Health and Medicine
100 Medical Translation: To Technology or Not to Technology
Pros and cons of using technology for medical interpretation
Haley Huynh
INTRODUCTION
Medical translation is a huge part of 21st century healthcare. Though the first evidence of medical translation dates all the way back to Ancient Mesopotamia, our interpretation situation remains in a state of cultural lag, unable to keep up with increasingly diverse communities in the United States (Montalt et al, 2018). To make matters worse, cultural competency is a recent field of study that current physicians and medical staff are not trained in, leaving patients who face language barriers to be hidden voices without anyone to speak for them. This poses an issue for patients in life-or-death situations, but also affects families who simply want to understand what life-saving efforts are being done on their loved ones. To effectively deliver patient care, there must be trust between patients and physicians, but language barriers continue to make interactions impersonal and distant, breaching the trust that could be formed. This then perpetuates an ever-widening gap in quality of care that diverse patients receive. Utilizing technology to reduce language barriers may be a great idea, but technology has come out faster than we can implement ethical guidelines and perfect translation services, making caveats that have forced medical systems to remain cautious about its use. In this chapter, I will briefly review the pros and cons of using modern technology for medical interpretation in healthcare settings.
Connection to STS
Access to healthcare is a large societal concern in the United States. Intertwined into ethics and politics, how to improve access has been a large and long debate. Science and Technology could be a solution to this issue, such as by contributing to the development of interventions like AI that can translate medical visits. However, like anything else, we should consider potential harms that these interventions could have on society.
PROS FOR THE USAGE OF TECHNOLOGY IN MEDICAL INTERPRETATION
1. Technology Could Help Improve Accessibility
To give the benefit of the doubt, let’s say you’ve heard of an in-house medical translator in a hospital setting. But have you seen one in a rural clinic? Probably not. The fact is, community practices often do not have interpreters on hand, which leaves technology as an option to fill the gap (Randhawa et al, 2013). It is much easier for clinics and hospitals to consistently have iPads for their patients, rather than people. One reason that accessibility may be improved by technology is its cost effectiveness, which will be discussed in the next section. Additionally, technology can be used to access a much wider variety of languages than what can be offered in-house by connecting patients to interpreters who live farther away or by using databases that offer many languages.
2. Technology is More Cost Effective for Hospitals and Clinics
It is well known that translation apps, such as Google Translate (Google Translate), are free of cost for both patients and hospitals (Panayiotou et al, 2019). In clinics that may not receive as much funding as hospitals, technology may serve to quickly translate when dealing with limited resources. Technology has also been used in hospitals to connect patients to certified medical interpreters that work from home, which reduces how much hospitals have to pay for translation services. One study shows that a health care system saved 1.5 million dollars by switching to remote interpreters (Fetterolf, 2017). However, we will discuss in the Cons section how these initiatives may have pitfalls.
3. Technology Provides Standardization
Humans unconsciously introduce bias into all work that they do. It’s important to provide standardized care regardless of an individual or situation, and technology can be a way to mitigate these effects. No matter how many times you type in the same word to Google Translate, it will always spit out the same answers. Humans don’t operate like that. Interpreters may translate sentences in many different ways, even introducing errors in times of high stress that are often encountered in healthcare settings that can affect quality of care (Zhao et al, 2023).
CONS FOR THE USAGE OF TECHNOLOGY IN MEDICAL INTERPRETATION
1. Technology Has Not Accounted for Cultural Sensitivity
Research has not found a way to standardize measurement of cultural sensitivity in healthcare settings, highlighting how patients continue to be missing voices in the field. Even if technology can accurately translate complex medical tests and diagnoses, presenting the information while considering how it may affect patients culturally has not been accurately studied (Panayiotou et al, 2019). Therefore, using technology in the hospital as of now poses the risk of interpreting out of cultural context, possibly making patients less likely to adhere to physician recommendations. However, this isn’t just an issue with the technology itself, but an issue in the medical education curriculum in general.
2. Privacy Concerns with The Use of Technology
Artificial intelligence has been proposed for use in the healthcare system, in everything from reading tests and scans to medical interpretation. However, AI, like technology in general, brings into question ethics and protection of privacy. The major concerns lie in privacy breaches and trusting private entities to handle sensitive information (Murdoch, 2021). Perhaps legal action needs to take place before relying on technology fully for medical purposes. Additionally, patients might not feel comfortable disclosing all their health information to technology when they don’t know who is listening on the other end, which is not any better than not having a translator at all.
3. Technology Continues To Be Inaccurate
Spanish is spoken by 20 countries in the world. Though “popote” means straw in Venezuela, I’ve been told it colloquially means “big poop” in Colombia. Don’t go asking for a “popote” at a restaurant there. The fact is, Spanish, like many other languages is diverse. This means that words can still be lost in translation, an issue that would arise if we tried to standardize medical interpretation using technology. Furthermore, apps like Google Translate can just be flat out wrong. In one study evaluating Google Translate in a medical setting, only 57.7% of translations were correct (Patil and Davies, 2014).
