Developing Transformative Technologies to Enhance Equitable Acute Stroke Care in Patients with Limited English Proficiency
Bavica Gummadi1, Joanna Marmo2, Laura Ades1, Aaron Lord3
1NYU Langone, 2NYU Langone Health, 3NYU Langone-Brooklyn
Objective:
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Background:

Advancements in acute stroke care and time-based metrics have reduced overall stroke mortality, but patients with limited English proficiency (LEP) remain at higher risk for worse neurological outcomes. Data from urban academic centers show clinically significant delays in door-to-needle time for LEP patients, highlighting the need for innovative strategies to ensure equitable care.

Design/Methods:

Adult neurology residents at a large academic hospital were surveyed using numeric scales to assess their comfort in managing stroke codes for English-proficient versus LEP patients. A mobile app, TransCODE, featuring speech-to-text, text-to-speech, and offline NIHSS commands in multiple languages (Spanish, Arabic, Toishanese, Fuzhonese, Cantonese, Mandarin, Russian), will be developed and evaluated by residents. The survey will be repeated post-introduction to assess the app's impact on resident confidence and efficiency. Based on feedback, the app will be tested in clinical settings.

Results:

All 15 neurology residents completed the survey. While all felt comfortable managing English-speaking stroke codes, only 26.7% felt comfortable with LEP patients, and 40% expressed discomfort. Confidence in NIHSS performance dropped from 100% with English-speaking patients to 20% with LEP patients. Challenges with interpreter services were reported, with only 20% finding in-person interpreters accessible during a stroke code and 53.3% finding virtual interpreters accessible. However, only 13.3% trusted virtual interpreters’ accuracy, compared to 93.4% for in-person interpreters. Additionally, 80% noted interpretation issues slowed stroke care, and 73.3% felt intervention times (time to thrombolysis or thrombectomy) were delayed for LEP patients. Importantly, 100% believed a mobile app could improve their comfort and efficiency in LEP stroke codes.

Conclusions:

These findings highlight a clear opportunity to improve stroke care for LEP patients, where interpretation barriers hinder timely, effective treatment. While virtual interpreters offer accessibility, concerns about their accuracy remain. By ensuring confidence and efficiency in LEP stroke codes, TransCODE can enhance equity in stroke diagnosis and treatment.

10.1212/WNL.0000000000212143
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