Speech recognition for clinical documentation from 1990 to 2018: a systematic review
Open Access
- 11 February 2019
- journal article
- review article
- Published by Oxford University Press (OUP) in Journal of the American Medical Informatics Association
- Vol. 26 (4) , 324-338
Abstract
Objective: The study sought to review recent literature regarding use of speech recognition (SR) technology for clinical documentation and to understand the impact of SR on document accuracy, provider efficiency, institutional cost, and more.Materials and Methods: We searched 10 scientific and medical literature databases to find articles about clinician use of SR for documentation published between January 1, 1990, and October 15, 2018. We annotated included articles with their research topic(s), medical domain(s), and SR system(s) evaluated and analyzed the results.Results: One hundred twenty-two articles were included. Forty-eight (39.3%) involved the radiology department exclusively and 10 (8.2%) involved emergency medicine; 10 (8.2%) mentioned multiple departments. Forty-eight (39.3%) articles studied productivity; 20 (16.4%) studied the effect of SR on documentation time, with mixed findings. Decreased turnaround time was reported in all 19 (15.6%) studies in which it was evaluated. Twenty-nine (23.8%) studies conducted error analyses, though various evaluation metrics were used. Reported percentage of documents with errors ranged from 4.8% to 71%; reported word error rates ranged from 7.4% to 38.7%. Seven (5.7%) studies assessed documentation-associated costs; 5 reported decreases and 2 reported increases. Many studies (44.3%) used products by Nuance Communications. Other vendors included IBM (9.0%) and Philips (6.6%); 7 (5.7%) used self-developed systems.Conclusion: Despite widespread use of SR for clinical documentation, research on this topic remains largely heterogeneous, often using different evaluation metrics with mixed findings. Further, that SR-assisted documentation has become increasingly common in clinical settings beyond radiology warrants further investigation of its use and effectiveness in these settings.Keywords
Funding Information
- Healthcare Research and Quality (R01HS024264)
This publication has 122 references indexed in Scilit:
- Non-Clinical Errors Using Voice Recognition Dictation Software for Radiology Reports: A Retrospective AuditJournal of Digital Imaging, 2010
- Voice recognition versus transcriptionist: Error rates and productivity in MRI reportingJournal of Medical Imaging and Radiation Oncology, 2010
- Speech recognition software and electronic psychiatric progress notes: physicians' ratings and preferencesBMC Medical Informatics and Decision Making, 2010
- Immediate and sustained benefits of a “total” implementation of speech recognition reportingBritish Journal of Radiology, 2010
- An intelligent listening framework for capturing encounter notes from a doctor-patient dialogBMC Medical Informatics and Decision Making, 2009
- Improving language models for radiology speech recognitionJournal of Biomedical Informatics, 2009
- Improvement of Report Workflow and Productivity Using Speech Recognition—A Follow-up StudyJournal of Digital Imaging, 2008
- Voice Recognition Dictation: Radiologist as TranscriptionistJournal of Digital Imaging, 2007
- Improving the Utility of Speech Recognition Through Error DetectionJournal of Digital Imaging, 2007
- The influence of time on error-detectionBehaviour & Information Technology, 1998