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Top 5 Benefits of NLP in Healthcare

The healthcare space is growing exponentially, especially after the COVID-19 pandemic. It is reported that the global healthcare expenditure is expected to reach USD 10 trillion by 2022. 

NLP or Natural Language Processing in the healthcare space poses some unique and exciting opportunities. NLP provides a slide through an enormous amount of new data and leverages it to boost outcomes, optimize costs, and provide optimal care quality.

Gradually, the application of technology has brought many changes to the healthcare industry for the better. Whether it’s managing ongoing organizational processes in hospitals, giving personalized care and treatment or aiding better access, technological headways like mobile healthcare, a.k.a as mhealth, have modernised the healthcare sector to a great extent.

Let us dive deeper into how natural language processing in healthcare is transforming the healthcare space. But first, what is NLP in healthcare?

What is NLP in Healthcare? 

NLP illustrates the manners in which machine learning systems gather and assess unstructured data to derive patterns, understand the purpose and thus compose feedback. NLP facilitates healthcare providers to automate managerial jobs, invest more time in taking care of the patients, and enhance the patient’s experience using real-time data. 

The adoption of natural language processing in healthcare is rising because of its distinguished potential to search, examine and evaluate enormous amounts of patient datasets. Using advanced medical algorithms, NLP technology services can utilize relevant previously thought insights hidden in text form. NLP in healthcare can give in depth insights into understanding quality, improving methods, and better results for patients.

Top 5 Benefits of NLP in Healthcare

1. Speech Recognition

NLP benefits speech recognition by allowing clinicians to transcribe notes for proper Electronic Health records (EHR) data entry. Front-end speech recognition eliminates the task of doctors to record notes. At the same time, back-end technology works to detect and fix any errors in the transcription before passing it on for human proofing. 

2. Clinical Documentation

Clinical documentation using NLP helps free clinicians from the cumbersome physical systems of EHRs and allows them to invest more time in patient care.
The NLP innovations bring out applicable data from speech recognition equipment which will significantly change logical data used to run VBC and PHM endeavors. This has better results for the clinicians.

3. Automated Registry Reporting

NLP helps extract values as needed by each use case. Health IT systems are overwhelmed by administrative reporting. To enable automated reporting, health systems will have to recognize when an ejection fraction is documented as part of a note and save each value in a form that the organization’s analytics platform can utilize for automated registry reporting.

4. Review Management & Sentiment Analysis

 NLP can assist healthcare organizations to manage online reviews. It can collect and assess thousands of reviews daily on 3rd party websites. In addition, NLP can find out PHI or Protected Health Information, profanity, or any data related to HIPAA compliance. NLP can also track customers’ attitudes by understanding positive and negative words in the review. 

5. Clinical Trial Matching

Using NLP and machine learning in healthcare for recognizing patients for a clinical trial is a significant use case. A few companies are attempting to address the challenges in this area using Natural Language Processing engines for trial matching. With the current growth rate, NLP can automate trial matching and make it a seamless procedure. 

Conclusion

The benefits of using natural language processing solutions are endless. NLP can help optimize patient experience, reduce costs and improve overall care outcomes. Although the healthcare industry still needs to upgrade its data capabilities, it has a tremendous potential to enhance care delivery and simply work significantly. Hence, NLP and other ML tools will be the key to oversee clinical decision support and patient health.

Despite all its benefits, NLP is not a single solution to all problems. Hence, the system needs to comprehend the sublanguage used by medical experts and patients.

NLP experts at Maruti Techlabs have vast experience working with the healthcare industry and thus can help your company receive the utmost from real-time and past data. With their AI-driven NLP services, they are supporting leading hospitals and healthcare units across the globe.

Vinay Kumar
Student. Coffee ninja. Devoted web advocate. Subtly charming writer. Travel fan. Hardcore bacon lover

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