The healthcare industry relies heavily on data to find patterns, make breakthroughs, and improve the lives of all patients. However, healthcare providers deal with so much data that it is difficult to store, analyze, and synthesize all of it in meaningful and efficient ways. This is a problem that cannot be solved with human minds alone. Artificial intelligence, however, presents a promising solution for handling data analytics in the healthcare industry.
Early forms of AI have already been implemented in every major industry. Though the technology is young, it is growing at an exponential rate. AI systems learn as they go, getting better and faster at analyzing data to help humans make decisions. One of the methods by which AI does this is known as Natural Language Processing, or NLP.
Natural Language Processing (NLP): What is It?
NLP describes the ways in which artificial intelligence systems gather and analyze raw data from human language to extract patterns, uncover meaning, and formulate responses. NLP focuses on four categories of language: syntax, semantics, discourse, and speech. In other words, NLP attempts to get to the heart of language formation and use that understanding to automate and improve human processes.
NLP can be rule-based or statistical. Rule-based NLP requires that humans code a set of heuristics into the system beforehand, while statistical NLP requires that the AI learn its own set of rules based on large amounts of data. This latter method may take longer, but it tends to produce more authentic results that help advance NLP technology further.
A crude example of NLP in action would be the AI robot Sophia having seemingly off-the-cuff conversations with interviewers. Experts claim that Sophia does not fully express NLP, however, as “she” likely comes with pre-programmed answers. Ideally, NLP systems would gather natural language data in real time, analyze it faster than the human brain, and come up with truly original responses, not already programmed or biased.
How NLP Can Help Healthcare Providers
Because the healthcare industry deals with so much data, there is perhaps no better application for NLP than health analytics. When it comes to prognosis and record-keeping, healthcare providers can be incredibly limited and inefficient. Medical professionals must sort through data on each individual patient and analyze it from every angle to help determine diagnoses and treatment solutions. Binary Fountain’s NLP technology greatly reduces the time and energy spent sifting through this data, helping providers make better decisions for their patients and giving them actionable insights for improving patient experience.
By targeting patterns of language, finding keywords, comparing records, and analyzing patient data, NLP systems hone in on the most relevant information. This helps healthcare providers improve patient experience in multiple ways. First, patients spend less time in the waiting room and in the doctor’s office itself. With Natural Language Processing, doctors can easily find the best possible treatment method for a specific patient based on his/her genetic information, previous health records, and other probabilities.
NLP and Patient Feedback
Natural Language Processing also proves valuable in gathering insights from patients. Healthcare providers who want to better manage their reputation or learn more about their patients can use NLP technology to find and analyze relevant data regarding patient experience and more. For example, NLP could identify reviews with phrasing like ‘waiting’ ‘long time’ or ‘after an hour’ to determine a doctor’s office was having issues with wait times.
By targeting and analyzing keywords and phrases from social media, online review sites, and post-care surveys, the algorithm can report on areas that need attention. This information helps healthcare providers improve the patient experience while in the clinic and better engaging patients.
Healthcare facilities would also increase patient satisfaction and reduce employee burden using NLP. Patients could enter information and/or ask questions about their health in a text field, then, NLP systems could respond accordingly, eventually connecting the patient to an online doctor if necessary.
Natural Language Processing is changing the way all industries, including healthcare, gather information, analyze it, and use that data to improve all aspects of the operation.
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