Healthcare Natural Language Processing (NLP) Market - Forecasts from 2023 to 2028

The healthcare natural language processing (NLP) market is anticipated to rise at a CAGR of 38.89% during the forecast period.

The healthcare natural language processing (NLP) market has experienced significant growth due to the increasing adoption of NLP technologies in healthcare settings. As healthcare organizations recognize the promise of NLP in enhancing clinical decision support, information retrieval, and data analytics, the healthcare natural language processing market size has grown. Specific suppliers' healthcare natural language processing market share may vary depending on aspects like technical improvements, product offerings, client base, and industry relationships. The healthcare natural language processing market growth is likely to develop further as demand for NLP solutions continues to climb and healthcare organizations increasingly embrace data-driven methods, driven by the requirement for effective analysis of unstructured healthcare data.

The application of advanced language processing techniques and algorithms to extract meaningful information from unstructured healthcare data, such as clinical notes, medical literature, and patient records, is referred to as healthcare natural language processing (NLP). NLP technologies improve information retrieval, clinical decision support, and healthcare data analytics by allowing the analysis and interpretation of textual data.

The healthcare natural language processing market size is expanding rapidly as the healthcare sector recognizes the enormous potential of natural language processing technology. NLP technology can convert unstructured data into structured and actionable insights, allowing for better clinical decision-making, improved patient outcomes, and optimized healthcare operations. The healthcare natural language processing market growth has enormous promise in terms of enhancing clinical procedures, facilitating efficient information retrieval, and advancing healthcare research. As the sector generates vast volumes of unstructured data, the usage of NLP technology is projected to increase, revolutionizing healthcare analytics and changing the way healthcare practitioners engage with textual data.

Key players in healthcare natural language processing market:

• 3M Health Information Systems:3M Health Information Systems provides a variety of natural language processing (NLP) solutions for healthcare, such as clinical documentation enhancement, coding, and population health analytics. Their NLP solutions aid in the extraction of valuable clinical information from unstructured data, hence improving coding accuracy and clinical decision support.
• Linguamatics: Linguamatics specializes in natural language processing (NLP)--based text mining solutions for healthcare and life sciences. Their natural language processing (NLP) engine pulls significant insights from unstructured text, includingclinical notes, literature, and electronic health records, to aid in research, data analytics, and clinical decision-making.
• Clinithink: Clinithink offers NLP solutions for clinical comprehension and semantic search. Their natural language processing (NLP) technology enables the extraction and analysis of structured data from unstructured clinical documentation, therefore enabling activities like clinical research, revenue cycle management, and quality reporting.
• Health Fidelity: NLP-powered coding and clinical documentation solutions are available from Health Fidelity. By automatically analyzing and extracting valuable clinical information from unstructured data sources, its NLP software supports proper coding and revenue cycle management.

MARKET DRIVERS:

• Growing Volume of Unstructured Healthcare Data:

The increasing number of unstructured healthcare data refers to the growing amount of information created in healthcare that is difficult to organize or categorize. Clinical notes, physician narratives, medical imaging reports, and other documents fall under this category. This data explosion has been aided by the growth of electronic health records and digital healthcare systems. Managing and extracting insights from unstructured data effectively is a major problem, necessitating the use of modern technologies such as Natural Language Processing (NLP) to unlock its value for decision-making and research purposes.

• Enhanced information retrieval and search capabilities:

Enhanced information retrieval and search skills in healthcare relate to the capacity to swiftly and correctly obtain important information from enormous amounts of healthcare data. Healthcare Natural Language Processing (NLP) approaches provide improved search algorithms, semantic comprehension, and context-aware retrieval, allowing healthcare workers to swiftly identify and retrieve information for clinical decision-making and research reasons.

• Integration of NLP with healthcare applications and systems:

Natural Language Processing (NLP) integration with healthcare applications and systems entails embedding Natural Language Processing technology into current healthcare software and platforms. This interface enables the analysis and extraction of useful information from unstructured data sources, increasing clinical decision support, data analytics, and overall workflow and system efficiency.

• Increasing awareness of NLP benefits in healthcare:

The benefits of Natural Language Processing (NLP) in healthcare are becoming more widely recognized. NLP's capacity to extract meaningful insights from unstructured data, such as clinical notes and medical literature, is becoming recognized by healthcare practitioners and organizations. Advanced information retrieval, clinical decision assistance, and population health management are all possible with NLP. It promotes operational efficiency, research skills, and leads to more accurate coding and documentation. The healthcare sector is rapidly adopting NLP as a powerful tool for unlocking the possibilities of unstructured healthcare data as awareness grows.

The healthcare natural language processing market is expanding at a steady rate in the forecast period.

The market for healthcare natural language processing is segmented by component, technology, application, and geography. The component is further segmented into software and services. Technology is further segmented into machine-learning and rule-based.

North America is a market leader in the healthcare natural language processing market.

North America dominates the healthcare natural language processing (NLP) market. This is mostly due to factors such as strong healthcare infrastructure, early technological adoption, and the region's high concentration of major players. Because of its huge healthcare business and emphasis on digital health efforts, the United States contributes considerably to healthcare natural language processing market share. Furthermore, the region's emphasis on R&D, government funding, and the presence of significant healthcare organizations all contribute to the healthcare natural language processing market growth in North America.

Key Developments:

• In April 2023,3M Health Information Systems (HIS) announced a partnership with Amazon Web Services (AWS) to speed the development and growth of 3M M*Modal ambient intelligence. 3M will employ AWS Machine Learning (ML) and generative AI services, such as Amazon Bedrock, Amazon Comprehend Medical, and Amazon Transcribe Medical, as part of the cooperation to help speed, refine, and expand the delivery of 3M's ambient clinical documentation and virtual assistant solutions.
• In December 2022,Clinithink, the startup that created the world's first Healthcare AI capable of properly interpreting unstructured medical notes, collaborated with AstraZeneca Oncology UK on a new initiative aimed at identifying individuals with lung cancer at an early stage where therapy can be more successful. The project would be based on AI-approach where natural language processing (NLP) and Machine learning (ML) will be used to identify the asymptomatic and symptomatic patients who are in their early stage.

Segmentation

BY COMPONENT

• Software
• Services

BY TECHNOLOGY

• Machine Learning
• Rule-based

BY DEPLOYMENT

• Cloud-based
• On-premises

BY APPLICATION

• Clinical Documentation
• Machine Translation
• Medical Coding
• Clinical Decision Support
• Others

BY GEOGRAPHY

• North America
  • United States
  • Canada
  • Mexico
• South America
  • Brazil
  • Argentina
  • Others
• Europe
  • United Kingdom
  • Germany
  • France
  • Italy
  • Spain
  • Others
• Middle East and Africa
  • Saudi Arabia
  • UAE
  • Others
• Asia Pacific
  • Japan
  • China
  • India
  • South Korea
  • Indonesia
  • Taiwan
  • Others