Evaluating the efficiency and safety of speech recognition within a commercial electronic health record system: a replication study

Tobias Hodgson*, Farah Magrabi, Enrico Coiera

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


Objective: To conduct a replication study to validate previously identified significant risks and inefficiencies associated with the use of speech recognition (SR) for documentation within an electronic health record (EHR) system. Methods: Thirty-five emergency department clinicians undertook randomly allocated clinical documentation tasks using keyboard and mouse (KBM) or SR using a commercial EHR system. The experiment design, setting, and tasks (E2) replicated an earlier study (E1), while technical integration issues that may have led to poorer SR performance were addressed. Results: Complex tasks were significantly slower to complete using SR (16.94%) than KBM (KBM: 191.9 s, SR: 224.4 s; p = 0.009; CI, 11.9-48.3), replicating task completion times observed in the earlier experiment. Errors (non-typographical) were significantly higher with SR compared with KBM for both simple (KBM: 3, SR: 84; p < 0.001; CI, 1.5- 2.5) and complex tasks (KBM: 23, SR: 53; p = 0.001; CI, 0.5-1.0), again replicating earlier results (E1: 170, E2: 163; p = 0.660; CI, 0.0-0.0). Typographical errors were reduced significantly in the new study (E1: 465, E2: 150; p < 0.001; CI, 2.0-3.0). Discussion: The results of this study replicate those reported earlier. The use of SR for clinical documentation within an EHR system appears to be consistently associated with decreased time efficiencies and increased errors. Modifications implemented to optimize SR integration in the EHR seem to have resulted in minor improvements that did not fundamentally change overall results. Conclusion: This replication study adds further evidence for the poor performance of SR-assisted clinical documentation within an EHR. Replication studies remain rare in informatics literature, especially where study results are unexpected or have significant implication; such studies are clearly needed to avoid overdependence on the results of a single study.

Original languageEnglish
Pages (from-to)326-335
Number of pages10
JournalApplied Clinical Informatics
Issue number2
Publication statusPublished - 1 Apr 2018


  • Electronic health record
  • Integration
  • Medical errors
  • Patient safety
  • Speech recognition


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