How Machine Translation Can Be Used In Clinical Practice

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If you’ve ever traveled to another country and you needed to visit a clinical practice there, you would have immediately noticed that the language barrier is rife. It’s crucial for medical professionals to have the correct information before them to make an accurate diagnosis of the medical condition at hand and address the problem through the most appropriate treatment. Yet, clinical practices that do not take language barriers into account can be problematic for the patients and the healthcare providers. 

But beyond point-of-care, clinical practices extend their scope into areas that include medical documents, web medical help, insurance claims forms, patient records, educational materials, studies and papers, warnings, IVR scripts, etc. This is why machine translation is so crucial in the clinical practice setting. If you’re wondering why this is the case, how it can be applied in practice, what its drawbacks are, as well as where machine translation is headed into the future in the context of medical translation, take a look below.

Why is machine translation needed in clinical practice?

Clinical practice guidelines require that medical interpretation be as accurate as possible. There are several reasons for this as well as reasons why machine translation is necessary for the clinical practice setting. Here are some of them.

• Reduce cost and turnaround times: a document in a clinical practice that has been translated by a machine can quickly and efficiently reduce turnaround times. This is because of statistical machine translation, which uses a language corpus and preexisting glossaries and style guides, to make a more accurate prediction based on a source language that’s been input so that the result in the target language is as precise as possible. Although not perfect, machine translation efforts can help with inputting and processing large quantities of data, which then means that costs for the client are reduced because only editing and final checks by a human translator will need to follow after the machine translation process has been utilized. 
• Expedite content analysis: irrespective of the quantities of data, the preexisting information and language codes that have been input in a machine translation program means that content analysis can be expedited. 
• Address quality: finally, when using machine translation tools, an organization such as a clinical practice can ensure that final checks are implemented and quality issues are addressed for a final output that is the closest to the original in the source language as possible.

Practical applications and drawbacks

Of course, apart from looking at machine translation in clinical practice, it’s also essential to determine the ways in which it can be practically applied as well as see what some of the existing drawbacks may be. Let’s take a closer look

Practical applications

As a starting point, machine translation in clinical practice has the potential to process large volumes of data through a program or several programs that are utilized simultaneously. Often, medical translations require high quantities of work to be translated into several languages at the same time. What would take human translators months to complete can take a machine several days or weeks at the most. This is an effective time-saving practice. 

Secondly, machine translations in a healthcare setting can assist with post-market surveillance. Since requirements for this practice are becoming ever more stringent, medical providers are increasingly required to be able to offer content in multiple languages and in short spaces of time. This applies to cases where they may need to respond to social media inquiries or even patient complaints. With machine translation, areas that may require further investigation are quickly resolved. 

Furthermore, machine translations can help with clinical trials. One example of this is the creation of Patient-Informed Consent Forms. With machine translation for medical documents, an organization can see a quick turnaround time that is between 30% and 50% faster as opposed to the use of non-machine translation tools.

Finally, a machine-translated piece of content can help improve the process of content audits or quality reviews. This means more consistency and uniformity in areas such as product labeling. As a result, it’s crucial for improving patient safety.

Drawbacks

However, despite these practical applications, we also need to consider the drawbacks of machine translation in a clinical practice setting.

Perhaps the first one is that machine translation cannot be performed without the help of qualified and experienced human translators to ensure that quality touches are apparent on every piece of content that’s ready to be utilized.

There are also pitfalls related to misunderstandings that may arise in the event of inaccurate translations. Here, a regular cycle of feedback will be crucial in order to train machine translation programs to improve their productivity and quality of output. Another important factor to be kept in mind here is that patients’ levels of literacy also need to be considered because medical interpretation is not always a 100% accurate depiction of the intended meaning that’s translated from a source language into a target language.

Can it be used in all areas of healthcare?

When it comes to medical translations, the potential for content creation and the need to translate this into multiple languages at high speeds is crucial. Luckily, despite the drawbacks mentioned above, machine translation can be used in all, if not most, areas of healthcare. The following are some guidelines to consider:

• It’s essential to carry out a proper assessment of the machine translation program in order to ensure that the content that will be translated is suitable for the translation memory. This is essential for retaining consistency. 
• It’s also important to conduct pilot tests of both content and language combinations. The purpose of this is not only to see where cost savings can be introduced but also to determine the quality of the medical translation.
• A further guideline is to have a team of experienced and qualified human medical translators in the post-edit process to ensure high-quality output. 
• The use of glossaries, translation memories, style guides, term bases, and others will be helpful in leveraging the benefits of machine translation. 
• Artificial intelligence technology can be utilized in order to better customize the machine translation program, help with post-edit tasks, and even automate quality checks.

What does the future look like for machine translation in the healthcare industry?

Machine translation is used in the healthcare industry in massive proportions and is unlikely to decrease in the future. The reasons for this include the fact that borders are shrinking, medical information is being shared at a much faster rate, there is increased collaboration between medical organizations, etc. As such, machine translation is likely to see continued improvements and refinements in both processes, systems, and language corpuses used to expand and grow the initial framework. 

Despite some of the current drawbacks to machine translation in a clinical practice setting, these are only going to be fine-tuned as time progresses, which is expected to leave us with much more accurate medical translations, resulting in better adherence to clinical practice guidelines and good clinical practice overall.

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