Natural language processing has many spheres to apply at. What are these spheres? Unstructured and semi-structured data is, by its nature, largely text based. The problem of the unstructured data exists also in the field of Healthcare Service.Nowadays clinical documentation is stored in two ways: paper-based records and electronic records. Paper records are good in some cases but require a significant amount of storage space compared to digital records.In the USA electronic records are gathered to EHR (electronic health record). EHR is a systematic collection of electronic health information about an individual patient or population.But the problem of such records is that 80 percent of such clinical documentation that exists in healthcare today is unstructured. It is sometimes referred to as "the text blob" and is stored in EHRs. The problem of this huge amount of information is that all valuable clinical data should be leveraged to make more informed clinical decisions, to ultimately improve patient care and reduce healthcare costs.Recently, there was a study published in JAMA, led by Harvey J. Murff and colleagues that validates natural language processing (NLP) technologies as a powerful tool to unlock data (meaning) from EHRs. However, the use of NLP in healthcare is not limited to information queries and while the above mentioned study reveals NLP as a way to track negative events after surgery, this use-case is just the tip of the iceberg when it comes to the value of NLP technologies for healthcare.The specialists are sure that Natural language processing will become a well-known, primary component of the point-of-care process, providing doctors with real-time information about a patient that they're documenting a medical record on behalf of, and will guide physicians to include the most thorough and accurate patient information as they are dictating their notes. Here you can find a report of AMIA (American Medical Informatics Association) that provides facts to support the enhancement of natural language processing of biomedical text. Sources used:KevinMd, The National Center for Biotechnology Information , wikipedia, dominionpayroll, world news article
