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Lost in Translation: How automated machine translation can address the shortage of medical interprets
Lower Lobby - West
Lost in Translation: How automated machine translation can address the shortage of medical interprets
UC Davis
Background: Healthcare providers typically use live interpreters to communicate with patients who either do not speak English or who have limited English proficiency. With the Affordable Care Act (ACA)... Read more

Description

Background: Healthcare providers typically use live interpreters to communicate with patients who either do not speak English or who have limited English proficiency. With the Affordable Care Act (ACA) encouraging uninsured patients to obtain health insurance, the anticipated demand for language interpretation will increase, as the proportion of LEP patients for Medi-Cal and Healthy Families will increase to 41% by 2019. However, a shortage of interpreters exists because medical interpretation incurs a typical $30 to $50 per hour overhead cost, there is a 35% decrease in earning potential for medical interpreters versus government or scientific and technical interpreters, and using live interpreters increases doctor-patient encounter times by 57% versus phone interpreters. The quality of live interpretation can also vary as there are legally and professionally no mandated requirements for certification or quality control.

A possible solution is the use of automated digital interpretation of clinical encounters, but there are no descriptions of such systems in the medical literature, though some public health agencies  and clinicians may already be employing such tools. 

Methods: We constructed a prototype of translation software that runs on Google Glass, using Nuance NDEV speech recognition technology to convert speech to text, and Google Translate for converting text in other languages into English. We additionally tested Google Translate’s ability to convert Spanish-language speech to another language on Android tablets using sample patient-doctor interview scripts.

Results:  Our initial acceptability trials demonstrate that these tools are feasible for use in clinical settings. The next stage is to test their accuracy. 

Conclusion: Using speech recognition and machine translation is feasible. Accuracy trials to determine errors of addition, omission, substitution, and false fluency are essential, as is usability comparison with live interpreters.

Steven Chan (@StevenChanMDwww.stevenchanMD.com) is regarded as an accomplished top thinker in the intersection of healthcare, behavior, medicine, business, and technology. Steve not only reports on the latest technology trends as contributor to iMedicalApps.com — a leading news site written by physicians for physicians on mobile health — but also develops cutting-edge research in the areas of asynchronous telepsychiatry, smartphones and mobile wearable devices for mental health, and applications for cultural psychiatry and underserved minority health.
 
Steve's ideas, thoughts, and research have been featured in JAMA, Healthcare, and JMIR (Journal of Medical Internet Research). He has designed and developed interactive voice user interfaces at Microsoft. With the support of the U.S. Department of Health & Human Services, Steve serves as current American Psychiatric Association (APA) & SAMHSA MFP Fellow to the APA Council of Communications and Workgroup on Mental Health & Psychiatric Apps.
 
Dr. Chan draws from his extensive training at the University of California’s leading institutes — with computer science & engineering at UC Berkeley and informatics coursework at Stanford University; medical training at UCLA, UC San Francisco, UC Davis, UC Irvine, and Icahn School of Medicine at Mt. Sinai in New York City; and business & healthcare administration at UC Irvine. As a current resident physician in psychiatry & behavioral sciences at UC Davis School of Medicine, Dr. Chan treats a variety of patients, including veterans, felons, and the homeless.
 
Steve has an established reputation for business strategy and creativity. He has presented inspiring, well-researched talks at the national Health 2.0 conference in Silicon Valley, Institute for Psychiatric Services, the American Telemedicine Association, and for the California Healthcare Foundation Design-a-thon. Steve has also led winning collaborative teams at numerous health tech competitions, including the UC Berkeley-Genentech Hacking Health competition and the Health 2.0 San Francisco code-a-thon twice.
 
Giving back is important to Steve. He currently volunteers as preceptor at a UC Davis free clinic for the medically underserved. He mentors over 200 students for the Edge Interns program, designed to empower undergraduates and graduate students from around the United States. He has also trained future physicians in topics ranging from organic chemistry to computer science to topics in psychopharmacology and cultural and linguistic diversity in medicine. He has made healthcare technology accessible to his local community as co-founder of Health 2.0 Sacramento. And, he volunteers as third-in-command at the Kraken Con semi-annual pop culture convention for families and fans.
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