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hospital administrators

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Healthcare staff face risks when using Google Translate for medical abbreviations

"I just assumed that it would translate": examining MT risk awareness among healthcare staff with abbreviations as a use case

Abstract: In the UK, public healthcare staff report turning to machine translation (MT) - predominantly Google Translate (GT) - to communicate with patients across language barriers. Though intended to support their duty of care, potentially uninformed reliance on MT in such contexts could have serious consequences for patient safety. Research nonetheless remains limited on staff awareness of the possible risks posed by higher-stakes MT use in general and with patient medical records in particular, most existing literature instead examining its use in interpersonal situations or with patient-oriented documentation. Moreover, medical abbreviations are well-documented as increasing patient risk even monolingually, with outcomes from their misuse and/or misinterpretation ranging from temporary harm to the death of the patient. Abbreviations were therefore selected as a use case for identifying the potential risks posed by their translation with MT. Contextualised French and Spanish data examples drawn from authoritative clinical corpora and translated via GT were presented during semi-structured interviews to 21 healthcare staff participants in diverse roles and specialties. The results were then subject to qualitative analysis and cross-analysis.

Thu 1 OctArtificial Intelligence
The gist
Healthcare workers in the UK often use Google Translate to talk with patients who speak different languages. The authors studied how aware these workers are of mistakes that machine translation can make, especially when translating medical abbreviations. Medical abbreviations are tricky even in one language and can cause serious harm if misunderstood. The researchers showed examples of translations from French and Spanish to healthcare workers and discussed the risks involved. They found that misunderstanding machine translations of abbreviations may lead to patient safety problems.
Open → 2610.02496v1