A systematic review of speech recognition technology in health care

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• 作者：Maree Johnson (6) (7)
  Samuel Lapkin (7) (8)
  Vanessa Long (9)
  Paula Sanchez (7) (9)
  Hanna Suominen (10)
  Jim Basilakis (9)
  Linda Dawson (11)
  
  6. Faculty of Health Sciences ; Australian Catholic University ; 40 Edward Street ; 2060 ; North Sydney ; NSW ; Australia
  7. Centre for Applied Nursing Research (a joint facility of the South Western Sydney Local Health District and the University of Western Sydney) ; Affiliated with the Ingham Institute of Applied Medical Research ; Sydney ; Australia
  8. Central Queensland University ; Bundaberg ; Australia
  9. University of Western Sydney ; Sydney ; Australia
  10. Department of Information Technology ; NICTA ; The Australian National University ; College of Engineering and Computer Science ; University of Canberra ; Faculty of Health ; and University of Turku ; Canberra ; ACT ; Australia
  11. University of Wollongong ; Wollongong ; Australia
  
• 关键词：Nursing ; Systematic review ; Speech recognition ; Interactive voice response systems ; Human transcriptions ; Health professionals
• 刊名：BMC Medical Informatics and Decision Making
• 出版年：2014
• 出版时间：December 2014
• 年：2014
• 卷：14
• 期：1
• 全文大小：616 KB
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  42. The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1472-6947/14/94/prepub
  
• 刊物主题：Health Informatics; Information Systems and Communication Service; Management of Computing and Information Systems;
• 出版者：BioMed Central
• ISSN：1472-6947

文摘

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.