Global Natural Language Processing (NLP) in Healthcare and Life Sciences Market – Industry Trends and Forecast to 2031

Global Natural Language Processing (NLP) In Healthcare And Life Sciences Market, By Component (Standalone Solutions and Services), NLP Type (Rule-Based NLP, Statistical NLP, and Hybrid NLP), Deployment Mode (On-Premises and Cloud), Organization Size (Large Enterprises and Small and Medium Enterprises), Application (Interactive Voice Response (IVR), Pattern and Image Recognition, Auto Coding, Classification and Categorization, Text and Speech Analytics, and Others), End-Users (NLP for Physicians, NLP for Researchers, NLP for Patients, and NLP for Clinical Operators) – Industry Trends and Forecast to 2031.

Natural Language Processing (NLP) in Healthcare and Life Sciences Market Analysis and Size

S&P Global's subsidiary, Kensho Technologies, launched Kensho Classify in March 2023, marking a significant advancement in Natural Language Processing (NLP) that contributes to the market's growth in healthcare and life sciences. This solution plays a pivotal role in enhancing data usability across industries by significantly improving content discoverability and streamlining the analysis of large text datasets. NLP technologies enable healthcare organizations and life sciences companies to process vast amounts of unstructured textual and speech data, such as clinical notes, patient records, medical literature, and research documents. This capability is pivotal in improving clinical decision-making, enhancing patient outcomes, and optimizing operational efficiencies across the healthcare continuum. Moreover, advancements in machine learning and artificial intelligence are expanding the capabilities of NLP, enabling deeper insights into patient demographics, treatment patterns, and healthcare trends.

Global natural language processing (NLP) in healthcare and life sciences market size was valued at USD 2.11 billion in 2023 and is projected to reach USD 8.49 billion by 2031, with a CAGR of 19.0% during the forecast period of 2024 to 2031. In addition to the market insights such as market value, growth rate, market segments, geographical coverage, market players, and market scenario, the market report curated by the Data Bridge Market Research team includes in-depth expert analysis, import/export analysis, pricing analysis, production consumption analysis, and pestle analysis.

Report Scope and Market Segmentation       

Market Definition

Natural Language Processing (NLP) in healthcare and life sciences refers to the application of computational techniques and algorithms to process and analyze natural language data (text or speech) generated within the contexts of medical and biological domains. NLP technologies enable computers to understand, interpret, and derive meaningful insights from human language, facilitating tasks such as clinical documentation, medical transcription, patient data analysis, disease prediction, and healthcare information management.

Natural Language Processing (NLP) in Healthcare and Life Sciences Market Dynamics

Drivers

• Increasing Adoption of Electronic Health Records (EHRs)     

The widespread adoption of Electronic Health Records (EHRs) across healthcare organizations has led to the accumulation of vast amounts of unstructured data, including clinical notes, medical reports, and patient histories. This surge in data volume underscores the need for Natural Language Processing (NLP) solutions capable of extracting valuable insights from unstructured textual information. NLP enables healthcare providers to analyze and interpret this data more effectively, facilitating improved clinical decision-making, personalized patient care, and operational efficiency, driving market growth.     

• Advancements in Artificial Intelligence (AI) and Machine Learning (ML)  

AI and ML algorithms enhance NLP systems' ability to analyze and interpret complex medical texts, patient records, and speech data with greater accuracy and efficiency. These technologies enable NLP to extract meaningful insights, detect patterns, and predict outcomes from large datasets, contributing to more informed clinical decision-making and improved patient outcomes. By leveraging AI and ML, healthcare providers can automate routine tasks, such as transcription and documentation, optimize treatment plans based on patient data analysis, and support research initiatives with sophisticated data analytics tools. Continuous advancements in AI and ML technologies are revolutionizing the capabilities of Natural Language Processing (NLP) within the healthcare sector.

Opportunities

• Integration with Wearable Devices and IoT    

Integrating NLP with wearable devices that capture real-time patient data, can enhance predictive analytics, monitor patient health remotely, and intervene proactively in case of anomalies or critical health events. NLP-powered IoT applications enable continuous monitoring and analysis of patient-generated data, facilitating personalized healthcare interventions and improving patient outcomes through early detection and preventive care strategies. Integrating NLP capabilities with wearable devices and Internet of Things (IoT) technologies presents significant opportunities to revolutionize healthcare delivery.

• Collaboration with Pharmaceutical and Biotech Companies    

Collaborating with pharmaceutical and biotechnology companies to integrate Natural Language Processing (NLP) into drug discovery, clinical trials management, and pharmacovigilance processes drives efficiency and accelerates innovation in life sciences. NLP enhances the efficiency of clinical trials by automating data extraction from medical records and patient reports, facilitating faster recruitment and analysis of trial data. For instance, in February 2022, Edifecs, Inc. partnered with VirtualHealth, a leading provider of medical management technology, to integrate automated prior authorization into the HELIOS platform. This collaboration aims to enhance service delivery for healthcare payers and providers. By leveraging NLP's ability to interpret medical literature and analyze adverse event reports, pharmaceutical companies can enhance drug safety monitoring and regulatory compliance, creating new opportunities for natural language processing (NLP) in healthcare and life sciences market.

Restraints/Challenges

• Data Privacy and Security Concerns  

Managing sensitive patient data presents significant challenges related to privacy regulations and data security breaches in the adoption of Natural Language Processing (NLP) solutions within healthcare. Healthcare organizations must adhere to stringent data protection laws, such as HIPAA in the United States and GDPR in Europe, to safeguard patient confidentiality and prevent unauthorized access to personal health information. NLP systems must employ robust encryption methods, access controls, and anonymization techniques to protect patient data throughout its lifecycle.     

