Application of text analytics and NLP in healthcare

Natural Language Processing and Text Analytics are becoming all the more mainstream in the healthcare domain. The growing lot of unstructured data has been one of the significant challenges for these service providers worldwide. Health care providers must utilize the data pool efficiently. It will enable them to make better decisions. Adequate data analytics will help a healthcare service provider get the best insight into patients’ expectations and needs. Consequently, it becomes easier to match their demand with the most relevant solutions. It is where NLP and text analytics solutions can play a significant part.

An overview of the contemporary picture of text analytics across the healthcare industry worldwide

The text analytics concept has become more popular in the healthcare industry since 2016. However, it has not covered more than five percent of the total potential. Typically, healthcare service providers adopt the manual record-keeping system, majorly depending on the coded data. This approach significantly restricts the capacity to comprehend the patient behavior. The application of text analytics has been helping healthcare service providers worldwide to handle the unstructured data in the most proficient manner. The methodology is still in its infancy. But, indeed, it is going to take significant strides in the years to come. Understanding this transformation as the demand of the time, you need to adopt this methodology.

The impact of NLP and text analytics on the healthcare industry around the globe

The shift to the text analytics approach has paved the way for significant changes to develop the domain of healthcare services. It is helping these providers gain a more accurate observation about the medical history of their patients. The application of text analytics has enabled healthcare service providers to serve more than three million PAD patients. These individuals stand highly vulnerable to the threat of coronary cardiac issues and other heart ailments. These risks and threats embrace severe health hazards and financial hardships for patients and their families. Healthcare providers embracing text analytics methodology have managed to mitigate the risks and threats for these individuals.

What is the typical scenario about text analytics in the healthcare industry?

Typically, the process involves the participation of a data Scientist, assigned to develop a specific NLP algorithm. The purpose of this algorithm is to determine the count of patients suffering from various health issues. Consequently, the data scientist will validate the NLP algorithm, reporting the outcome to the concerned investigator. Thus only the stakeholders will have a piece of precise knowledge about the patient data. The framework, in this regard, demands specialized algorithms that serve stakeholders in closed groups.

What can be the ideal scenario about the application of text analytics in the healthcare domain?

The ideal scenario will be significantly different than the usual approaches in applying text analytics to healthcare. In the ideal condition, a data scientist will develop a specialized algorithm. Subsequently, the professional will deploy the algorithm to the analytical ecosystem, running on a nightly basis. It will allow an authorized user to utilize the analytical outcome. Consequently, the algorithm result gets combined with coded data. The objective is to develop a precise yet comprehensive patient registry.

In the ideal condition, the healthcare framework is aware of the counts of patients under different categories. Likewise, it will also track the remedial measures applied to these patients and the outcome it produces. It helps providers to track the gap in offering adequate medical care. The system must facilitate nontechnical users to utilize the system proficiently.

Related Article: How Voice to Text and NLP based solutions can drive efficiency into telehealthcare

How text search benefits healthcare companies?

Speaking about text analytics, Google is undoubtedly the pioneer. Users hold the opinion that the search engine is user-friendly, and it is highly accurate and fast.

  1. It will complete your sentences, ensuring that users find the most relevant answer to their query. However, you cannot overrule the fact that the mechanism appears highly complex and intricate than usual.
  2. It is a fact that Google features a simple, yet a highly sophisticated mechanism that helps users to leverage the text analytics concept.
  3. Understanding this, healthcare provider worldwide majorly relies on the Google mechanism to make the concept maximum.

To the core of the methodology stands a unique Index. It is precisely similar to the ending of a book, listing words in the entire text. It goes as it appears in the search engine documenting index. The algorithm will read all the documents, eventually splitting it into different words, thereby developing a sorted list for the words involved.

Tricks and tips to excel in the application of text analytics in the healthcare domain

  • Focus on optimizing the result display for the use cases involved. It will help in creating the most relevant solution to the need of the users.
  • On aggregating the text analytics results, one can offer access to the most crucial results. The best thing is that it will never involve any compromises with privacy and confidentiality.
  • It would help if you expanded the quest with appropriate healthcare terminologies. You can expect the most insightful analysis results if you expand the quest with suitable healthcare terminologies.
  • Remember, the top search engines come up with suggestions that comply with the queries in the manner users type it. If you expand the search appropriately, it will make your brand more visible to the target customers.
  • Your focus should be on refining the results in the context. It is highly beneficial for clinical applications. Eventually, it gets you the capacity to handle the utilize the heathcare data most productively. It is for the reason that when you describe analytical results in the lights of the clinical aspects, it comes the most effective to give a precise account about the patient concerned.


The discussion above shows that the usual approaches and orientations in the healthcare services will change majorly as NLP and text analytics methodologies become all the more mainstream.

Author: Muthamilselvan is a passionate Content Marketer and SEO Analyst. He has 5 years of hands on experience in Digital Marketing with IT and Service sectors.

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