A Pragmatic Assessment of Google Translate for Emergency Department Instructions

Background Because many hospitals have no mechanism for written translation, ED providers resort to the use of automated translation software, such as Google Translate (GT) for patient instructions. A recent study of discharge instructions in Spanish and Chinese suggested that accuracy rates of Google Translate (GT) were high. Study Objective To perform a pragmatic assessment of GT for the written translation of commonly used ED discharge instructions in seven commonly spoken languages. Methods A prospective assessment of the accuracy of GT for 20 commonly used ED discharge instruction phrases, as evaluated by a convenience sample of native speakers of seven commonly spoken languages (Spanish, Chinese, Vietnamese, Tagalog, Korean, Armenian, and Farsi). Translations were evaluated using a previously validated matrix for scoring machine translation, containing 5-point Likert scales for fluency, adequacy, meaning, and severity, in addition to a dichotomous assessment of retention of the overall meaning. Results Twenty volunteers evaluated 400 google translated discharge statements. Volunteers were 50% female and spoke Spanish (5), Armenian (2), Chinese (3), Tagalog (4), Korean (2), and Farsi (2). The overall meaning was retained for 82.5% (330/400) of the translations. Spanish had the highest accuracy rate (94%), followed by Tagalog (90%), Korean (82.5%), Chinese (81.7%), Farsi (67.5%), and Armenian (55%). Mean Likert scores (on a 5-point scale) were high for fluency (4.2), adequacy (4.4), meaning (4.3), and severity (4.3) but also varied. Conclusion GT for discharge instructions in the ED is inconsistent between languages and should not be relied on for patient instructions.

Automated summary

The study evaluated the use of Google Translate for written translation of emergency department discharge instructions in seven commonly spoken languages. While overall meaning was retained in a majority of translations, accuracy varied between languages, suggesting inconsistent reliability for patient instructions.