• Integration Complexity of NLP Systems  

Integrating natural language processing (NLP) systems with existing healthcare IT infrastructure, including EHRs and clinical systems, can be complex and time-consuming. Healthcare organizations face challenges such as interoperability issues, data standardization, and compatibility with legacy systems when deploying NLP solutions. The integration process requires careful planning, customization, and coordination with IT teams to ensure seamless connectivity and functionality across different platforms. Moreover, training healthcare staff to effectively utilize NLP tools and interpret the insights generated poses additional implementation challenges.

This market report provides details of new recent developments, trade regulations, import-export analysis, production analysis, value chain optimization, market share, impact of domestic and localized market players, analyses opportunities in terms of emerging revenue pockets, changes in market regulations, strategic market growth analysis, market size, category market growths, application niches and dominance, product approvals, product launches, geographic expansions, technological innovations in the market. To gain more info on the market contact Data Bridge Market Research for an Analyst Brief, our team will help you take an informed market decision to achieve market growth.

Recent Developments

• In February 2024, Persistent Systems partnered with Microsoft to launch a Population Health Management (PHM) solution powered by Generative AI. This innovative solution supports value-based care models and leverages Social Determinants of Health (SDoH) to evaluate non-clinical patient needs. It enhances predictive capabilities related to healthcare costs linked with clinical conditions
• In June 2023, Apixio, a company specializing in artificial intelligence for value-based healthcare, completed a merger with ClaimLogiq, a technology firm specializing in pre-payment claim accuracy for health plans. Following the merger, the combined entity will operate under the name Apixio. This strategic union creates a leading data and analytics provider in the healthcare industry, harnessing an advanced AI platform

Natural Language Processing (NLP) in Healthcare and Life Sciences Market Scope

The market is segmented on the basis of component, NLP type, deployment mode, organization size, application, and end-users. The growth amongst these segments will help you analyze meagre growth segments in the industries and provide the users with a valuable market overview and market insights to help them make strategic decisions for identifying core market applications.

Component

• Standalone Solutions
• Services

NLP Type

• Rule-Based NLP
• Statistical NLP
• Hybrid NLP

Deployment Mode

• On-Premises
• Cloud

Organization Size

• Large Enterprises
• Small and Medium Enterprises

Application

• Interactive Voice Response (IVR)
• Pattern and Image Recognition
• Auto Coding
• Classification and Categorization
• Text and Speech Analytics
• Others

End-Users

• NLP for Physicians
• NLP for Researchers
• NLP for Patients
• NLP for Clinical Operators

Natural Language Processing (NLP) in Healthcare and Life Sciences Market Regional Analysis/Insights

The market is analyzed and market size insights and trends are provided by country, component, NLP type, deployment mode, organization size, application, and end-users as referenced above.

The countries covered in the market report are U.S., Canada, Mexico, Germany, France, U.K., Netherlands, Switzerland, Belgium, Russia, Italy, Spain, Turkey, rest of Europe, China, Japan, India, South Korea, Singapore, Malaysia, Australia, Thailand, Indonesia, Philippines, rest of Asia-Pacific, Saudi Arabia, U.A.E., South Africa, Egypt, Israel, rest of Middle East and Africa, Brazil, Argentina, and rest of South America.

North America is expected to dominate the market due to increasing demand for NLP solutions and substantial investments in robotics and NLP-related research and development initiatives. The region's advanced healthcare infrastructure and strong presence of key technology giants facilitate the rapid adoption of NLP technologies across various applications, including clinical documentation, patient interaction analysis, and data analytics.         

Asia-Pacific is expected to witness significant growth due to widespread adoption of advanced technologies aimed at optimizing business operations. Increasing investments in healthcare IT infrastructure and rising awareness about the benefits of NLP in improving clinical decision-making processes and patient engagement are key factors driving this growth.

The country section of the report also provides individual market impacting factors and changes in regulation in the market domestically that impacts the current and future trends of the market. Data points like down-stream and upstream value chain analysis, technical trends and porter's five forces analysis, case studies are some of the pointers used to forecast the market scenario for individual countries. Also, the presence and availability of global brands and their challenges faced due to large or scarce competition from local and domestic brands, impact of domestic tariffs and trade routes are considered while providing forecast analysis of the country data.

Competitive Landscape and Natural Language Processing (NLP) in Healthcare and Life Sciences Market Share Analysis

The market competitive landscape provides details by competitor. Details included are company overview, company financials, revenue generated, market potential, investment in research and development, new market initiatives, global presence, production sites and facilities, production capacities, company strengths and weaknesses, product launch, product width and breadth, application dominance. The above data points provided are only related to the companies' focus related to market.

Some of the major players operating in the market are:

• 3M (U.S.)
• Cerner Corporation (U.S.)
• Nuance Communications Inc. (U.S.)
• Dolby Systems Inc. (U.S.)
• Microsoft (U.S.)
• IBM (U.S.)
• Google LLC (Alphabet Inc.) (U.S.)
• Amazon Web Services Inc. (U.S.)
• Apixio Inc. (U.S.)
• Averbis (Germany)
• Clinithink (U.S.)
• Lexalytics (U.S.)
• Narrative Science (U.S.)
• JohnSnow Labs (U.S.)
• BenevolentAI (U.K.)