Accepted for/Published in: JMIR Research Protocols
Date Submitted: Jun 4, 2020
Date Accepted: Sep 4, 2020
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Medical translation assistant for non-english speaking caregivers of CSHCN: A scalable and interoperable mobile app
ABSTRACT
Background:
Communication and comprehension of medical information is a known barrier in health communication and equity, especially for non-English speaking caregivers of children with special healthcare needs.
Objective:
To develop an interoperable and scalable medical translation app for non-English speaking caregivers to facilitate the conversation between provider and caregiver/patient.
Methods:
We employed user centered and participatory design methods in understanding the problems and developing a solution by engaging the stakeholder group (including caregivers, physicians, researchers, clinical informaticists, nurses, developers, nutritionists, pharmacists, and interpreters).
Results:
Considering the lack of interpreter service accessibility and advancement in translation technology, our team will develop and test an integrated, multimodal (voice-interactive and text-based) patient portal communication and translation app to enable Non-English speaking caregivers to communicate with providers using their preferred languages. For this initial prototype, we will focus on Spanish language and Spanish-speaking families to test technical feasibility and evaluate usability.
Conclusions:
Our proposal brings a unique perspective in medical translation and communication between caregiver and provider by (1) enabling voice entry and transcription in healthcare communications, (2) integration with patient portal to facilitate caregiver and provider communications, (3) adoption of translation verification model to improve accuracy of AI facilitated translations. Expected outcomes include improved health communications, literacy, and health equity. In addition data points will be collected to improve auto translation (AI) services as well as voice transcription in medical communications. We believe our proposed solution is affordable and scalable for the health systems.
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.