Efficiency and safety of speech recognition for documentation in the electronic health record

Tobias Hodgson*, Farah Magrabi, Enrico Coiera

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

38 Citations (Scopus)
31 Downloads (Pure)


Objective: To compare the efficiency and safety of using speech recognition (SR) assisted clinical documentation within an electronic health record (EHR) system with use of keyboard and mouse (KBM). Methods: Thirty-five emergency department clinicians undertook randomly allocated clinical documentation tasks using KBM or SR on a commercial EHR system. Tasks were simple or complex, and with or without interruption. Outcome measures included task completion times and observed errors. Errors were classed by their potential for patient harm. Error causes were classified as due to IT system/system integration, user interaction, comprehension, or as typographical. User-related errors could be by either omission or commission. Results: Mean task completion times were 18.11% slower overall when using SR compared to KBM (P=.001), 16.95% slower for simple tasks (P=.050), and 18.40% slower for complex tasks (P=.009). Increased errors were observed with use of SR (KBM 32, SR 138) for both simple (KBM 9, SR 75; P<0.001) and complex (KBM 23, SR 63; P<0.001) tasks. Interruptions did not significantly affect task completion times or error rates for either modality. Discussion: For clinical documentation, SR was slower and increased the risk of documentation errors, including errors with the potential to cause clinical harm compared to KBM. Some of the observed increase in errors may be due to suboptimal SR to EHR integration and workflow. Conclusion: Use of SR to drive interactive clinical documentation in the EHR requires careful evaluation. Current generation implementations may require significant development before they are safe and effective. Improving system integration and workflow, as well as SR accuracy and user-focused error correction strategies, may improve SR performance.

Original languageEnglish
Pages (from-to)1127-1133
Number of pages7
JournalJournal of the American Medical Informatics Association
Issue number6
Publication statusPublished - 1 Nov 2017

Bibliographical note

Copyright the Author(s) 2017. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.


  • patient safety
  • electronic health record
  • speech recognition
  • documentation
  • medical errors


Dive into the research topics of 'Efficiency and safety of speech recognition for documentation in the electronic health record'. Together they form a unique fingerprint.

Cite this