A clinician survey of using speech recognition for clinical documentation in the electronic health record

Foster R Goss; Suzanne V Blackley; Carlos A Ortega; Leigh T Kowalski; Adam B Landman; Chen-Tan Lin; Marie Meteer; Samantha Bakes; Stephen C Gradwohl; David W Bates; Li Zhou

doi:10.1016/j.ijmedinf.2019.07.017

A clinician survey of using speech recognition for clinical documentation in the electronic health record

Int J Med Inform. 2019 Oct:130:103938. doi: 10.1016/j.ijmedinf.2019.07.017. Epub 2019 Jul 31.

Authors

Affiliations

¹ Department of Emergency Medicine, University of Colorado School of Medicine, Aurora, CO, USA. Electronic address: foster.goss@ucdenver.edu.
² Clinical & Quality Analysis, Partners HealthCare System, Boston, MA, USA.
³ Division of General Medicine and Primary Care, Brigham and Women's Hospital, Boston, MA, USA.
⁴ Department of Emergency Medicine, Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.
⁵ Department of Internal Medicine, University of Colorado School of Medicine, Aurora, CO, USA.
⁶ Brandeis University, Waltham, MA, USA.
⁷ Department of Emergency Medicine, University of Colorado School of Medicine, Aurora, CO, USA.
⁸ Children's Hospital Colorado, University of Colorado School of Medicine, Aurora, CO, USA.
⁹ Clinical & Quality Analysis, Partners HealthCare System, Boston, MA, USA; Division of General Medicine and Primary Care, Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.
¹⁰ Division of General Medicine and Primary Care, Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.

PMID: 31442847
DOI: 10.1016/j.ijmedinf.2019.07.017

Abstract

Objective: To assess the role of speech recognition (SR) technology in clinicians' documentation workflows by examining use of, experience with and opinions about this technology.

Materials and methods: We distributed a survey in 2016-2017 to 1731 clinician SR users at two large medical centers in Boston, Massachusetts and Aurora, Colorado. The survey asked about demographic and clinical characteristics, SR use and preferences, perceived accuracy, efficiency, and usability of SR, and overall satisfaction. Associations between outcomes (e.g., satisfaction) and factors (e.g., error prevalence) were measured using ordinal logistic regression.

Results: Most respondents (65.3%) had used their SR system for under one year. 75.5% of respondents estimated seeing 10 or fewer errors per dictation, but 19.6% estimated half or more of errors were clinically significant. Although 29.4% of respondents did not include SR among their preferred documentation methods, 78.8% were satisfied with SR, and 77.2% agreed that SR improves efficiency. Satisfaction was associated positively with efficiency and negatively with error prevalence and editing time. Respondents were interested in further training about using SR effectively but expressed concerns regarding software reliability, editing and workflow.

Discussion: Compared to other documentation methods (e.g., scribes, templates, typing, traditional dictation), SR has emerged as an effective solution, overcoming limitations inherent in other options and potentially improving efficiency while preserving documentation quality.

Conclusion: While concerns about SR usability and accuracy persist, clinicians expressed positive opinions about its impact on workflow and efficiency. Faster and better approaches are needed for clinical documentation, and SR is likely to play an important role going forward.

Keywords: Artificial intelligence; Clinical documentation; Efficiency; Natural language processing; Quality of care; Safety; Speech recognition.

Publication types

Research Support, U.S. Gov't, P.H.S.

MeSH terms

Adult
Aged
Boston
Documentation / methods*
Electronic Health Records / standards*
Electronic Health Records / statistics & numerical data*
Female
Health Personnel / statistics & numerical data*
Humans
Male
Medical Errors / statistics & numerical data*
Middle Aged
Perception
Speech / physiology*
Speech Recognition Software / statistics & numerical data*
Surveys and Questionnaires
Workflow

Grants and funding

R01 HS024264/HS/AHRQ HHS/United States