Healthcare Natural Language Processing (NLP) Outsourcing Market

Global Healthcare Natural Language Processing (NLP) Outsourcing Market: Global Size, Trends, Competitive, and Historical & Forecast Analysis, 2023-2029- The market will expand due to the increasing demand for clinical documentation improvement, rising need for population health management, and increasing adoption of artificial intelligence and machine learning in healthcare.

Global Healthcare Natural Language Processing (NLP) Outsourcing Market is valued at USD 3.57 Billion in 2022 and it is expected to reach USD 9.69 Billion by 2029 with a CAGR of 18.1% over the forecast period.

Scope of Global Healthcare Natural Language Processing (NLP) Outsourcing Market Report-

Healthcare Natural Language Processing (NLP) outsourcing is a process where healthcare organizations outsource their NLP needs to third-party service providers. NLP involves the use of artificial intelligence and computational linguistics to process and analyze human language data. The healthcare industry has been an early adopter of NLP technology, as it has been instrumental in improving patient care, reducing healthcare costs, and enhancing clinical research.

The history of healthcare NLP outsourcing dates back to the 1980s when researchers started using NLP technology to improve patient care. Over the years, the technology has evolved significantly, and today, it is being used in various applications, including electronic health records (EHRs), clinical decision support systems (CDSS), and telemedicine, among others.

The applications of healthcare NLP outsourcing include clinical documentation improvement, revenue cycle management, clinical decision support, population health management, patient engagement, clinical research, telemedicine, and drug discovery. The end-users of healthcare NLP outsourcing include hospitals, clinics, ambulatory care centers, academic medical centers, pharmaceutical companies, and research institutes, among others.

Revenue Generation Model:

The revenue generation model for healthcare NLP outsourcing is primarily based on the volume of data processed and the complexity of the project. Service providers may charge on a per-record or per-document basis, or they may charge based on the complexity of the NLP task.

Supply Chain Model:

The supply chain model of healthcare NLP outsourcing involves service providers who offer NLP solutions, tools, and technologies to healthcare organizations. These service providers may work with technology vendors, data providers, and other stakeholders in the healthcare industry to deliver their solutions.

Value Chain Model:

The value chain model of healthcare NLP outsourcing includes various stages, including data acquisition, data preprocessing, data analysis, and data visualization. The value chain also includes service providers, technology vendors, healthcare organizations, and other stakeholders who are involved in the NLP process.

Covid-19 Impact on the Healthcare Natural Language Processing (NLP) Outsourcing market:

The Covid-19 pandemic has had a significant impacts on the healthcare NLP outsourcing market. On the one side, the pandemic has accelerated the adoption of digital health technologies, including NLP, as healthcare organizations have had to shift to remote care and telemedicine services. This has led to increased demand for NLP solutions that can help automate and streamline clinical documentation, improve patient care, and support clinical research.

However, the pandemic has also resulted in budget cuts for many healthcare organizations, leading to a slowdown in the adoption of new technologies. Additionally, the pandemic has disrupted supply chains and caused delays in the delivery of NLP solutions, leading to project cancellations and delays.

Key Players of Global Healthcare Natural Language Processing (NLP) Outsourcing Market Report-

• Cognizant
• 3M
• IBM
• Dolbey
• Nuance Communications
• Clinithink
• Linguamatics
• Health Fidelity
• nThrive
• Flatiron Health
• Apixio
• Medisolv
• MedCPU
• Artificial Medical Intelligence
• Averbis
• Cureatr
• Deep 6 AI
• Health Catalyst
• HealthLytix
• HealthVerity
• John Snow Labs
• MieRADIAN
• Prognos Health
• Suki.AI
• Symcat
• Viz.ai
• Zephyr Health
• Hiteks Solutions
• I2E
• MeVis Medical Solutions
• Proximie
• Savience
• Saykara
• Veracity.ai
• Vynca
• Zocdoc
• and others.

Global Healthcare Natural Language Processing (NLP) Outsourcing Market Segmentation:-

By Service:

• Machine Translation
• Information Extraction
• Text and Voice Processing
• Others

By Component:

• Solution
• Services

By End-User:

• Hospitals
• Clinics and Healthcare Providers
• Research Institutes and Academic Centers
• Others

By Regional & Country Level:

• North America
  • S.
  • Canada
• Europe
  • K.
  • France
  • Germany
  • Italy
• Asia Pacific
  • China
  • Japan
  • India
  • Southeast Asia
• Latin America
  • Brazil
  • Mexico
• Middle East and Africa
  • GCC
  • Africa
  • Rest of Middle East and Africa

Market Drivers:

Increasing demand for clinical documentation improvement: Clinical documentation improvement (CDI) is a process aimed at enhancing the accuracy and completeness of patient medical records. It involves reviewing clinical documentation to ensure that it accurately reflects the patient's condition and treatment, and to identify any gaps or inconsistencies. The increasing demand for CDI is being driven by various factors, including the growing emphasis on quality reporting and value-based care, the need to reduce medical errors and adverse events, and the increasing adoption of electronic health records (EHRs) and other health IT solutions.

CDI can also help improve patient outcomes, reduce healthcare costs, and support clinical research. For example; according to the Health Care Payment Learning and Action Network, the percentage of healthcare payments tied to value-based care increased from 23% in 2015 to 34% in 2018 and is projected to reach 59% by 2023.

Rising need for population health management: Rising need for population health management is driven by several factors, including the increasing prevalence of chronic diseases, aging populations, and rising healthcare costs. Population health management focuses on improving the health outcomes of entire populations, rather than just individual patients, by analyzing and addressing the social determinants of health, implementing preventive measures, and promoting healthy behaviors.

