Automated translation accurately translates recorded pediatric neurosurgery clinic conversations between Spanish and English.

Access to Care Global neurosurgery Pediatric Neurosurgery Clinic Quality Improvement Translation

Journal

Neurosurgical review
ISSN: 1437-2320
Titre abrégé: Neurosurg Rev
Pays: Germany
ID NLM: 7908181

Informations de publication

Date de publication:
10 May 2024
Historique:
received: 29 10 2023
accepted: 27 04 2024
revised: 26 03 2024
medline: 10 5 2024
pubmed: 10 5 2024
entrez: 9 5 2024
Statut: epublish

Résumé

The purpose of this study is to analyze an automated voice to text translation device by reporting the translation accuracy for recorded pediatric neurosurgery clinic conversations, classifying errors in translation according to their impact on overall understanding, and comparing the incidence of these errors in English to Spanish vs. Spanish to English conversations. English and Spanish speaking patients at a single academic health system's outpatient pediatric neurosurgery clinic had their conversations recorded. These recordings were played back to a Google Pixel handheld smartphone with Live Translate voice to text translation software. A certified medical interpreter evaluated recordings for incidence of minor errors, errors impacting understanding, and catastrophic errors affecting patient-provider relationship or care. Two proportion t-testing was used to compare these outcomes. 50 patient visits were recorded: 40 English recordings translated to Spanish and 10 Spanish recordings translated to English. The mean transcript length was 4244 ± 992 words. The overall accuracy was 98.2% ± 0.5%. On average, 46 words were missed in translation (1.09% error rate), 31 understanding-altering translation errors (0.73% error rate), and 0 catastrophic errors were made. There was no significant difference in English to Spanish or vice versa. Voice to text translation devices using automatic speech recognition accurately translate recorded clinic conversations between Spanish and English with high accuracy and low incidence of errors impacting medical care or understanding. Further study should investigate additional languages, assess patient preferences and potential concerns with respect to device use, and compare these devices directly to medical interpreters in live clinic settings.

Identifiants

pubmed: 38724863
doi: 10.1007/s10143-024-02441-w
pii: 10.1007/s10143-024-02441-w
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

210

Informations de copyright

© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

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Auteurs

Benjamin Succop (B)

School of Medicine, University of North Carolina - Chapel Hill, Chapel Hill, NC, USA. benjamin_succop@med.unc.edu.

Meghan Currin (M)

School of Medicine, University of North Carolina - Chapel Hill, Chapel Hill, NC, USA.

Gabriella Hesse (G)

School of Medicine, University of North Carolina - Chapel Hill, Chapel Hill, NC, USA.

Hannah Black (H)

School of Medicine, University of North Carolina - Chapel Hill, Chapel Hill, NC, USA.

Bethany Andrews (B)

Department of Neurosurgery, University of North Carolina - Chapel Hill, Chapel Hill, NC, USA.

Scott Wentworth Elton (SW)

Department of Neurosurgery, University of North Carolina - Chapel Hill, Chapel Hill, NC, USA.

Carolyn Quinsey (C)

Department of Neurosurgery, University of North Carolina - Chapel Hill, Chapel Hill, NC, USA.

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