NLP In Healthcare And Life Sciences Market Size, Share & Trends Analysis Report By Technique (Smart Assistance, OCR), By End-use (Providers, Payers), By Region, And Segment Forecasts, 2024 - 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.
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.
Table of Contents
Chapter 1. Methodology and Scope
1.1. Market Segmentation and Scope
1.2. Market Definitions
1.3. Research Methodology
1.4. Information Procurement
1.4.1. Purchased Database
1.4.2. GVR's Internal Database
1.5. Details of primary research
1.6. Market Formulation & Validation
1.7. Model Details
1.7.1. Commodity flow analysis (Model 1)
1.7.1.1. Approach 1: Commodity flow approach
1.8. Research Scope and Assumptions
1.8.1. List of Secondary Sources
1.8.2. List of Primary Sources
1.8.3. Objectives
Chapter 2. Executive Summary
2.1. Market Outlook
2.2. Segment Outlook
2.2.1. Technique Outlook
2.2.2. End Use Outlook
2.3. Competitive Insights
Chapter 3. NLP in Healthcare and Life Sciences Market Variables, Trends, & Scope
3.1. Market Lineage Outlook
3.1.1. Parent Market Outlook
3.1.2. Related/Ancillary Market Outlook
3.2. Industry Analysis
3.2.1. User Perspective Analysis
3.2.2. Key End Users
3.3. Technology Outlook
3.4. Regulatory Framework
3.5. Market Dynamics
3.5.1. Market Drivers Analysis
3.5.2. Market Restraints Analysis
3.5.3. Industry Challenges and Opportunity Analysis
3.6. NLP in Healthcare and Life Sciences Market Analysis Tools
3.6.1. Porter's Analysis
3.6.1.1. Bargaining power of the suppliers
3.6.1.2. Bargaining power of the buyers
3.6.1.3. Threats of substitution
3.6.1.4. Threats from new entrants
3.6.1.5. Competitive rivalry
3.6.2. PESTEL Analysis
3.6.2.1. Political landscape
3.6.2.2. Economic and Social landscape
3.6.2.3. Technological landscape
3.6.2.4. Environmental landscape
3.6.2.5. Legal landscape
3.7. Major Deals & Strategic Alliances Analysis in the U.S. Healthcare Payers Core Administrative Processing Solutions Industry
3.8. Impact of COVID-19
3.9. Case Studies: Real-World Implementation Success Stories of NLP in Healthcare and Life Sciences Market
Chapter 4. NLP in Healthcare and Life Sciences Market: Technique Estimates & Trend Analysis
4.1. Definition and Scope
4.2. Technique Market Share Analysis, 2023 & 2030
4.3. Segment Dashboard
4.4. NLP in Healthcare and Life Sciences Market: By Technique, 2018 to 2030