JMIR Publications

ABSTRACT

Background:

In the context of the current refugee crisis, emergency services have often to deal with patients who have no language in common with the staff. As interpreters are not always available, especially in emergency settings, the medical personnel relies on alternative solutions such as machine translation, which raises reliability and data confidentiality issues, or medical fixed-phrase translators, which are sometimes lacking in usability. A collaboration between Geneva University Hospitals and Geneva University led to the development of BabelDr, a new type of speech-enabled fixed-phrase translator. Similar to other fixed-phrase translators (Medibabble or UniversalDoctor), it relies on a predefined list of pre-translated sentences, but instead of searching for sentences in this list, doctors can freely ask questions.

Objective:

This study aimed to assess if a translation tool, such as BabelDr, allows doctors to perform a diagnostic interview under emergency conditions and reach a correct diagnosis. We also wanted to observe how doctors interact with the system and how they use text and speech and to investigate if speech is a useful modality in this context.

Methods:

We conducted a cross-over study in December 2017 at Geneva University Hospitals among 12 French-speaking doctors (6 doctors working at the outpatient emergency service and 6 general practitioners who also regularly work in this service). They were asked to use the BabelDr tool to diagnose two standardized Arabic-speaking patients, male and female. The patients received an a priori list of symptoms for the condition they presented and were instructed to give a negative or non-committal answer for all other symptoms during the diagnostic interview. The male patient was standardized for nephritic colic and the female for cystitis. Doctors used BabelDr as the only means of communication with the patient and they were asked to give their diagnosis at the end of the dialogue. They also completed a satisfaction questionnaire.

Results:

All doctors were able to reach a correct diagnosis based on the information collected using BabelDr. They all agreed that the system helped them to reach a conclusion, even if one-half felt constrained by the tool and some considered that they could not ask enough questions to reach a diagnosis. Overall, participants used more speech than text, thus confirming that speech is an important functionality in this type of tool. There was a strong correlation (P < .001) between the percentage of successful speech interactions (spoken sentences sent for translation) and the number of translated text items, thus showing that they used more text when they had no success with speech.

Conclusions:

In emergency settings when no interpreter is available, speech-enabled fixed-phrase translators can be a good alternative to reliably collect information from the patient. Clinical Trial: n/a