Eleanor Taylor-Stilgoe
About
My research project
A study of healthcare staff awareness of potential risk posed by machine translationWhen faced with language barriers, UK healthcare staff have found themselves turning to machine translation (MT) – predominantly Google Translate – to fulfil their duty of care to patients. Despite the risks potentially posed by the use of MT in such complex and sensitive situations, little research currently exists as to healthcare staff awareness of these risks in real-life settings. This gap is particularly notable concerning the use of MT with patient medical record information compared with interpersonal situations and patient-oriented documentation. While research has been conducted into the perceptions and practices of the general population concerning MT use in largely lower-stakes contexts, research on the extent to which these transfer to higher-stakes settings remains lacking.
Furthermore, medical abbreviations, an ubiquitous presence in healthcare environments, have previously been shown to pose an increased risk for patient harm even prior to their translation with Google Translate. As such, these were selected as higher-risk phenomena to serve as a use case for the present study. Using appropriately contextualised French and Spanish data examples sourced from authoritative clinical corpora and translated using Google Translate, these higher-risk phenomena were then incorporated into semi-structured interviews with 21 healthcare staff members in diverse roles and specialties to ascertain their awareness of the risks posed by their translation with MT.
The contribution that the present research aims to make is therefore as follows: firstly, to explore the extent to which healthcare staff are aware of the risks potentially posed by the use of MT with patient medical documentation and, secondly, to determine the effectiveness of medical abbreviations as a use case with which to identify such risks. The findings shall be subject to qualitative thematic analysis and conclusions drawn accordingly.
Supervisors
When faced with language barriers, UK healthcare staff have found themselves turning to machine translation (MT) – predominantly Google Translate – to fulfil their duty of care to patients. Despite the risks potentially posed by the use of MT in such complex and sensitive situations, little research currently exists as to healthcare staff awareness of these risks in real-life settings. This gap is particularly notable concerning the use of MT with patient medical record information compared with interpersonal situations and patient-oriented documentation. While research has been conducted into the perceptions and practices of the general population concerning MT use in largely lower-stakes contexts, research on the extent to which these transfer to higher-stakes settings remains lacking.
Furthermore, medical abbreviations, an ubiquitous presence in healthcare environments, have previously been shown to pose an increased risk for patient harm even prior to their translation with Google Translate. As such, these were selected as higher-risk phenomena to serve as a use case for the present study. Using appropriately contextualised French and Spanish data examples sourced from authoritative clinical corpora and translated using Google Translate, these higher-risk phenomena were then incorporated into semi-structured interviews with 21 healthcare staff members in diverse roles and specialties to ascertain their awareness of the risks posed by their translation with MT.
The contribution that the present research aims to make is therefore as follows: firstly, to explore the extent to which healthcare staff are aware of the risks potentially posed by the use of MT with patient medical documentation and, secondly, to determine the effectiveness of medical abbreviations as a use case with which to identify such risks. The findings shall be subject to qualitative thematic analysis and conclusions drawn accordingly.
My qualifications
Affiliations and memberships
Certificate in Teaching English to Speakers of Other Languages (CELTA)
Course Leader, A1 Beginners' Spanish, Evening Language Classes
ResearchResearch interests
Translation ethics and risk management, healthcare communications, and the use of NLP as integrated into wider social contexts and frameworks.
Research interests
Translation ethics and risk management, healthcare communications, and the use of NLP as integrated into wider social contexts and frameworks.
Publications
When faced with language barriers, UK healthcare staff have found themselves turning to machine translation (MT) – predominantly Google Translate – to fulfil their duty of care to patients. Despite the risks potentially posed by the use of MT in such complex and sensitive situations, little research currently exists as to healthcare staff awareness of these risks in real-life settings. This gap is particularly notable concerning the use of MT with patient medical record information compared with interpersonal situations and patient-oriented documentation. While research has been conducted into the perceptions and practices of the general population concerning MT use in largely lower-stakes contexts, research on the extent to which these transfer to higher-stakes settings remains lacking. The contribution this paper aims to make is therefore twofold: to investigate the impact of MT on patient medical record documentation, and to explore the extent to which healthcare staff are aware of the risks potentially posed by its use. In this paper, we selected contextualised medical abbreviation examples from authoritative French and Spanish clinical corpora to serve as a use case, abbreviations having previously been shown to pose an increased risk for patient harm even prior to their translation with Google Translate. Examples containing higher-risk MT errors were then presented to healthcare staff to ascertain their perceptions and risk awareness as part of semi-structured interviews. Whilst these interviews remain ongoing, this paper presents the findings on risks identified in the use of MT with patient medical documentation, and the responses obtained thus far.