CONSIDERING Healthcare professional OPINIONS
A New York Times article (When Coronavirus Care Gets Lost in Translation – The New York Times (nytimes.com) was released amidst the pandemic, highlighting doctor and medical interpreter opinions in a time when medical interpreters were only permitted to work remotely, a mirror of what medical translation might look like using technology (Goldberg, 2020). Connecting patients to remote interpreters lengthens the time it takes to administer care, frustrating already burnt-out doctors and reducing the quality of care received by patients, according to the article. The article also highlights the quality of work that can be done using remote interpreters. An interpreter in San Francisco mentions how physical contact and face-to-face communication, though not officially part of the job description, can make the difference when it comes to effective interpretation. A medical student also describes worries about discharge, making sure patients correctly understand what they need to do when they leave to protect others around them, especially in times of a pandemic. In-house interpreters can make more meaningful connections, following patients through to discharge, while remote interpreters do not remain with patients for longer than they’re “needed” .
HYBRID MODELS
As we navigate through this relatively new world of technology in medicine, hybrid models may be a compromise to improve accessibility, while maintaining culturally sensitive, accurate translations. Multiple studies have shown how technology and in-house interpreters can work together to fill in the gaps that one cannot accomplish on its own (Mehandru et al, 2022, Susam-Saraeva and Spišiaková, 2021). Perhaps instead of arguing for one or the other, we should compromise and include both. However more research and implementation of hybrid models needs to be done in order to determine this model’s effectiveness.
Conclusion
There is still much debate about whether costs outweigh the benefits of using technology for medical interpretation, such as if being culturally competent is more important than being financially practical. In this way, hybrid models seem to be a potential compromise, though more studies need to be done.
References
Fetterolf, T. D. F., David. (2017, December 1). Carolinas Healthcare System Saved $1.5M Annually by Using Remote Interpreter Technology. HFMA. https://www.hfma.org/finance-and-business-strategy/patient-experience/57149/
Goldberg, E. (2020, April 17). When Coronavirus Care Gets Lost in Translation. The New York Times. https://www.nytimes.com/2020/04/17/health/covid-coronavirus-medical-translators.html
Mehandru, N., Robertson, S., & Salehi, N. (2022). Reliable and Safe Use of Machine Translation in Medical Settings. 2022 ACM Conference on Fairness, Accountability, and Transparency. https://doi.org/10.1145/3531146.3533244
Montalt, Vicent; Karen Zethsen & Wioleta Karwacka. (2018) “Medical translation in the 21st century – challenges and trends.” In: Montalt, Vicent; Karen Zethsen & Wioleta Karwacka (eds.) 2018. Retos actuales y tendencias emergentes en traducción médica / Current challenges and emerging trends in medical translation. MonTI 10, pp. 27-42.
Murdoch, B. (2021). Privacy and artificial intelligence: challenges for protecting health information in a new era. BMC Medical Ethics, 22(1). https://doi.org/10.1186/s12910-021-00687-3
Panayiotou, A., Gardner, A., Williams, S., Zucchi, E., Mascitti-Meuter, M., Goh, A. M., You, E., Chong, T. W., Logiudice, D., Lin, X., Haralambous, B., & Batchelor, F. (2019). Language Translation Apps in Health Care Settings: Expert Opinion. JMIR mHealth and uHealth, 7(4), e11316. https://doi.org/10.2196/11316
Patil, S., & Davies, P. (2014). Use of Google Translate in medical communication: evaluation of accuracy. BMJ, 349(dec15 2), g7392–g7392. https://doi.org/10.1136/bmj.g7392
Randhawa, G., Ferreyra, M., Ahmed, R., Ezzat, O., & Pottie, K. (2013). Using machine translation in clinical practice. Canadian family physician Medecin de famille canadien, 59(4), 382–383.
Susam-Saraeva, Ş., & Spišiaková, E. (2021). The Routledge Handbook of Translation and Health. In Google Books. Routledge. https://books.google.com/books?hl=en&lr=&id=MLEjEAAAQBAJ&oi=fnd&pg=PA108&dq=machine+vs+human+translation+in+hospitals&ots=oA9wvC9
Zhao, N., Cai, Z. G., & Dong, Y. (2023). Speech errors in consecutive interpreting: Effects of language proficiency, working memory, and anxiety. PloS one, 18(10), e0292718. https://doi.org/10.1371/journal.pone.0292718
Images
Ceren’s Designs. “Red and Navy Colorful Translation Day Animated Social Media Your Story.” Canva. Accessed 2/27/2024. Templates (canva.com)
“Language Interpretation”. Created with Mircosoft Copilot, https://copilot.microsoft.com/.
AI ACknowledgements
I acknowledge the use of ChatGTP (ChatGPT (openai.com)) to create an outline for this chapter. The prompts used include “outline a chapter about the debate of whether technology should be used in medical interpretation (for example yes, because of a shortage of interpreters or no because it is impersonal) as it relates to modernization theory,” “outline a short chapter about the debate of whether technology should be used in medical interpretation (for example yes, because of a shortage of interpreters or no because it is impersonal) as it relates to modernization theory,” and “give me an outline for a chapter on the pros and cons of using technology for medical translation in hospitals.”
I also acknowledge the use of Microsoft Copilor (Copilot (microsoft.com)) to generate an image for this chapter. The prompt used included “language interpretation.”