcomes. Experimental and non-experimental designs were considered. Six databases (Ebscohost including CINAHL, EMBASE, MEDLINE including the Cochrane Database of Systematic Reviews, OVID Technologies, PreMED-LINE, PsycINFO) were searched by a qualified health librarian trained in systematic review searches initially capturing 1,730 references. Fourteen studies met the inclusion criteria and were retained. RESULTS: The heterogeneity of the studies made comparative analysis and synthesis of the data challenging resulting in a narrative presentation of the results. SR, although not as accurate as human transcription, does deliver reduced turnaround times for reporting and cost-effective reporting, although equivocal evidence of improved workflow processes. CONCLUSIONS: SR systems have substantial benefits and should be considered in light of the cost and selection of the SR system, training requirements, length of the transcription task, potential use of macros and templates, the presence of accented voices or experienced and in-experienced typists, and workflow patterns. BioMed Central 2014-10-28 /pmc/articles/PMC4283090/ /pubmed/25351845 http://dx.doi.org/10.1186/1472-6947-14-94 Text en © Johnson et al.; licensee BioMed Central Ltd. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Johnson, Maree Lapkin, Samuel Long, Vanessa Sanchez, Paula Suominen, Hanna Basilakis, Jim Dawson, Linda A systematic review of speech recognition technology in health care |
title | A systematic review of speech recognition technology in health care |
title_full | A systematic review of speech recognition technology in health care |
title_fullStr | A systematic review of speech recognition technology in health care |
title_full_unstemmed | A systematic review of speech recognition technology in health care |
title_short | A systematic review of speech recognition technology in health care |
title_sort | systematic review of speech recognition technology in health care |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4283090/ https://www.ncbi.nlm.nih.gov/pubmed/25351845 http://dx.doi.org/10.1186/1472-6947-14-94 |
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