PP109 Use Of Speech Recognition In Medical Reports: A Systematic Review

Abstract

Introduction:Speech recognition is increasingly used in medical reporting. The aim of this article is to identify in the literature the advantages and weaknesses of this technology, as well as barriers and facilitators to its implementation.Methods:A systematic review of systematic reviews has been conducted in PubMed, Scopus, Cochrane Library and Center for Reviews and Dissemination up to August 2017. The grey literature has also been consulted. The quality of systematic reviews has been assessed with the AMSTAR checklist. Inclusion criteria were to use speech recognition for medical reporting (front or back-end). A Survey has also been conducted in Quebec, Canada, to identify the dissemination of this technology in this province, as well as the factors of success or failure in its implementation.Results:Five systematic reviews were identified. These reviews indicated a high level of heterogeneity across studies. The quality of the studies reported was generally poor. Speech recognition is not as accurate as human transcription but can dramatically reduce the turnaround times for reporting. In front-end use, medical doctors need to spend more time for dictation and correction than with human transcription. With speech recognition, major errors can be up to three times more frequent. In back-end use, a potential increase in the productivity of transcriptionist is noted.Conclusions:Speech recognition offers some advantages for medical reporting, the main one being a reduction in turnaround times. However, these advantages are challenged by an increased burden for medical doctor and risks of additional errors in medical reports. It is also hard to identify for which medical specialties and which clinical activities the use of speech recognition will be the most beneficial.