The Advantages of Natural Language Processing in Healthcare

Natural language processing (NLP) can save healthcare providers time and energy by automatically transcribing notes into the correct paperwork.

Healthcare providers must fill out reams of paperwork for every patient they treat. Natural language processing can let computers and AI handle this workload, letting providers focus on treating patients instead.

What is Natural Language Processing (NLP)?
Natural Language Processing (NLP) is the field of software focused on enabling computers to listen and understand language the same way that humans can. Historically, NLP software has been very limited and could not handle much more than very basic and formal verbal commands. More casual and informal language fell outside the pre-programmed expectations of the software and could not be processed.

Modern NLP programs rely on computational linguistic techniques, which translate human language into a format that is easier for computers to process. This includes techniques like syntactic and semantic analysis, which help them understand conversational language by looking at the relationships between words in a sentence.

Types of NLP
NLP software has gone through multiple iterations over the years.

Rules-based NLP: These programs were based on if-then decision trees with preprogrammed rules and could only answer in response to very specific prompts. These models were extremely limited and could not scale in terms of capability, which led to them being replaced.
Statistical NLP: A statistical NLP extracts, classifies, and labels each element of the text or voice data and then assigns a statistical likelihood to each meaning of those elements. These NLP programs rely on machine learning and introduced the technique of “mapping” language elements like words and grammatical rules onto vector representations so that language can be modeled using mathematical methods, making it easier for computers to understand and analyze it.
Deep learning NLP: Deep learning NLP programs are an evolution of statistical NLPs and rely heavily on the implementation of machine learning and AI neural networks. These networks are designed to mimic how a human mind works, effectively copying a person’s learning ability. By reviewing massive data sets and learning from the patterns within them, a deep learning-based NLP can provide more accurate transcriptions of dialogue.

Applications for NLP in Healthcare
NLP software in healthcare is a particularly hot topic, as it can copy, transcribe, and expedite the massive amount of verbal and written communication between patients and providers.

Clinical Documentation and Management
Filling out the forms and paperwork associated with healthcare is a colossal timesink for providers, to the point that it can even overtake their off-hours as "pajama time." NLP software running on a medical computer can transcribe notes or record an appointment and then automatically fill out fields in the EHR system. More advanced NLP technology can even correct errors during transcription, preventing medical accidents from occurring.

Patient Care and Diagnosis
NLP software’s ability to discern phrases or terms from notes lets it assist clinicians in patient care and diagnosis. For example, the software can detect key symptoms that the patient is experiencing, compare them with other testimonies from other patients, and offer suggestions as to what condition the patient is experiencing. This is especially important in situations like early infection detection, where an early and accurate diagnosis can literally be the difference between life and death.

Big Data Analytics
Healthcare groups can use NLP software to analyze enormous amounts of data, enabling easier clinical trial matching and population health management. This makes critical responsibilities such as pairing patients with the right clinical trials and early pandemic detection easier.

Benefits of NLP in Healthcare
Implementing NLP software in healthcare processes can bring major benefits for healthcare providers, freeing up time during and after a shift.

Greater Efficiency for Healthcare Providers
The greatest advantage that NLP offers for healthcare is its ability to listen to a conversation between a provider and patient, automatically filling out fields in an EHR as they go. This lets the provider focus entirely on the patient, with only minor amounts of review and editing required afterwards. This reduces the time spent filling out EHRs and spares providers from pajama time, letting them focus on their true calling: treating their patients.

Dialectical Flexibility
Another significant benefit of modern NLP software is that it can sort through various dialects, slang, and grammatical oddities that occur in a typical day-to-day conversation. It can also decipher the imprecise language used by patients who (understandably) don’t know the correct technical terms for their conditions. This places it far ahead of previous generations of speech processing software, which struggled to decipher or transcribe more casual dialogue.

Flexibility Across Written and Audio Notes
AI-powered NLP programs can work off of both written and audio notes, letting providers document their conversations however they prefer and letting the NLP program transcribe afterwards. An NLP program running on a medical AI box PC is the perfect means for doing so.

Challenges for NLP in Healthcare
There are always challenges when it comes to adopting new technology and tools, and NLP is no different. The most important hurdles to overcome when using NLP software are:

Specialized Equipment
First and foremost, natural language processing requires specialized software to run, as well as hardware to support it. NLP programs, especially AI-powered versions, require powerful computers to run them alongside EHRs, audio recording software, and other tools. If the provider wants to take audio notes, they will also need effective recording equipment that can clearly pick up the voices of their patients.

Cost
Obviously, any new tool comes with a price tag. Along with licensing NLP software for use, healthcare groups must also consider the price of new computers capable of supporting said software. One way to manage costs for new equipment is by working with an original equipment manufacturer (OEM). An OEM can customize products to the exact specifications of the end-user, ensuring you can get the most out of your purchase without breaking your budget.

Training and Adoption
The final major hurdle to overcome is encouraging its adoption by the actual end-users; in this case, healthcare providers. In this stage, giving providers the time to train and actually familiarize themselves with the new tools. It’s also critical to listen to user feedback during this time, so that you can identify areas of improvement and make deploying the NLP software easier.

NLP-Capable Computers from Cybernet Manufacturing
Integrating NLP into healthcare operations can save critical time for providers, leading to a less stressful work environment and more time to focus on what actually matters: the health of their patients.

If you’re looking for medical-grade computers that can support NLP software, contact the team at Cybernet Manufacturing. We’d be happy to explain how our computers can enable these high-demand but powerful programs.