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Natural Language Processing in Healthcare

Doctors and natural language processing

It goes without saying that artificial intelligence (AI) is having a profound impact across industries today, healthcare not being an exception. Some of the most exciting AI applications are driven by natural language processing (NLP) technology. Simply put, NLP is a branch of AI focused on the interpretation and manipulation of human languages. In fact, NLP has already been tightly integrated into our daily lives: personal voice assistants, machine translation, autocorrect, and spam filter on your email system are all examples of NLP-driven applications.

The adoption of NLP in healthcare is rising due to its enormous potential to search, analyze, and interpret whopping amounts of unstructured data. For instance, NLP is highly promising in terms of data entry and extraction across electronic health records (EHRs), while it can give EHRs speech-recognition capabilities during clinician visits and help quickly find necessary information.

Many organizations have already started to leverage natural language processing solutions from Unicsoft to reduce their administrative cost and improve healthcare delivery. In this article, we’ll take a closer look at the potential of NLP to maximize the value of the EHR and healthcare data, and therefore improve health outcomes.

NLP Helps Doctors Cut Down On Administration Routines

One of the toughest challenges in care delivery is that physicians lack time to dedicate to their patients due to numerous administrative tasks. Sometimes doctors have to work overtime, which puts them at risk of burning out. NLP provides a solution to this issue. In many cases, clinicians have already replaced handwriting or typing with voice notes. With clinical dictation, doctors can devote more time to patient care.

NLP Enhances EHR Data Usability

The process of documentation in EHRs is known to be time consuming and inefficient. The two major challenges it presents include the time-consuming data entry and the issue of quickly finding critical patient information. Natural language processing streamlines data entry by offering speech recognition capability, enabling clinicians to maintain control of the process and potentially decrease the documentation burden. Next, NLP can facilitate an EHR interface that makes patient data easier to find. NLP techniques are used to extract key information: diagnoses, recommendations, timeline, or possible symptoms to streamline the decision-making process.

NLP Facilitates Predictive Analytics

NLP technology can analyze multiple healthcare reviews posted every day on third-party listings, and, which is even more amazing, identify human sentiment in unstructured comments, along with the context of how they are being used. For instance, a 2018 study used NLP to foresee suicide attempts by tracking social media. The outcomes showed clear signals of suicide attempts by Twitter users who posted fewer emojis, emojis of certain types like a broken heart symbol, or more tweets expressing annoyance or sadness prior to attempting suicide. This NLP-driven system had a 70% prediction rate with just a 10% false-positive rate. In addition, healthcare systems may use text and sentiment analytics to monitor consumer reviews, so clinicians can better understand the patients and use this data to enhance their services.

NLP Can Streamline Phenotyping

Phenotype is an individual’s observable physical characteristics. This includes your height and eye color, but also your overall health, your disease history, and even your behavior and general disposition. Phenotyping facilitates categorizing patients that help provide a deeper look into data. NLP provides analysts with a tool to derive and process unstructured data such as follow-up appointments, orders, symptoms, etc., making a huge deal of all patient data available for analysis and creating patient groups.

NLP Improves the Quality of Healthcare Services

Not to mention, NLP-driven tools streamline human communication by providing translation solutions, auto-complete, autocorrect, and voice recognition. The ability to exchange health information across different systems can help providers improve the quality of their services. Plus, NLP enables instant access to patient records, facilitates coding and billing, allowing clinicians to diagnose patients more effectively and avoid medical errors.

NLP Enables Simplified Financial Reporting

With NLP, financial reports can be generated automatically, and any necessary data can be issued upon request. It substantially reduces the time of collecting them. The patient, the hospital, the government and the insurance company can easily monitor all expenses and prevent fraud.

NLP Can Raise Patient Awareness and Involvement

Over the last few decades, regulatory guidelines caused a strong need for patient involvement in care. Today, patients can easily access their reports and other information related to healthcare. However, it’s not always beneficial. Patients might lack knowledge of medical terms and misinterpret their health data, which can have hazardous consequences. Natural language processing can effectively respond to this challenge: it can explain complex terms in a language that can be easily understood by patients, enabling them to be more involved and make an informed decision regarding their health.

To Wrap it Up

All in all, natural language processing is creating exciting opportunities for healthcare delivery and patient experience. It is here to disrupt documentation processes and enable quick and efficient decision-making.


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