NLP In Healthcare And Life Sciences Market To Reach $37.0 Billion By 2030

NLP In Healthcare And Life Sciences Market Growth & Trends

The global NLP in healthcare and life sciences market size is expected to reach USD 37.0 billion by 2030. It is projected to grow at a CAGR of 34.7% over the forecast period, according to a new report by Grand View Research, Inc. The growth of the market is attributed to the increasing demand to enhance care delivery and patient engagement, the growing need for predictive analytics to improve significant health concerns, the rising focus on enhancing clinical decision support, and the growing investment for AI integration in healthcare.

The increasing demand for advanced clinical decision support is driving the adoption of NLP in healthcare and life sciences. Natural Language Processing (NLP) offers a solution by enabling the extraction of complex information from various sources beyond the capabilities of conventional clinical decision support systems. This enhances decision-making by incorporating unstructured data, such as physician narratives and patient notes. Integrating NLP aims to improve clinical decision support, providing a more thorough understanding of patient data and ultimately facilitating better healthcare outcomes and well-informed medical actions. For instance, in November 2030, Elsevier Health, a medical information and analytics leader, entered a strategic alliance with OpenEvidence, a provider of artificial intelligence capabilities in the medical field. This collaboration aims to develop ClinicalKey AI, an advanced clinical decision support system. This system merges up-to-date, evidence-based medical content with advanced generative AI to assist healthcare professionals during patient care. It features a natural language interface that provides access to content alongside continuously updated evidence-based research crucial for medical training and decision-making at the point of care.

Artificial Intelligence (AI) and Machine Learning (ML) technologies were increasingly utilized for precise diagnostic processes, mostly in identifying COVID-19-positive individuals through tailored patient data. A study published by NCBI in 2020 demonstrated that AI-enhanced algorithms successfully identified 68% of COVID-19-positive cases within a sample of 25 patients, initially misdiagnosed as negative by medical practitioners. The deployment of AI and ML in healthcare aims to improve patient outcomes, minimize equipment downtime, and reduce medical costs, contributing to market expansion. The onset of the pandemic has significantly boosted the integration of AI-driven technologies in patient and medication management, diagnostics, system interoperability, claims handling, workflow enhancement, and cybersecurity measures.

Moreover, some of the key players in the market, such as IBM, Microsoft, Google (Alphabet Inc.), IQVIA, and Dolbey Systems, Inc., among others, are adopting various strategies such as product launches, partnerships, expansions, collaborations, and mergers & acquisitions. Through these strategic initiatives, market players are trying to strengthen their market positions and expand their customer base. For instance, in April 2023, Google Cloud introduced its AI-enabled Claims Acceleration Suite to enhance health insurance prior authorization and claims processing efficiency. Utilizing the Claims Data Activator, this solution aims to mitigate administrative burdens and reduce costs for health plans and providers by transforming unstructured data into structured data. It leverages technologies such as Document AI, Healthcare Natural Language API, and Healthcare API for data conversion processes. This facilitates quicker, more informed decision-making, potentially improving patient care.

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NLP In Healthcare And Life Sciences Market Report Highlights

• The market is segmented by technique into smart assistance, optical character recognition, auto coding, text analytics, speech analytics, and classification and categorization. The smart assistance segment held the largest market share of 18.71% in 2023. The increasing demand for enhanced patient care and medication adherence fuels the demand for smart assistance in the healthcare sector.

• Based on end use, the market is segmented into providers, payers, Life Science Companies, and others. Life Science Companies accounted for a significant market share of 43.73% in 2023, driven by the Increasing awareness regarding the benefits associated with the adoption of NLP.

• North America dominated the market with a revenue share of 43.60% in 2023. This is attributed to the presence of sophisticated healthcare infrastructure, supportive government policies, well-established IT infrastructure, and high digital literacy. Moreover, Asia Pacific is anticipated to witness the fastest growth at a CAGR of 37.0% from 2024 to 2030.

• Some of the notable companies in the market are IBM, Microsoft, Google (Alphabet Inc.), IQVIA, and Dolbey Systems, Inc., among others.

NLP In Healthcare And Life Sciences Market Segmentation

Grand View Research has segmented the global NLP in healthcare and life sciences market based on technique, end-use, and region:

NLP in Healthcare And Life Sciences Technique Outlook (Revenue, USD Million, 2018- 2030)

• Smart Assistance

• Optical Character Recognition

• Auto Coding

• Text Analytics

• Speech Analytics

• Classification and Categorization

NLP in Healthcare And Life Sciences End-use Outlook (Revenue, USD Million, 2018- 2030)

• Providers

• Payers

• Life Science Companies

• Others

NLP in Healthcare And Life Sciences Regional Outlook (Revenue, USD Million, 2018 - 2030)

• North America

• U.S.

• Canada

• Mexico

• Europe

  • Germany

  • UK

  • Spain

  • Italy

  • France

  • Denmark

  • Norway

  • Sweden

• Asia Pacific

  • Japan

  • China

  • India

  • Australia

  • Thailand

  • South Korea

• Latin America

  • Brazil

  • Argentina

• MEA

  • South Africa

  • Saudi Arabia

  • UAE

  • Kuwait

List of Key Players in the NLP in Healthcare and Life Sciences Market

• IBM

• Microsoft

• Google (Alphabet Inc.)

• IQVIA

• Dolbey Systems, Inc.

• Averbis

• Press ganey

• lexalytics

• Clinithink

• Hewlett Packard enterprise

• Apixio

• Edifecs

• JohnSnow Labs

• Itrex Group

• CloudMedx

• BenevolentAI

• Tempus