With the increasing burden of chronic diseases, such as diabetes and cardiovascular diseases, population health management has become a critical tool for healthcare organizations to improve health outcomes, reduce healthcare costs, and enhance patient satisfaction. The global economic burden of chronic diseases is estimated to be around $47 trillion over the next 20 years, according to a report by the World Economic Forum.

Additionally, advances in healthcare analytics and data-driven technologies, such as NLP, have made it easier for healthcare organizations to implement population health management strategies.

Market Restraints:

Lack of skilled workforce in healthcare NLP: NLP requires a combination of expertise in both healthcare and natural language processing, which is a highly specialized field. There is a shortage of professionals with the necessary skills and knowledge, which has led to a talent gap in the industry. As a result, healthcare organizations are finding it difficult to implement NLP solutions, and the shortage of skilled professionals has also led to high labor costs for those with the necessary expertise.

For example; a 2019 report by Burning Glass Technologies found that there is a shortage of qualified candidates for nearly 40% of healthcare NLP job openings. Additionally, a survey by Healthcare IT News found that 67% of healthcare organizations struggle with hiring qualified data analytics and NLP professionals. This lack of skilled workforce is expected to hinder the growth of the healthcare NLP outsourcing market in the coming years.

Security and privacy concerns related to patient data: The sensitive nature of patient data, including personal and medical information, means that healthcare organizations must take great care to protect it from cyber threats and unauthorized access. The use of NLP solutions to analyze and process patient data raises concerns about the security of that data, particularly in light of the increasing frequency of data breaches and cyber-attacks.

Additionally, the healthcare sector was one of the most targeted industries, with 616 data breaches reported in 2020, accounting for 55.5% of all reported breaches. Moreover, regulations such as HIPAA impose strict requirements for the protection of patient data, which can add complexity and cost to NLP outsourcing projects.

Opportunity Factors:

• Increasing adoption of artificial intelligence (AI) and machine learning (ML) in healthcare.
• Growing demand for personalized medicine and precision health.
• Rising need for clinical decision support systems (CDSS) and clinical trial optimization.
• Expansion of telemedicine and remote patient monitoring services.
• Advancements in voice recognition and natural language understanding (NLU) technologies.

Market Trend:

Product and Technology Development:

There are several trends driving product and technology development in the healthcare NLP outsourcing market. One trend is the increasing use of cloud-based NLP solutions, which offer scalability, flexibility, and cost-effectiveness. Another trend is the integration of NLP with other AI and ML technologies, such as computer vision and predictive analytics, to improve accuracy and efficiency. Additionally, there is a growing emphasis on developing NLP solutions that can support real-time clinical decision-making and automate repetitive administrative tasks.

Customer Trends:

Customer trends in the healthcare NLP outsourcing market are being shaped by a variety of factors, including the need for improved patient outcomes, increased efficiency, and reduced costs. One trend is the growing demand for NLP solutions that can improve the accuracy and completeness of clinical documentation, which can improve patient care and reduce the risk of adverse events. Another trend is the increasing use of NLP to support population health management and disease surveillance, which can help healthcare organizations identify and address health disparities and emerging health threats.

Market Competition Nature:

The healthcare NLP outsourcing market is highly competitive, with numerous players offering a wide range of NLP solutions and services. Some of the key players in the market include 3M, Cerner Corporation, Nuance Communications, and Dolbey Systems, Inc.

To remain competitive, key market players are focusing on developing innovative NLP solutions that can address specific healthcare challenges, such as clinical documentation improvement and population health management. These are also investing in partnerships and collaborations with other healthcare technology providers to expand their offerings and reach new markets.

Additionally, market players are expanding their global presence through strategic acquisitions and partnerships, and by investing in research and development to stay ahead of emerging trends and technologies in the healthcare NLP outsourcing market.

Geography Analysis:

North America:

In North America, the United States is the largest market for healthcare NLP outsourcing, driven by factors such as the presence of major NLP vendors, high healthcare spending, and the growing demand for value-based care. Additionally, a survey by the National Association of ACOs found that accountable care organizations (ACOs), which are a type of value-based care model, have become increasingly popular in North America. In 2020, there were 559 ACOs operating across the United States, covering more than 12.3 million Medicare beneficiaries.

The region has a well-established healthcare system and a high level of awareness about the benefits of NLP solutions, which is expected to continue driving growth in the market. Additionally, the Covid-19 pandemic has accelerated the adoption of NLP solutions in North America, particularly for applications such as telemedicine and remote patient monitoring.

Europe:

Europe is also a significant market for healthcare NLP outsourcing, driven by the region's highly developed healthcare infrastructure, the presence of several major healthcare IT companies, and increasing government initiatives to improve patient outcomes and reduce healthcare costs.

The growing demand for NLP solutions to support clinical documentation, population health management, and clinical decision-making is also driving market growth in the region. For example; the UK's NHS Long Term Plan includes a focus on population health management, with a goal to prevent 150,000 heart attacks, strokes, and dementia cases by 2029.

Key Benefits of Global Healthcare Natural Language Processing (NLP) Outsourcing Market Report–

• Global Healthcare Natural Language Processing (NLP) Outsourcing Market report covers in-depth historical and forecast analysis.
• Global Healthcare Natural Language Processing (NLP) Outsourcing Market research report provides detailed information about Market Introduction, Market Summary, Global market Revenue (Revenue USD), Market Drivers, Market Restraints, Market Opportunities, Competitive Analysis, and Regional and Country Level.
• Global Healthcare Natural Language Processing (NLP) Outsourcing Market report helps to identify opportunities in the marketplace.
• Global Healthcare Natural Language Processing (NLP) Outsourcing Market report covers extensive analysis of emerging trends and competitive landscape.