The digital transformation of healthcare has come with as many benefits as it has new obstacles. Electronic health records (EHRs) are easier to share between healthcare providers but are labor-intensive to fill out correctly. How do we answer this issue?
The solution may lie with natural language processing (NLP). NLP is the ability of computers to comprehend natural language (i.e., the way people normally speak or write) and turn it into EHR-compatible verbiage. Powered by advances in artificial intelligence and machine learning, NLP may be the answer to help save time for providers and deliver better results for patients.
What Is An NLP?
Humans talking to computers has been a fixture in science fiction media for decades and a real capability for almost as long. However, this capability has been typically limited to the most basic verbal commands; language that is more casual, informal, or outside of its pre-programmed expectations is far too difficult for most speech-to-text programs to handle.
However, as technology has progressed, new methods for computers to analyze and understand language have emerged, leading to the evolution of NLP programs that we now see today.
Modern NLP programs rely on computational linguistics, which is the science of understanding human language for computers and software. This includes syntactic and semantic analysis, which helps machines understand typical conversational language. These tools free computers from relying on rigidly specific terms and sentence structures by analyzing the relationships between words in a sentence, whether written or spoken. Outside of healthcare, these same tools are also used in language translators, text-to-speech synthesizers, and speech recognition software in other sectors.
Types of NLP
Like any other piece of technology, NLP software has gone through several different versions 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 them.
- 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 mimicking 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.
Benefits of NLP Programs
The greatest advantage that NLP programs offer for healthcare is their ability to automatically listen to a conversation between providers and patients and automatically fill out fields in an EHR as they go. Rather than switch their focus back and forth between their patient and the healthcare computer, they can simply write or record notes, which the NLP software can then automatically translate into data in the EHR system.
NLP programs can sort through the differences in dialects, slang, and grammatical oddities that occur in a typical day-to-day conversation or decipher the imprecise language used by patients who (understandably) don’t know the correct technical terms for their condition.
AI-powered NLP programs can also work off of both written and audio notes, meaning healthcare providers can document their conversation however they prefer and let the NLP program transcribe the information afterward. An NLP program running on a medical AI box PC can dramatically reduce the amount of time providers need to spend on filling out EHRs and other forms of paperwork, sparing them from “pajama time” and letting them focus on their true calling: helping their patients.
Embrace Natural Language Processing with Cybernet Computers
Dealing with paperwork and EHRs is a major source of burnout for healthcare providers in a profession that is already struggling with employee retention. By allowing natural language processing programs to handle the tedious task of filling out these forms, healthcare groups can help prevent burnout and lessen turnover.
If your healthcare group is looking for computers that can support NLP software, contact the team at Cybernet Manufacturing. We’d be happy to discuss how our range of medical-grade tablets and computers can support these new programs and lesson the bureaucratic workload of your employees.
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