A systematic review of speech recognition technology in health care

Maree Johnson, Samuel Lapkin, Vanessa Long, Paula Sanchez, Hanna Suominen, Jim Basilakis, Linda Dawson

    Research output: Contribution to journalArticlepeer-review

    103 Citations (Scopus)

    Abstract

    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.
    Original languageEnglish
    Article number94
    Number of pages14
    JournalBMC Medical Informatics and Decision Making
    Volume14
    DOIs
    Publication statusPublished - 2014

    Open Access - Access Right Statement

    © 2014 Johnson et al.; licensee 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.

    Keywords

    • interactive voice response
    • nursing
    • speech perception
    • systematic review
    • transcription

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