Analytics, AI/ML
January 30, 2024

What is the role of NLP in Healthcare?

Cogent Infotech
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Dallas, TX
January 30, 2024

What is the role of NLP in Healthcare?

The healthcare industry has seen a significant rise in utilizing natural language processing (NLP). NLP is a powerful tool that can help in various areas, from medical record analysis to patient diagnosis and treatment.

Recent data shows that the worldwide market size of NLP in healthcare and life sciences is anticipated to grow to US$7.2 billion by 2027, increasing at a CAGR of 27.1% between 2022 and 2027, rising from US$2.2 billion in 2022.

In this blog post, we'll discuss the role of NLP in healthcare, its benefits, its driving factors, and how it can be used to improve patient care.

Role of NLP in Healthcare

A vast amount of structured and unstructured data is collected daily by healthcare systems like EHRs and sensors in the form of medical records, lab results, and patient surveys. NLP can unlock the full potential of this data to gain insights into patient behavior and needs, identify high-risk patients, and improve patient outcomes.

NLP algorithms can also analyze patient records and medical documents, extract essential information, and identify patterns to inform medical decisions. For example, NLP algorithms detect medical conditions, identify diagnostic and treatment options, and predict patient outcomes. 

4 Factors Driving NLP Adoption in Healthcare

As NLP is receiving more attention in healthcare, providers are creating NLP solutions to understand and analyze healthcare data to make it usable for healthcare professionals. Some factors that are driving the adoption of NLP systems in healthcare are:

Identifying Patients who Need Improved Care

Improved care reduces readmission rates, saving healthcare facilities time and money. Also, identifying patients who need improved care ensures quality health care. For example, patients with mental health issues may need improved care to manage their symptoms.

NLP can identify patients that require specialized care by analyzing their medical records and other data sources. NLP systems can detect patterns in patient data that indicate the need for additional care, such as missed appointments, repeat visits to the hospital or inadequate follow-up care. This gives healthcare providers an added assistance for patients' management.

Managing Clinical Data

The growing use of patient health record systems has led to the generation of massive amounts of clinical data, including the history of past diseases, prescriptions, and allergies. NLP can analyze the data and draw actionable insights from it.

Additionally, NLP can be used to identify and classify different medical concepts, such as symptoms, diseases, and treatments, from unstructured data. It can help to improve the accuracy of clinical decision-making and to reduce medical errors. By leveraging NLP, healthcare providers can better care for their patients and streamline their workflow.

Population Health Management 

Population health management aims to improve the health of a population by focusing on preventative care, health promotion, and disease management. Healthcare professionals may identify high-risk populations, such as those living in poverty or with chronic health conditions, and develop strategies, such as providing access to preventive care, disease management, or lifestyle interventions to help reduce the risk of illness and improve overall health.

NLP techniques can simplify and automate processes that sort, organize, and interpret complex medical data. NLP applications might identify patients with certain conditions and alert clinicians to take action. It could help with chronic disease management, preventative care, and population health surveillance. Additionally, NLP can help identify gaps in care and provide targeted interventions to improve patient outcomes. 

For instance, NLP systems can analyze the risk of type 2 diabetes in a patient population. It does so by identifying words or phrases associated with type 2 diabetes risk factors, such as obesity, lack of exercise, sedentary lifestyle, smoking, poor diet, etc. It then analyzes the frequency of these words or phrases used by patients to determine their likelihood of developing type 2 diabetes. 

Electronic Health Records

Enhanced clinical communication between patients and providers through electronic health records (EHRs) is essential to improving patient care. EHRs provide a comprehensive record of a patient's health history, including their medical history, laboratory results, medication list, and more. This information can be accessed quickly and easily by both the patient and provider, improving patient care and communication.

For example, if a patient has a new medical concern, their provider can use the EHR to quickly review their medical history and current condition. It allows the provider to make a more informed decision about the care needed for the patient. 

Integrating NLP systems with EHRs can help streamline the data entry process by automatically extracting patient information from unstructured text documents and entering it into the EHR. It could include extracting patient demographics, clinical notes, test results, and other data, which can be used to create a more comprehensive view of the patient's health history. 

Why NLG is crucial for Patients?

Empower Patients Health Literacy

Health literacy is crucial because it helps patients make informed decisions about their health care. For example, implementing NLP-driven chatbots in the healthcare industry helps patients understand their symptoms and conditions. This knowledge enables them to make informed decisions about their health and stay on track.

Address the Need for Higher-Quality of Healthcare

All individuals should have access to the care and treatment they need. Higher-quality healthcare can help save lives by providing better diagnoses, treatments, and preventive care.

NLP can improve healthcare quality by automating the process of extracting useful clinical information from unstructured data. It can identify potential safety issues, such as drug interactions and discrepancies between prescribed medications and actual treatments. By using NLP systems to monitor patient records, healthcare professionals can quickly and accurately detect potential health risks and take the necessary action to ensure patient safety. 

Benefits of NLP in Healthcare

Some of the benefits of NLP in healthcare include:

Improved Patient Engagement

Automating patient engagement using NLP will help healthcare professionals understand and respond to patient queries more efficiently. It can also enable the generation of tailored content that meets patients' individual needs.

Improved Quality of Care

NLP can analyze patient data and determine patterns. It can tell which treatments work the best or what drugs are most often used. This information helps doctors make better decisions and give better care to their patients.

Enhanced Insights into Patient Health

 NLP can help doctors better understand their patients by quickly and accurately analyzing large amounts of patient data and deriving valuable insights.

Reduced Costs

NLP can save costs in healthcare by reducing the time spent on paperwork and other administrative tasks. NLP systems can automatically extract information from medical records and other documents instead of having people do it by hand.

The Future of NLP in Healthcare

NLP has not yet been fully utilized in the healthcare industry. Still, many organizations are investing in related technologies such as semantic big data analytics and cognitive computing to make progress. As these tools continue to be developed, they could help healthcare professionals manage the vast amounts of data they encounter daily, alleviating some cognitive burdens of interpreting and understanding it.


NLP can completely change the healthcare industry if it can be perfected to extract and present data accurately and in an understandable way. By developing algorithms that are intelligent and specific to the needs of the industry, the technology can be used to solve complicated problems in precision medicine and everyday tasks like coding a reimbursement claim or scheduling appointments. NLP has a huge potential, leading to better physical performance and patient care.

Cogent Infotech helps organizations make better decisions, identify and maximize opportunities, maximize efficiency and cost savings, and create sustainable competitive advantages. To read more articles about NLP and related emerging technologies, please visit the Cogent website

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